Evaluation method and device for periodic irregularity of simply supported beam

Abstract

The invention discloses a method and device for evaluating periodical irregularity of a simply supported beam, and the method comprises the steps: extracting a low-frequency signal representing the periodical irregularity of the simply supported beam from track height irregularity data through employing a wavelet decomposition technology; identifying trough data representing unevenness of the simply supported beam from the low-frequency signal; based on the periodic irregularity characteristic wavelength of the simply supported beam, screening out sections with periodic irregularity of the simply supported beam according to the trough data; according to the vehicle dynamics response data when the train passes through each section, the periodical irregularity level of the simply supported beam of each section is determined; the periodical irregularity grade of the simply supported beam is used for representing the influence degree of periodical irregularity of the simply supported beam on the track structure state and the train operation comfort. The method is used for carrying out automatic identification and quantitative evaluation on the periodic irregularity of the simply supported beam, and the identification precision and accuracy of the periodic irregularity of the simply supported beam are improved.

Description

Technical Field

[0001] The invention relates to the technical field of railway track detection, and in particular to a method and a device for evaluating periodic irregularity of a simply supported beam. Background Art

[0002] This section is intended to provide a background or context for the presented embodiments of the invention. No description herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] At present, prestressed concrete simply supported beam bridges are mostly used in the line foundation structure of high-speed railways. Due to the influence of concrete creep, existing high-speed railway simply supported beam bridges generally have mid-span arch deformation, which is mapped to the track surface to form periodic high and low unevenness. This periodic unevenness will cause periodic forced vibration of high-speed trains during operation, and the frequency is low, which increases the low-frequency force of the wheel and rail, and has an adverse effect on the service status of the track structure. At the same time, this periodic unevenness will also cause periodic vertical vibration when the train passes, causing discomfort to passengers. Therefore, it is urgent to develop a method for identifying and evaluating the periodic unevenness of simply supported beams based on track geometry and vehicle dynamic response detection data, find out the sections with poor periodic unevenness of simply supported beams and intervene in advance.

[0004] The existing technology has the following problems in identifying and evaluating the periodic irregularity of simply supported beams:

[0005] 1. Identification accuracy problem: Traditional methods are difficult to accurately extract the characteristic components of periodic irregularities of simply supported beams, and are easily interfered by short-wave irregularities, resulting in inaccurate identification results. For example, although bandpass filtering technology can extract periodic components, it will cause the periodic irregularity characteristics to spread to non-periodic irregularity sections, and the peak and trough amplitudes after filtering will be homogenized, resulting in a large number of missed and misjudgments.

[0006] 2. Classification accuracy problem: Traditional recognition methods are difficult to accurately distinguish the periodic irregularities of simply supported beams of different spans, and are prone to misjudgment and missed detection.

[0007] 3. Severity evaluation problem: When the amplitude of high and low irregularities does not exceed the maintenance management limit, there is a lack of mature methods to evaluate the severity of the periodic irregularities of simply supported beams, making it difficult to guide the railway department when to intervene in maintenance. Traditional evaluation methods fail to fully consider the vehicle dynamic response and cannot fully reflect the impact of the periodic irregularities of simply supported beams on train operation safety and ride comfort. Summary of the invention

[0008] The embodiment of the present invention provides a method for evaluating the periodic irregularity of a simply supported beam, which is used to automatically identify and quantitatively evaluate the periodic irregularity of a simply supported beam, thereby improving the identification precision and accuracy of the periodic irregularity of a simply supported beam. The method includes:

[0009] Wavelet decomposition technology is used to extract low-frequency signals representing the periodic irregularity of simply supported beams from track height irregularity data.

[0010] Identify the trough data representing the height irregularity of the simply supported beam from the low-frequency signal;

[0011] Based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are screened out according to the trough data;

[0012] The periodic irregularity grade of the simply supported beam in each section is determined according to the vehicle dynamics response data when the train passes through each section; the periodic irregularity grade of the simply supported beam is used to characterize the influence of the periodic irregularity of the simply supported beam on the track structure state and the train running comfort.

[0013] The embodiment of the present invention further provides a device for evaluating the periodic irregularity of a simply supported beam, which is used to automatically identify and quantitatively evaluate the periodic irregularity of a simply supported beam, thereby improving the identification precision and accuracy of the periodic irregularity of a simply supported beam. The device includes:

[0014] The low-frequency signal extraction module is used to extract the low-frequency signal representing the periodic irregularity of the simply supported beam from the track height irregularity data by using wavelet decomposition technology;

[0015] The trough data recognition module is used to identify the trough data representing the unevenness of the simply supported beam from the low-frequency signal;

[0016] A section screening module, for screening different sections of the periodic irregularity of the simply supported beam according to the trough data based on the characteristic wavelength of the periodic irregularity of the simply supported beam;

[0017] The module for determining the periodic irregularity grade of a simply supported beam is used to determine the periodic irregularity grade of a simply supported beam in each section according to the vehicle dynamics response data when the train passes through each section; the periodic irregularity grade of a simply supported beam is used to characterize the degree of influence of the periodic irregularity of a simply supported beam on the track structure state and the train running comfort.

[0018] An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for evaluating the periodic irregularity of a simply supported beam when executing the computer program.

[0019] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for evaluating the periodic irregularity of a simply supported beam is implemented.

[0020] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned method for evaluating the periodic irregularity of a simply supported beam is implemented.

[0021] In an embodiment of the present invention, wavelet decomposition technology is used to extract a low-frequency signal representing the periodic unevenness of a simply supported beam from track height unevenness data; trough data representing the height unevenness of a simply supported beam is identified from the low-frequency signal; based on the characteristic wavelength of the periodic unevenness of the simply supported beam, different sections of the periodic unevenness of the simply supported beam are screened out according to the trough data; based on the vehicle dynamics response data when a train passes through each section, the periodic unevenness grade of the simply supported beam in each section is determined; the periodic unevenness grade of the simply supported beam is used to characterize the degree of influence of the periodic unevenness of the simply supported beam on the track structure state and the train running comfort. The embodiment of the present invention uses wavelet decomposition technology to extract low-frequency signals containing periodic characteristics of simply supported beams from track height unevenness data, which can effectively retain the periodic components of simply supported beams, improve the recognition accuracy of periodic unevenness of simply supported beams, and avoid interference from short-wave unevenness components; based on the characteristic wavelength of periodic unevenness of simply supported beams, different sections of periodic unevenness of simply supported beams are screened out according to identified trough data, and simply supported beams of different spans can be accurately distinguished, avoiding the problems of missed judgment and misjudgment caused by the use of bandpass filtering technology under the prior art; according to the vehicle dynamics response data when the train passes through each section, the periodic unevenness levels of simply supported beams in different sections can be quantitatively evaluated, and the severity of periodic unevenness of simply supported beams can be comprehensively evaluated, providing a scientific basis for repair and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0023] Figure 1 This is a schematic diagram showing the unevenness of the center line of a 350 km / h ballastless high-speed railway in an embodiment of the present invention;

[0024] Figure 2 It is a schematic diagram showing the bandpass filtering effect of the unevenness of the center line according to the wavelength of 30-35m in the embodiment of the present invention;

[0025] Figure 3 A schematic diagram showing wavelet decomposition levels and corresponding wavelength ranges in an embodiment of the present invention;

[0026] Figure 4a A schematic diagram showing raw data of high and low unevenness in an embodiment of the present invention;

[0027] Figure 4b This is a schematic diagram showing the low-frequency components obtained by one-layer wavelet decomposition in an embodiment of the present invention;

[0028] Figure 4c A schematic diagram showing low-frequency components obtained by two-layer wavelet decomposition in an embodiment of the present invention;

[0029] Figure 4d A schematic diagram showing low-frequency components obtained by three-layer wavelet decomposition in an embodiment of the present invention;

[0030] Figure 4e A schematic diagram showing low-frequency components obtained by 4-layer wavelet decomposition in an embodiment of the present invention;

[0031] Figure 4f A schematic diagram showing low-frequency components obtained by 5-layer wavelet decomposition in an embodiment of the present invention;

[0032] Figure 4g A schematic diagram showing low-frequency components obtained by 6-layer wavelet decomposition in an embodiment of the present invention;

[0033] Figure 5 It is a schematic diagram comparing the high and low uneven low frequency components of 5-layer decomposition of different wavelet bases in an embodiment of the present invention;

[0034] Figure 6 It is a schematic diagram showing the frequency distribution of the intervals between adjacent troughs of low-frequency components decomposed by wavelet and the intervals between adjacent troughs of original high and low unevenness in an embodiment of the present invention;

[0035] Figure 7 It is a schematic diagram showing the preliminary screening of periodic irregularities of 32m and 23m simply supported beams based on characteristic wavelengths in an embodiment of the present invention;

[0036] Figure 8a It is a schematic diagram showing the unevenness of the trough problem near the mid-span of the same hole beam in an embodiment of the present invention;

[0037] Figure 8b A schematic diagram showing the adjacent trough intervals for the trough problem near the mid-span of the same hole beam in an embodiment of the present invention;

[0038] Figure 9a A schematic diagram showing the unevenness of the beam length identification error of a 32m simply supported beam in an embodiment of the present invention;

[0039] Figure 9b A schematic diagram showing the adjacent trough intervals for the 32m simply supported beam length identification error problem in an embodiment of the present invention;

[0040] Fig.10 It is a schematic diagram showing the final recognition result of the interval distance between adjacent troughs after supplementary recognition in an embodiment of the present invention;

[0041] Fig.11 A schematic diagram showing the supplementary identification results of the intermediate beam gap problem of two consecutive 32m simply supported beams in an embodiment of the present invention;

[0042] Fig.12a It is a schematic diagram showing the high and low unevenness of the periodic unevenness of the simply supported beam in the section K302+600-K304+500 in an embodiment of the present invention;

[0043] Figure 12b It is a schematic diagram showing the interval distance between adjacent troughs of periodic unevenness of a simply supported beam in the section K302+600-K304+500 in an embodiment of the present invention;

[0044] Fig.13 It is a schematic diagram of a method for calculating the camber amount of periodic unevenness of a simply supported beam in an embodiment of the present invention;

[0045] Fig.14a It is a schematic diagram showing the relationship between the vertical acceleration peak value of the simply supported beam vehicle body of a ballastless track and the camber of the simply supported beam in an embodiment of the present invention;

[0046] Fig.14b It is a schematic diagram showing the relationship between the peak value of the vertical acceleration of the simply supported beam vehicle body on a ballasted track and the camber of the simply supported beam in an embodiment of the present invention;

[0047] Fig.15 It is a schematic diagram showing the relevant data near the beam joint when a 32m simply supported beam section has periodic unevenness in an embodiment of the present invention;

[0048] Fig.16 It is a schematic diagram showing a situation in which a certain simply supported beam section has continuous multiple waves of height irregularities exceeding the limit in an embodiment of the present invention;

[0049] Fig.17 is a schematic diagram of a frequency correction coefficient curve in an embodiment of the present invention;

[0050] Fig.18a It is a schematic diagram showing the unevenness of a certain section based on the evaluation result of the vertical stability index in an embodiment of the present invention;

[0051] Fig.18bIt is a schematic diagram showing the vertical acceleration of a vehicle body in a certain section based on the evaluation result of the vertical stability index in an embodiment of the present invention;

[0052] Fig.18c It is a schematic diagram showing the vertical stability index situation of a certain section based on the evaluation result of the vertical stability index in an embodiment of the present invention;

[0053] Fig.19 It is a schematic flow chart of a method for evaluating periodic irregularity of a simply supported beam in an embodiment of the present invention;

[0054] Fig. 20 It is a structural schematic diagram of a device for evaluating periodic irregularity of a simply supported beam in an embodiment of the present invention;

[0055] Fig.21 Schematic diagram of a computer device for evaluating the periodic irregularity of a simply supported beam in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0057] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0058] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps is not limited and can be appropriately adjusted as needed.

[0059] The acquisition, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations. The information collected in this application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure, and application of relevant data are in compliance with the relevant laws, regulations, and standards of relevant countries and regions, and necessary confidentiality measures are taken, which do not violate public order and good customs, and provide corresponding operation entrances for users to choose to authorize or refuse. In addition, this application provides users with corresponding operation entrances for users to choose to agree or refuse the results of automated decision-making. If the user chooses to refuse, they can enter the expert decision-making process.

[0060] It should be noted that in the embodiments of the present application, some existing solutions in the industry such as certain software, components, models, etc. may be mentioned. For example, some existing software tools, components, algorithm models or other well-known solutions in other technical fields may be cited. They should be considered as exemplary, and their purpose is only to illustrate the feasibility of the implementation of the technical solution of the present application. These references should be understood as typical examples, and their core purpose is to explain and verify the rationality and feasibility of the implementation of the technical solution proposed in the present application. However, it does not mean that the applicant has or will inevitably use the solution. Such references do not imply that the applicant has actually adopted these existing solutions, or will inevitably adopt these methods in the future during its technical implementation. In other words, these references only serve to illustrate the nature of the description, to help understand the connection and transcendence between the innovation of the present application and the prior art, and do not constitute an endorsement or reliance statement on a specific prior art product.

[0061] At present, the foundation structure of high-speed railway lines mostly adopts prestressed concrete simply supported beam bridges. Due to the influence of concrete creep, existing high-speed railway simply supported beam bridges generally have mid-span arch deformation, which is mapped to the track surface to form periodic high and low unevenness. This causes periodic forced vibrations in the operation of high-speed trains with low frequency, increases the low-frequency force of the wheel and rail, and has an adverse effect on the service state of the track structure. At the same time, it causes periodic vertical vibrations when the train passes, causing discomfort to passengers. Therefore, it is urgent to develop a method for identifying and evaluating the periodic unevenness of simply supported beams based on track geometry and vehicle dynamic response detection data, find out the sections with poor periodic unevenness of simply supported beams and intervene in advance, which has a good prospect for engineering application.

[0062] The characteristic wavelength of the periodic unevenness of a simply supported beam is basically consistent with the center distance of the bridge pier, that is, the sum of the total length of the beam and the width of the beam gap. Existing high-speed railway simply supported beams mainly have four spans of 20, 24, 32 and 40m. Among them, the 32m simply supported beam is the most commonly used, followed by the 24m simply supported beam. The 20m and 40m simply supported beams are less frequently laid, so the identification objects are mainly the periodic unevenness of 32m and 24m simply supported beams. The 32m simply supported beam has a total length of 32.6m and a beam gap of 10cm. The characteristic wavelength of the periodic unevenness caused by it is about 32.7m; the 24m simply supported beam has a total length of 24.6m and a beam gap of 10cm. The characteristic wavelength of the periodic unevenness caused by it is about 24.7m. Therefore, the identification of periodic unevenness of simply supported beams should focus on wavelengths of 32.7m and 24.7m.

[0063] The present invention proposes a method and device for identifying and evaluating the periodic irregularity of a simply supported beam. The method identifies the periodic irregularity of a simply supported beam based on the high and low irregularities. On this basis, the vehicle dynamics response is integrated to evaluate the periodic irregularity of the simply supported beam and select the sections that need priority attention. It can be foreseen that the intelligent method for identifying and evaluating the periodic irregularity of a simply supported beam will further improve the maintenance management efficiency of this typical smoothness problem and provide technical support for maintaining the high smoothness of high-speed railway tracks and rationally formulating maintenance and repair plans.

[0064] In order to solve the above problems, an embodiment of the present invention provides a method for evaluating the periodic irregularity of a simply supported beam, which is used to automatically identify and quantitatively evaluate the periodic irregularity of a simply supported beam, thereby improving the identification precision and accuracy of the periodic irregularity of a simply supported beam. Fig.19 , the method may include:

[0065] Step 1901: using wavelet decomposition technology to extract low-frequency signals representing periodic irregularities of simply supported beams from track height irregularities data;

[0066] Step 1902: Identify trough data representing the unevenness of the simply supported beam from the low-frequency signal;

[0067] Step 1903: based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are selected according to the trough data;

[0068] Step 1904: Determine the periodic irregularity grade of the simply supported beam in each section according to the vehicle dynamic response data when the train passes through each section; the periodic irregularity grade of the simply supported beam is used to characterize the influence of the periodic irregularity of the simply supported beam on the track structure state and the train running comfort.

[0069] In an embodiment of the present invention, wavelet decomposition technology is used to extract a low-frequency signal representing the periodic unevenness of a simply supported beam from track height unevenness data; trough data representing the height unevenness of a simply supported beam is identified from the low-frequency signal; based on the characteristic wavelength of the periodic unevenness of the simply supported beam, different sections of the periodic unevenness of the simply supported beam are screened out according to the trough data; based on the vehicle dynamics response data when a train passes through each section, the periodic unevenness grade of the simply supported beam in each section is determined; the periodic unevenness grade of the simply supported beam is used to characterize the degree of influence of the periodic unevenness of the simply supported beam on the track structure state and the train running comfort. The embodiment of the present invention uses wavelet decomposition technology to extract low-frequency signals containing periodic characteristics of simply supported beams from track height unevenness data, which can effectively retain the periodic components of simply supported beams, improve the recognition accuracy of periodic unevenness of simply supported beams, and avoid interference from short-wave unevenness components; based on the characteristic wavelength of periodic unevenness of simply supported beams, different sections of periodic unevenness of simply supported beams are screened out according to identified trough data, and simply supported beams of different spans can be accurately distinguished, avoiding the problems of missed judgment and misjudgment caused by the use of bandpass filtering technology under the prior art; according to the vehicle dynamics response data when the train passes through each section, the periodic unevenness levels of simply supported beams in different sections can be quantitatively evaluated, and the severity of periodic unevenness of simply supported beams can be comprehensively evaluated, providing a scientific basis for repair and maintenance.

[0070] In the specific implementation, step 101 is first performed: using wavelet decomposition technology, a low-frequency signal representing the periodic unevenness of a simply supported beam is extracted from track height unevenness data.

[0071] In the embodiment, wavelet decomposition technology is used to extract low-frequency signals representing the periodic unevenness of simply supported beams from track height unevenness data, including:

[0072] Wavelet decomposition technology is used to perform multi-level decomposition on the track unevenness data based on a preset number of wavelet decomposition layers, and a low-frequency signal characterizing the periodic unevenness of a simply supported beam is extracted; the multi-level decomposition is used to smooth the short-wave signals in the track unevenness data.

[0073] In the above embodiment, the present invention uses wavelet decomposition technology to extract low-frequency signals representing the periodic irregularity of simply supported beams from track irregularity data. The process involves performing multi-level step-by-step decomposition of track irregularity data based on a preset number of wavelet decomposition layers, thereby achieving smooth processing of shortwave signals and extracting the required low-frequency signals. The specific operations are as follows:

[0074] 1. Determine the number of wavelet decomposition layers

[0075] According to the analysis of the characteristic wavelength of periodic irregularity of simply supported beams and the wavelength range covered by high and low irregularity data, the appropriate number of wavelet decomposition layers is determined. Since the characteristic wavelength of periodic irregularity of simply supported beams is 32.7m (32m simply supported beam) and 24.7m (24m simply supported beam), and the wavelength components covered by high and low irregularity are 1.5-42m, it is found that when the decomposition level reaches the fifth level, the low-frequency signal can retain the wavelength components above 16m. This range can effectively cover the characteristic wavelength of simply supported beams and can better suppress short-wave irregularity components. Therefore, it is determined to use 5 layers of wavelet decomposition.

[0076] 2. Perform multi-level decomposition

[0077] Wavelet decomposition is the process of decomposing the original signal into sub-signals of different frequency bands. For track unevenness data, it is sampled at equal spatial intervals of 0.25m, and the sampling frequency is 4m. -1 In the wavelet decomposition, by selecting a suitable wavelet basis (for example, the bior4.4 wavelet basis is selected after comparison in the present invention), the high and low unevenness data are decomposed at multiple levels.

[0078] In the 1-6 layer wavelet decomposition process, as the decomposition level increases, the short-wave components in the original high and low roughness are gradually smoothed out. For example, after the decomposition level reaches 6 layers, the periodic components at both ends of the simply supported beam section are filtered out, and when decomposed to the 5th layer, the periodic components of the simply supported beam can be well preserved, and the short-wave roughness components can also be effectively suppressed, thus verifying the rationality and effectiveness of the 5-layer wavelet decomposition.

[0079] 3. Extract low-frequency signals

[0080] After 5 layers of wavelet decomposition, bandpass signals and low-frequency signals of different bands are obtained. The low-frequency signal is the signal part that can characterize the periodic unevenness of the simply supported beam. This low-frequency signal retains the wavelength component of 16-42m, including the characteristic wavelength of the periodic unevenness of the simply supported beam, which provides a key data basis for the subsequent accurate identification of the periodic unevenness of the simply supported beam, and helps to further analyze and judge the status of the track structure, thereby providing strong support for railway track inspection and maintenance.

[0081] In specific implementation, after performing step 101: using wavelet decomposition technology to extract low-frequency signals representing periodic unevenness of simply supported beams from track unevenness data, step 102 is performed: identifying trough data representing unevenness of simply supported beams from the low-frequency signals.

[0082] In one embodiment, it further includes:

[0083] The original roughness adjacent trough intervals are pre-calculated as follows:

[0084] Extract the minimum point from the low-frequency signal as the first low-frequency sampling point;

[0085] Eliminate the sampling points that are not in the bridge section from the first sampling points to obtain the second low-frequency sampling points;

[0086] Retaining the sampling points whose absolute amplitude values ​​among the second sampling points are greater than the preset first threshold as the third low-frequency sampling points;

[0087] For each third low-frequency sampling point, the minimum value point of the track height irregularity data within a preset adjacent wavelength range of the third low-frequency sampling point is recorded as an original sampling point;

[0088] Calculate the distance between adjacent sampling points of the original sampling points to obtain the interval between adjacent troughs of the original high and low roughness;

[0089] Identify the trough data that characterizes the unevenness of the simply supported beam from the low-frequency signal, including:

[0090] When the trough intervals of adjacent signals in the low-frequency signal exceed the pre-calculated adjacent trough intervals of the original height irregularity, the data of the adjacent signals are used as the identified trough data representing the height irregularity of the simply supported beam.

[0091] Take the example of "identifying the trough data representing the unevenness of a simply supported beam from a low-frequency signal", which includes the following operations:

[0092] 1. Pre-calculate the interval between adjacent troughs of the original unevenness

[0093] 1. Extract the minimum point from the low-frequency signal as the first low-frequency sampling point

[0094] First, the high and low frequency components of unevenness obtained by bior4.4 wavelet 5-layer decomposition are used as the basis. In this low frequency component, all minimum points are found by using the corresponding algorithm or calculation logic. These minimum points together constitute the first low frequency sampling point set. These minimum points reflect the local minimum state of unevenness in the low frequency signal to a certain extent, which is the basis for further screening.

[0095] 2. Eliminate the sampling points that are not in the bridge section from the first sampling points to obtain the second low-frequency sampling points

[0096] The bridge summary table in the LKJ account of the introduction line covers key information such as the central mileage and total length of all bridges, including existing simply supported beam bridges, culverts, continuous beams and other large-span bridges. The first low-frequency sampling point set is screened based on the starting and ending mileage information of the bridge in the bridge account. The sampling points in the non-bridge section are removed from the set. After this operation, the remaining sampling point set is the second low-frequency sampling point set. This step aims to exclude interference data in non-bridge sections and focus on sampling points in the bridge section that may be related to the periodic irregularity of the simply supported beam.

[0097] 3. Retain the sampling points whose absolute amplitude values ​​in the second sampling points are greater than the preset first threshold as the third low-frequency sampling points

[0098] For each sampling point in the second low-frequency sampling point set, obtain its absolute amplitude value. Compare the absolute amplitude value with the preset first threshold. Only the sampling points whose absolute amplitude value is greater than the first threshold are retained, and these retained sampling points constitute the third low-frequency sampling point set. The amplitude of the trough of the periodic irregularity of simply supported beams is usually large. By setting an appropriate first threshold (such as the threshold specified according to the actual situation mentioned in the briefing book), it is possible to further screen out the sampling points that are more likely to be related to the periodic irregularity of simply supported beams, and exclude some sampling points with smaller amplitudes that may belong to other types of bridge sections (such as other span simply supported beams, culverts or large span bridges, etc.) or simply supported beam bridges with better track smoothness after fine-tuning. These situations are not the focus of the identification target of the periodic irregularity of simply supported beams in the present invention.

[0099] 4. Get the original sampling point for each third low-frequency sampling point and calculate the interval between adjacent troughs of the original high and low irregularity

[0100] For each sampling point in the third low-frequency sampling point set, in the track roughness data, with the sampling point as the center, search for the minimum point within its preset proximity (such as within a certain distance range near the sampling point mentioned in the briefing book, and the distance is set according to the actual situation). These minimum points found in the track roughness data are the original sampling points. Then, calculate the distance between the adjacent sampling points of these original sampling points. The set of these distances is the set of adjacent trough intervals of the original roughness. Through this step, the sampling points obtained by preliminary screening based on the low-frequency signal can be converted to the original roughness data to obtain more accurate adjacent trough interval information, providing a basis for subsequent judgment.

[0101] 2. Identify the trough data representing the unevenness of simply supported beams from low-frequency signals

[0102] After obtaining the original adjacent trough interval set of height irregularity, the trough interval of the adjacent signal in the low-frequency signal is calculated. The trough interval is compared with the value in the pre-calculated original adjacent trough interval set of height irregularity. When the trough interval exceeds the value in the set, the data of the adjacent signal is determined as the identified trough data characterizing the height irregularity of the simply supported beam.

[0103] For example, if the trough interval between two adjacent signals in the low-frequency signal is significantly larger than the normal adjacent trough interval range obtained by statistics in the original high and low unevenness data, this most likely means that there are characteristics related to the periodic unevenness of the simply supported beam. Therefore, the data of these two adjacent signals are used as important trough data for subsequent processing, such as further identification and classification of periodic unevenness of simply supported beams, providing key data support for accurate assessment of the track structure status.

[0104] In specific implementation, after performing step 102: identifying trough data characterizing the height unevenness of the simply supported beam from the low-frequency signal, step 103 is performed: based on the characteristic wavelength of the periodic unevenness of the simply supported beam, different sections of the periodic unevenness of the simply supported beam are screened out according to the trough data.

[0105] In one embodiment, based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are screened out according to the trough data, including:

[0106] Determine a first beam length recognition range of a first simply supported beam periodic irregularity type and a second beam length recognition range of a second simply supported beam periodic irregularity type according to a characteristic wavelength of a simply supported beam periodic irregularity and recognition errors of different preset characteristic wavelengths;

[0107] For each trough data, if the adjacent trough interval of the original high and low irregularities corresponding to the trough data is within the first beam length identification range or the second beam length identification range, it is identified that the trough data at this location has periodic irregularities of a simply supported beam;

[0108] The trough data at the location where the simply supported beam has periodic irregularities is taken as the screened section of the simply supported beam with periodic irregularities; the trough data at the location where the simply supported beam has no periodic irregularities is taken as the undetermined section.

[0109] In the embodiment, for the 32m simply supported beam periodic irregularity type (the first simply supported beam periodic irregularity type):

[0110] The characteristic wavelength of the periodic irregularity of the 32m simply supported beam is preset to 32.7m (obtained by adding the total length of the beam 32.6m and the beam gap 10cm). Taking into account the errors that may occur during the actual measurement and data processing, the recognition error is preset to a certain value (the value is determined according to the actual situation and the measurement accuracy requirements). Based on this, the first beam length recognition range is determined to be from 32.7 minus the recognition error to 32.7 plus the recognition error. The purpose of this determination is to accurately identify the possible periodic irregularities of the 32m simply supported beam during subsequent screening. The definition of this range fully combines the structural characteristics of the 32m simply supported beam and the measurement error factor.

[0111] In the embodiment, for the periodic irregularity type of a 24m simply supported beam (the second periodic irregularity type of a simply supported beam):

[0112] The characteristic wavelength of the periodic irregularity of a 24m simply supported beam is preset to 24.7m (the sum of the total beam length of 24.6m and the beam gap of 10cm). Similarly, the identification error is set in combination with the actual situation (the error value is determined according to the actual situation), and then the second beam length identification range is determined to be the interval from 24.7 minus the identification error to 24.7 plus the identification error. By reasonably setting the identification range, a judgment basis is provided for accurately screening the periodic irregularity section of a 24m simply supported beam.

[0113] In the embodiment, for each trough data identified from the low-frequency signal, the corresponding original adjacent trough interval of high and low unevenness is obtained. The original adjacent trough interval of high and low unevenness is compared with the first beam length identification range (interval from the minimum value to the maximum value) and the second beam length identification range (interval from the minimum value to the maximum value) determined above.

[0114] If the interval between adjacent troughs of the original high and low unevenness is within the first beam length identification range or the second beam length identification range, then it can be identified that the trough data has periodic unevenness of the simply supported beam. At this time, the trough data is identified as the selected section of periodic unevenness of the simply supported beam, and further analysis and processing can be carried out on these sections, such as evaluating their impact on the track structure and train operation.

[0115] If the interval between adjacent troughs of the original high and low unevenness is not within the above two beam length identification ranges, the trough data will be used as a pending section. For the pending section, further inspection or other auxiliary methods can be used for judgment according to actual needs to ensure the accuracy and completeness of the identification of periodic unevenness of simply supported beams, avoid missing sections that may have problems, and thus provide reliable protection for the safe maintenance of railway tracks and the stable operation of trains.

[0116] In one embodiment, in order to solve the problem of missed detection caused by the presence of troughs near the mid-span of the same hole beam: sum the intervals between the troughs of two adjacent suspected non-simply supported beam periodic irregularities. When the sum of the intervals between two adjacent troughs is within the corresponding beam length (32m or 24m) beam length recognition range, it is determined that there is still a simply supported beam periodic irregularity of the corresponding beam length, and other troughs of suspected non-simply supported beam periodic irregularities are extracted again for subsequent processing.

[0117] In one embodiment, in order to solve the missed detection caused by the error in the identification of the beam length of a 32m simply supported beam: a looser beam length identification range is specified. When the distance between adjacent points of the suspected non-simply supported beam periodic irregularity meets the range, the distance is summed with the interval between adjacent troughs of the nearest original high and low irregularities on both sides to obtain the assumed total length of the two-span beam. Then, based on the identification range of the two-span beam length (including the characteristic wavelength identification error amplification factor), it is determined whether there is periodic irregularity of the simply supported beam at that location.

[0118] In one embodiment, in order to solve the problem of missed detection caused by the small amplitude of high and low unevenness near the middle beam joint of two consecutive 32m simply supported beams: the distance between adjacent troughs of high and low unevenness is screened based on the identification range of the two-span beam length, and the section that meets the two-span 32m simply supported beam length is extracted, and the sampling points at both ends and the middle of the section are determined. For the troughs with the amplitude of the low-frequency component of high and low unevenness less than 0 in the five-layer wavelet decomposition of the bridge section, the high and low unevenness minimum points are searched near them and deduplication is processed. Then, according to whether the high and low unevenness sampling points near the middle sampling point are within the allowable retrieval range calculated based on the identification error of the two-span beam length of the 32m simply supported beam, it is judged whether there is a beam joint of the 32m simply supported beam and periodic unevenness on both sides.

[0119] In one embodiment, when the trough intervals corresponding to adjacent sections to be determined are within the first beam length identification range or the second beam length identification range, the adjacent sections to be determined are regarded as sections of the simply supported beam with periodic irregularities.

[0120] For example, if we select 32m and 24m simply supported beams based on characteristic wavelength, the following steps are involved:

[0121] 1. By identifying the intervals between adjacent troughs in the high and low roughness data, the sections where periodic roughness of 32m and 24m simply supported beams may exist are preliminarily screened out. This step is mainly based on the characteristic wavelengths of simply supported beams, which are around 32.7m and 24.7m.

[0122] 2. Solve the problem of missed inspection caused by the trough near the mid-span of the same hole beam:

[0123] For those cases where troughs exist near the mid-span of the same hole-beam, additional measures are taken for supplementary identification to avoid missing these areas.

[0124] 3. Solve the problem of missed detection caused by the error in identifying the length of the 32m simply supported beam:

[0125] In view of the possible errors in the identification process of the 32m simply supported beam length, measures are taken to correct the identification deviation to prevent missed detection due to incorrect beam length identification.

[0126] 4. Solve the problem of missed inspection caused by small amplitude of unevenness near the middle beam seam of two consecutive 32m simply supported beams:

[0127] Near the beam joint between two consecutive 32m simply supported beams, if the amplitude of the height irregularity is small, it may cause difficulty in identification. Special supplementary identification is also carried out for such cases to ensure that such areas are not overlooked.

[0128] Through the above steps, the sections of simply supported beams with periodic irregularities can be effectively identified and classified, thereby providing accurate data support for subsequent maintenance and repair work.

[0129] In specific implementation, after performing step 103: based on the characteristic wavelength of periodic irregularity of the simply supported beam, different sections of periodic irregularity of the simply supported beam are screened out according to the trough data, step 104 is performed: according to the vehicle dynamic response data when the train passes through each section, the periodic irregularity grade of the simply supported beam is determined; the periodic irregularity grade of the simply supported beam is used to characterize the degree of influence of the periodic irregularity of the simply supported beam on the track structure state and the train running comfort.

[0130] In one embodiment, the vehicle dynamics response data includes vehicle body vertical acceleration data;

[0131] Obtaining: determining, based on the vehicle body vertical acceleration data, a first correspondence between different vehicle body vertical vibration acceleration half-peak values ​​and simply supported beam periodic irregularity levels;

[0132] Based on the first corresponding relationship, the periodic irregularity grade of the simply supported beam in each section is determined according to the half-peak value of the vertical vibration acceleration of the vehicle body when the vehicle passes through each section.

[0133] In the above embodiment, during the railway track detection process, the acceleration sensor and other equipment installed on the train body are used to collect the vertical acceleration data of the vehicle body during operation in real time. These data record the vertical vibration of the vehicle body caused by factors such as track unevenness when the train passes through different track sections, which is an important basis for evaluating the impact of the periodic unevenness of the simply supported beam on the train operation.

[0134] According to relevant railway industry standards and research results, the corresponding relationship between the half-peak value of different car body vertical vibration acceleration and the periodic irregularity level of simply supported beam is determined. For example, referring to the maintenance rules of a certain high-speed railway line, the management requirements for the local peak value and multi-wave irregularity of track dynamic geometric irregularity stipulate that when the car body vertical vibration acceleration adopts a 20Hz low-pass filter, the allowable deviation management values ​​of levels I, II, III and IV are 1.0, 1.5, 2.0 and 2.5m / s respectively. 2 When the half-peak value of the vertical vibration acceleration of the vehicle body is in different ranges, it corresponds to different levels of periodic irregularity of the simply supported beam. For example, if the half-peak value exceeds 1.0m / s 2 But not reaching 1.5m / s 2 , which may correspond to the lower level of simply supported beam periodic irregularity; and when the half peak value exceeds 2.5m / s 2 When , it may correspond to a higher level of simply supported beam periodic irregularity, indicating that its impact on the track structure and train operation is more serious.

[0135] For different sections of simply supported beam periodic irregularities selected by the above method, the half-peak value of the vertical vibration acceleration of the vehicle body when the vehicle passes through the section is obtained respectively. Taking a certain section as an example, when the train passes through the specific section, the vertical acceleration data of the vehicle body is continuously collected and its half-peak value is calculated.

[0136] According to the determined first corresponding relationship, the calculated half-peak value of the vertical vibration acceleration of the vehicle body is compared with the threshold value in the corresponding relationship.

[0137] If the half-peak value of the vertical vibration acceleration of the vehicle body in a certain section exceeds the threshold of the corresponding level, the periodic irregularity level of the simply supported beam in this section is determined. For example, if the half-peak value of a certain section is 1.8m / s 2 According to the corresponding relationship, it may be judged as Grade III simply supported beam periodic irregularity, which means that the periodic irregularity of the simply supported beam has had a significant impact on the track structure and train operation, and the railway department needs to pay corresponding attention and formulate a reasonable maintenance or monitoring plan according to the grade to ensure the safety of the track structure and the smoothness and comfort of train operation. At the same time, this data-driven grade determination method can provide a scientific and quantitative decision-making basis for railway track maintenance and improve the efficiency and accuracy of track maintenance.

[0138] In one embodiment, the vehicle dynamics response data includes amplitude data of continuous multiple waves of height irregularities of the vehicle body at the trough of the beam gap;

[0139] Acquisition: According to the amplitude data of the high and low roughness of the continuous multi-wave of the vehicle body at the trough of the beam gap, the second corresponding relationship between the continuous multi-wave amplitudes of different vehicle bodies and the periodic roughness grades of the simply supported beam is determined;

[0140] Based on the second corresponding relationship, the periodic irregularity levels of simply supported beams in the multiple continuous sections are determined according to the continuous multiple wave amplitudes of the vehicle body when the vehicle passes through the multiple continuous sections.

[0141] In the above embodiment, in the practice of railway track detection, professional track detection equipment is used to accurately collect the amplitude data of the height and height unevenness of the vehicle body at the beam gap trough when the vehicle passes through multiple consecutive sections during the train operation. These data record in detail the fluctuation of the track height and height unevenness when the train passes through the beam gap trough area of ​​the simply supported beam bridge, which is one of the key indicators for evaluating the degree of periodic unevenness of the simply supported beam.

[0142] According to relevant railway industry standards, a large amount of experimental data and actual operation experience, the corresponding relationship between the continuous multi-wave amplitudes of different car bodies and the periodic irregularity grades of simply supported beams is established.

[0143] For example, for the line section with an allowable speed of 250km / h<max≤350km / h, when the height or rail amplitude reaches 4mm (the continuous multi-wave amplitude of the car body reaches this value), the corresponding simply supported beam periodic irregularity level is high, indicating that it has a great impact on the track structure and train operation, and maintenance measures may need to be taken in time; for the line section with an allowable speed of 200km / h≤max≤250km / h, when the height or rail amplitude reaches 5mm, the corresponding level of simply supported beam periodic irregularity is present. This standard is used to distinguish different degrees of simply supported beam periodic irregularity, providing a basis for subsequent grade determination.

[0144] For the continuous multiple simply supported beam periodic irregularity sections selected by the above method, the continuous multi-wave amplitudes of the vehicle body when the vehicle passes through these sections are obtained respectively. For example, for three consecutive sections, when the train passes through one by one, the amplitude data of the high and low irregularity of the continuous multi-wave of the vehicle body at the trough of the beam gap in each section are accurately recorded.

[0145] According to the determined second corresponding relationship, the obtained continuous multi-wave amplitude of the vehicle body is compared with the threshold in the corresponding relationship. If the continuous multi-wave amplitude of the vehicle body in a certain continuous multiple sections reaches or exceeds the threshold of the corresponding level, the periodic irregularity level of the simply supported beam in the continuous multiple sections is determined.

[0146] For example, if the continuous multi-wave amplitude of the car body in four consecutive sections reaches 4mm in a line section with an allowable speed of 250km / h<max≤350km / h, according to the corresponding relationship, the periodic irregularity level of the simply supported beam in these four sections is judged to be a higher level, which means that the periodic irregularity of the simply supported beam in these sections has a more significant impact on the track structure and train operation. The railway department needs to formulate targeted maintenance plans or strengthen the monitoring frequency based on this level to ensure the stability of the track structure and the safety and comfort of train operation, and ensure the efficiency and reliability of railway operations.

[0147] In one embodiment, the vehicle dynamics response data includes vertical stability data;

[0148] Obtaining: Based on the vertical stability data, the third correspondence between different vertical stability indicators and the periodic irregularity grades of the simply supported beam is determined;

[0149] Based on the third corresponding relationship, the periodic irregularity grade of the simply supported beam in each section is determined according to different vertical stability indicators when the vehicle passes through each section.

[0150] In the above embodiment, when the railway train is running, the vibration data of the vehicle body in the vertical direction is collected in real time by means of relevant sensors installed on the vehicle (such as acceleration sensors), and the vertical stability data is calculated based on the data according to a specific calculation method.

[0151] Specifically, according to the method specified in the specification for evaluation and test identification of the dynamic performance of locomotive vehicles, the acceleration spectrum of the vehicle body within 5 seconds is first calculated, and then the stability index component is calculated for the vibration in the frequency range of 0.5 Hz to 40 Hz. During the calculation, the stability index component is equal to the product of the vehicle body vibration acceleration and the frequency correction coefficient (where the frequency correction coefficient is taken according to Table 1 based on the different ranges of frequency). Finally, the vertical stability index is calculated by taking the square root of the sum of the squares of the stability index components in the frequency range from 0.5 Hz to 40 Hz. Through these calculation processes, accurate vertical stability data can be obtained, which reflects the stability of the train in the vertical direction during operation and is the key basis for evaluating the impact of the periodic unevenness of simply supported beams on the ride comfort of trains.

[0152] According to the evaluation criteria for railway passenger riding comfort and the research results on the influence of simply supported beam periodic unevenness, the corresponding relationship between different vertical stability indicators and the level of simply supported beam periodic unevenness is clarified. For example, when the vertical stability index is less than or equal to 2.5, the train running stability is at an excellent level, and the corresponding level of simply supported beam periodic unevenness is low, which means that the influence of simply supported beam periodic unevenness on train riding comfort is relatively slight at this time; when the vertical stability index is greater than 2.5 and less than or equal to 2.75, the stability is in a good state, corresponding to the corresponding level of simply supported beam periodic unevenness; when the vertical stability index is greater than 2.75 and less than or equal to 3.0, the stability is qualified, and the corresponding level of simply supported beam periodic unevenness is high, indicating that it has a certain degree of influence on riding comfort and needs to be paid attention to; when the vertical stability index is greater than 3.0, the level of simply supported beam periodic unevenness is higher, and the influence on train running comfort is more significant.

[0153] For each section of the simply supported beam with periodic irregularities selected in the previous steps, the vertical stability index when the vehicle passes through the section is determined using the vertical stability data collected and calculated. For example, for a specific section, when the train passes through the track, the specific value of its vertical stability index is obtained according to the above calculation method.

[0154] According to the determined correspondence, the calculated vertical stability index is compared with the threshold in the correspondence. If the vertical stability index meets the range corresponding to a certain level, the periodic irregularity level of the simply supported beam in the section is determined.

[0155] For example, if the vertical stability index of a section is 2.6, based on the corresponding relationship, the periodic unevenness level of the simply supported beam in this section is judged to be the periodic unevenness level of the simply supported beam corresponding to the "good" stability level, which shows that the periodic unevenness of the simply supported beam has a certain impact on the train ride comfort, but it is still at an acceptable level. The railway operation department can use this level information and other relevant factors (such as the frequency of use of the section of track, the surrounding geographical environment, etc.) to comprehensively consider whether it is necessary to further monitor the simply supported beam or take appropriate maintenance measures to ensure the train ride comfort and the overall quality of railway operations. At the same time, this level determination method based on vertical stability data provides scientific and effective decision-making support for the railway department in track maintenance and passenger service quality improvement.

[0156] In the above embodiment, it also includes:

[0157] For each section, a weighted calculation is performed on the periodic irregularity grade of the simply supported beam of each section determined according to different vehicle dynamics response data to obtain weighted data of the periodic irregularity grade of the simply supported beam.

[0158] In the embodiment, for each previously selected simply supported beam periodic unevenness section, the corresponding simply supported beam periodic unevenness level has been determined based on the vehicle body vertical acceleration data, the vehicle body continuous multi-wave high and low unevenness amplitude data at the beam seam trough, and the vertical stability data. For example, in a certain section, the level determined based on the vehicle body vertical acceleration data is a specific level (recorded as level A), the level determined based on the vehicle body continuous multi-wave amplitude data is another specific level (recorded as level B), and the level determined based on the vertical stability data is another specific level (recorded as level C). The levels determined in these different ways reflect the degree of influence of the simply supported beam periodic unevenness on the track structure and train operation from their own perspectives.

[0159] With a large amount of experimental data, actual operation experience and in-depth analysis of the importance of each vehicle dynamic response data, the weighted coefficients corresponding to different vehicle dynamic response data are clarified. For example, it has been determined through research that the vertical acceleration data of the vehicle body has a relatively direct reflection of the stress condition of the track structure, and a weighted coefficient (denoted as coefficient a) is set for it; the continuous multi-wave amplitude data of the vehicle body is closely related to the local unevenness characteristics of the track, and a weighted coefficient (denoted as coefficient b) is set for it; the vertical stability data is directly related to the ride comfort of the train, and a weighted coefficient (denoted as coefficient c) is set for it. The determination of the weighted coefficients requires ensuring that the sum of coefficients a, b and c is equal to 1, and the values ​​of each weighted coefficient are reasonably allocated according to the relative degree of importance of its data. For example, if it is determined that the vertical acceleration data of the vehicle body is relatively more critical, the coefficient a can be 0.4, the coefficient b can be 0.3, and the coefficient c can be 0.3 (this is only an example, and the actual value needs to be determined based on specific research and analysis).

[0160] For each section, the determined weighted coefficients are used to perform weighted calculations on the periodic irregularity grades of simply supported beams determined in different ways. Taking a certain section as an example, the calculation process is: the weighted calculation result is equal to grade A multiplied by coefficient a, plus grade B multiplied by coefficient b, plus grade C multiplied by coefficient c. Through such calculations, the weighted data of the periodic irregularity grade of the simply supported beam in this section is obtained. This weighted data comprehensively considers a variety of vehicle dynamic response factors, and can more comprehensively and accurately reflect the actual severity of the periodic irregularity of the simply supported beam, providing a more scientific and reliable basis for railway track maintenance decisions. For example, if the weighted data calculated for a certain section is high, it indicates that the periodic irregularity of the simply supported beam has a greater comprehensive impact on the track structure and train operation, and the railway department should give priority to its treatment or strengthen monitoring; on the contrary, if the weighted data is low, the maintenance plan can be reasonably arranged according to the actual situation to achieve optimal allocation of resources and ensure the efficiency and safety of railway operations.

[0161] A specific embodiment is given below to illustrate the specific application of the method of the present invention. In this embodiment, the following steps may be included:

[0162] The purpose of this specific embodiment is to provide a method and device for identifying and evaluating periodic irregularities of a simply supported beam, which can identify locations where periodic irregularities of a simply supported beam exist based on high and low irregularity detection data, and then evaluate the severity of periodic irregularities of a simply supported beam in combination with vehicle dynamics response test data, so as to determine whether early intervention and repair are required. The invention will further improve the maintenance management efficiency of periodic irregularities of a simply supported beam, a typical smoothness problem, and provide technical support for maintaining high smoothness of high-speed railway tracks and rationally formulating maintenance and repair plans.

[0163] This specific embodiment includes two parts:

[0164] Part 1 identifies the periodic irregularities of simply supported beams based on the high and low irregularities. Specifically, first, the periodic components of simply supported beams contained in the high and low irregularities need to be extracted. Then, the troughs of suspected periodic irregularities of simply supported beams are identified. Furthermore, based on the unit lengths divided by the suspected troughs, the periodic irregularities of simply supported beams are further screened out and classified according to the beam lengths of the two simply supported beams. Finally, the camber of the periodic irregularities of simply supported beams is calculated.

[0165] In the second part, based on the identification results of the periodic irregularity of the simply supported beam in the first part, the vehicle dynamic response is integrated to evaluate the periodic irregularity of the simply supported beam and select the sections that need priority attention. Specifically, three methods are used for joint evaluation: the first method uses the peak value of the vertical acceleration of the vehicle body for evaluation, the second method uses the continuous multi-wave peak value of the high and low irregularity for evaluation, and the third method uses the vertical stability index for evaluation.

[0166] The above specific embodiments are described as follows:

[0167] Part 1: Identification of periodic irregularities in simply supported beams based on high and low irregularities

[0168] (1) Extraction of periodic components of simply supported beams

[0169] First, professional track detection equipment is used to collect track unevenness data during train operation. These data cover the ups and downs of various parts of the track where the train passes, and are the basic materials for subsequent extraction work.

[0170] You can try to use the bandpass filtering method to process the high and low unevenness data and design a suitable bandpass filter, such as performing bandpass filtering for a specific wavelength range (such as setting the wavelength range to 30-35m).

[0171] Observe the effect after bandpass filtering and analyze the existing problems. For example, although the periodic irregularity components of some sections can be extracted, the sections on both sides that originally had no periodic irregularity will also have periodic components after filtering, and the trough mileage at the beam joints in some sections after filtering is different from the original high and low irregularity trough mileage. Therefore, it is judged that the bandpass filtering method may not be suitable for accurately extracting the periodic components of simply supported beams, and then consider other more suitable methods.

[0172] The appropriate wavelet decomposition level is determined based on the wavelength component range covered by the high and low roughness data (generally 1.5-42m) and the characteristic wavelength of the periodic roughness of simply supported beams (such as the common 32.7m and 24.7m).

[0173] By analyzing the wavelength retention after different levels of wavelet decomposition, the level that can make the low-frequency signal retain the appropriate wavelength component to cover the characteristic wavelength of the simply supported beam is selected. For example, after experiments or analysis, it is found that when the wavelet decomposition level reaches the 5th level, the low-frequency signal can retain the wavelength component of more than 16m, and this range can cover the characteristic wavelength of the periodic unevenness of the simply supported beam, so it is determined to use 5 layers of wavelet decomposition.

[0174] Select a suitable wavelet basis (for example, bior4.4 wavelet basis is determined based on the decomposition effects of different wavelet bases) to perform 5-layer wavelet decomposition on the unevenness data. In the decomposition process, according to the principle of wavelet decomposition, the original unevenness data is decomposed into bandpass signals and low-frequency signals of different bands step by step. With the increase of the decomposition level, the short-wave components in the original unevenness are gradually smoothed out, thereby highlighting the low-frequency characteristic signals related to the periodicity of the simply supported beam.

[0175] The periodic components of the simply supported beam are extracted from the low-frequency signal obtained by 5-layer wavelet decomposition. Specifically, by observing the waveform characteristics of the low-frequency signal and combining it with the known characteristics of the periodic irregularity of the simply supported beam (such as the downward "spike" characteristics at the beam seam, the high and low irregularity amplitudes at the trough are all negative, etc.), the part that can reflect the periodic irregularity of the simply supported beam can be identified as the required periodic component.

[0176] Through the above steps, the periodic components of simply supported beams can be extracted more accurately from track irregularity data.

[0177] Specifically, Figure 1 Schematic diagram showing the unevenness of the center line of a 350 km / h ballastless high-speed railway in an embodiment of the present invention; Figure 1As shown in the figure, there is periodic unevenness of the simply supported beam in the section K609+122~K609+809, and the unevenness waveforms of the left and right strands have similar periodic variation characteristics. Therefore, in order to improve the recognition efficiency and accuracy, the unevenness of the left and right strands Y L , Y R After calculating the average, the centerline height unevenness Y is obtained, and on this basis, the periodic unevenness of the simply supported beam is identified.

[0178] Figure 2 Schematic diagram showing the effect of bandpass filtering of the center line height unevenness according to the wavelength of 30-35m in the embodiment of the present invention; the FIR bandpass filter is designed to bandpass filter the center line height unevenness Y according to the wavelength of 30-35m, and the center line height unevenness Y after bandpass filtering FIR like Figure 2 As shown in the figure, it can be seen that the periodic irregularity components of the above sections are extracted, but the sections without periodic irregularity on both sides also have periodic components after filtering, which obviously affects the recognition effect and causes a large number of misjudgments. In addition, the mileage of the trough at the beam joint of the three-hole beam in the interval K609+122~K609+220 after filtering is also different from the original mileage of the high and low irregularity trough, and the maximum mileage deviation exceeds 4m. In summary, bandpass filtering is not suitable for the identification of periodic irregularity of simply supported beams based on geometric data.

[0179] The analysis results of the periodic irregularity caused by creep of simply supported beams show that the high and low irregularities have a downward "peak" feature at the beam joints, and the amplitudes of the high and low irregularities at the troughs are all negative. In view of this feature, it is more appropriate to use wavelet decomposition to extract the periodic components. The high and low irregularities are sampled at equal spatial intervals of 0.25m, with a sampling frequency of 4m. -1 By using wavelet to decompose the signal step by step, we can get the bandpass signals of different bands. i and low frequency signal a i , each wavelet decomposition level and its corresponding wavelength range are as follows Figure 3 As shown, Figure 3 The figure is a schematic diagram showing the wavelet decomposition level and the corresponding wavelength range in the embodiment of the present invention. It can be seen that when the decomposition level reaches the fifth level, the low-frequency signal a5 retains the wavelength components above 16m. Since the wavelength components covered by the high and low unevenness are 1.5 to 42m, after the fifth level of wavelet decomposition, the actual wavelength components of the low-frequency signal a5 include 16 to 42m, which can cover the two characteristic wavelengths of 32.7m and 24.7m.

[0180] Figure 4a A schematic diagram showing raw data of high and low unevenness in an embodiment of the present invention; Figure 4b This is a schematic diagram showing the low-frequency components obtained by one-layer wavelet decomposition in an embodiment of the present invention; Figure 4cA schematic diagram showing low-frequency components obtained by two-layer wavelet decomposition in an embodiment of the present invention; Figure 4d A schematic diagram showing low-frequency components obtained by three-layer wavelet decomposition in an embodiment of the present invention; Figure 4e A schematic diagram showing low-frequency components obtained by 4-layer wavelet decomposition in an embodiment of the present invention; Figure 4f A schematic diagram showing low-frequency components obtained by 5-layer wavelet decomposition in an embodiment of the present invention; Figure 4g Schematic diagram showing the low-frequency components obtained by 6-layer wavelet decomposition in the embodiment of the present invention; the high and low irregularities are respectively obtained by 1 to 6 layers of wavelet decomposition. Figure 4a to Figure 4g As shown in the figure, it can be seen that with the increase of the decomposition level, the short-wave components in the original high and low unevenness are gradually smoothed out. When the decomposition level reaches 6 layers, the periodic components at both ends of the K609+122~K609+809 simply supported beam section are also filtered out, indicating that the decomposition to the 6th layer is not appropriate. Only when the decomposition level reaches 5 layers, the periodic components of the simply supported beam can be well preserved, and the short-wave unevenness components can also be well suppressed, which verifies that the 5-layer wavelet decomposition is the most appropriate.

[0181] The selection of wavelet basis will affect the filtering effect. Commonly used wavelets include orthogonal wavelets or approximately symmetrical wavelets including Daubechies wavelet, Symlets wavelet, Coiflets wavelet and Biorthogonal wavelet. The uneven low-frequency components obtained by the 5-layer decomposition of the above wavelet basis are as follows: Figure 5 As shown, Figure 5 The figure is a schematic diagram comparing the high and low frequency components of the 5-layer decomposition of different wavelet bases in the embodiment of the present invention. Among them, the waveforms of the decomposition results of the db4 and sym4 wavelet bases are too smooth, and the amplitude of the high and low unevenness of the trough near the beam seam is significantly weakened, which is not suitable for the extraction of periodic components of simply supported beams, while the coif4 and bior4.4 wavelet bases have better effects. Compared with the bior4.4 wavelet, the waveform of the coif4 wavelet after filtering is smoother and can better eliminate some short wave fluctuation characteristics. Therefore, the bior4.4 wavelet is selected as the wavelet base used for subsequent decomposition.

[0182] (2) Identification of periodic irregularities in simply supported beams

[0183] First, obtain the track unevenness data, which is usually collected by professional track detection equipment during the train operation.

[0184] The acquired high and low roughness data is preprocessed as necessary, such as removing obviously abnormal data points (such as data with maximum or minimum values ​​caused by detection equipment failure and not conforming to actual track conditions) to ensure the data quality of subsequent analysis.

[0185] If wavelet decomposition technology is used for processing, determine the appropriate number of wavelet decomposition layers (such as a specific number of layers determined based on experience or preliminary experiments, such as 5 layers). Decompose the high and low unevenness data step by step according to the selected wavelet decomposition layer, separate the different frequency components in the original data through the decomposition process, and extract the low-frequency signal that can effectively characterize the periodic unevenness of the simply supported beam. As the decomposition level increases, the short-wave signal in the original high and low unevenness will gradually be smoothed, thereby highlighting the low-frequency characteristic signal related to the periodicity of the simply supported beam.

[0186] For the effective signal obtained after preprocessing or wavelet decomposition (which can be the original high and low unevenness data or the extracted low-frequency signal, depending on the previous processing steps), find the minimum points in it. These minimum points may be the locations of the troughs that characterize the periodic unevenness of the simply supported beam, and they are used as candidate points of the troughs.

[0187] When looking for a minimum point, you can traverse the data points and compare the value of each point with its adjacent points. When the value of a point is less than the value of its adjacent points, you can preliminarily determine that the point is a minimum point.

[0188] The found trough candidate points are further screened and the points that do not meet the conditions are eliminated to determine the final trough data. First, the sampling points that are not in the bridge section are eliminated. The known bridge location information (such as the starting mileage and ending mileage of the bridge) can be used to determine whether each sampling point is located in the bridge section, and the trough candidate points that are not in the bridge section are removed.

[0189] Secondly, the sampling points whose absolute amplitude is greater than a certain threshold are retained as qualified trough data. A reasonable threshold is set (determined according to actual conditions and experience, such as the amplitude of a specific value of high and low unevenness). Only when the absolute amplitude of the trough candidate point is greater than the threshold, it is identified as qualified trough data, thereby further excluding some points that are misjudged as troughs due to data fluctuations and other reasons.

[0190] For each qualified trough data screened out, its related parameters are determined, such as the position of the trough (which can be represented by the corresponding mileage information), the amplitude of the trough (that is, the height and roughness value of the point), etc.

[0191] At the same time, the adjacent trough intervals, that is, the distance between two adjacent qualified trough data (which can be expressed by the mileage difference), are calculated. These adjacent trough interval data will play a role in the subsequent identification of the periodic unevenness characteristics of simply supported beams. Through the above steps, the periodic unevenness troughs of simply supported beams can be identified more accurately.

[0192] Specifically, in order to accurately identify the trough with downward "peak" characteristics at the beam joint, the following steps are carried out:

[0193] ① The uneven low-frequency component Y obtained by using bior4.4 wavelet 5-layer decomposition bior Most of the shortwave irregularities have been smoothed out, and the low-frequency component Y is found. bior The minimum point N bior,1 , and only keep the sampling points N whose minimum amplitude is less than 0 bior,2 .

[0194] ② A brief list of bridges in the LKJ account of the introduction line. The bridge account contains the central mileage and total length of all bridges, including simple supported beam bridges, culverts, continuous beams and other large-span bridges. b,1 , X b,2 The minimum value points of non-bridge sections can be eliminated to obtain the minimum value points N of the bridge section. bior,3 .

[0195] ③ The amplitude of the periodic unevenness trough of the simply supported beam is generally too large. For the minimum point N obtained in the previous step bior,3 Sampling points with small amplitudes. They may be located in other types of bridge sections, such as other span simply supported beams, culverts or large span bridges, and are not 24m or 32m simply supported beam bridges; they may also be 24m or 32m simply supported beam bridges with better track smoothness after fine-tuning. The above two situations are not the identification targets of periodic irregularity of simply supported beams. Therefore, the screening threshold Y can be specified. lim,1 mm, retain the Y of the bridge section where the absolute value of the minimum amplitude point is greater than the threshold lim,1 mm sampling points, denoted as N bior,4 .

[0196] ④ By Figure 5 It can be seen that the mileage of the high and low unevenness valley after wavelet filtering is still somewhat different from the real mileage of the valley. In order to ensure the accuracy of the recognition of the characteristic wavelength of periodic unevenness, the minimum point N obtained in the previous step is bior,4 Nearby lim, Search for the original minimum value points of high and low unevenness within a range of 1m, recorded as N1, and remove duplicates from these original minimum value points of high and low unevenness, recorded as N2.

[0197] ⑤ Calculate the minimum value point N of the low-frequency component of the high and low uneven wavelet decomposition obtained in the first two steps respectively bior,4 and the distance between two adjacent points of the minimum value point N2 of the height unevenness, respectively denoted as L bior,4 and L2, and count the frequency of occurrence of minimum points in different adjacent trough intervals. The results are as follows Figure 6 As shown, Figure 6 Schematic diagram showing the frequency distribution of the interval between adjacent troughs of low-frequency components decomposed by wavelet and the interval between adjacent troughs of original unevenness. bior,4The main concentrations are at 24.0m and 32.0m, and the interval L2 between adjacent troughs of the original high and low irregularities is mainly concentrated at 24.7m and 32.7m. The above analysis shows that the characteristic wavelengths that need to be focused on are 24.7m and 32.7m. It can be seen that the estimated value of the periodic irregularity wavelength L is obtained after wavelet decomposition. bior,4 There is a certain deviation, so the original unevenness trough N2 should be used as the basis for subsequent identification.

[0198] ⑥ Since the wavelength of the periodic irregularity of the simply supported beam is only 24.7m and 32.7m, the threshold value L of the interval between adjacent troughs can be specified. lim,2 m. When the interval between adjacent troughs of the original high and low unevenness obtained in the previous step exceeds the threshold, it is considered that there is no periodic unevenness of the simply supported beam at that location, and the effective original high and low unevenness trough sampling point N3 and its adjacent trough interval L3 are further screened out.

[0199] (3) Identification and classification of periodic irregularities in simply supported beams

[0200] For simply supported beams of different beam lengths (such as 32m and 24m simply supported beams), the corresponding periodic irregularity characteristic wavelengths are determined according to their structural characteristics. For example, the characteristic wavelength of a 32m simply supported beam can be obtained by adding the total length of the beam to the width of the beam seam (assuming that the total length of the beam is 32m and the width of the beam seam is a certain value, the two are added to obtain the characteristic wavelength value). Similarly, the characteristic wavelength of a 24m simply supported beam can be determined.

[0201] Considering the possible errors in actual measurement and data processing, a reasonable identification error range is set for each characteristic wavelength. For example, based on the characteristic wavelength value, the identification error range is determined by floating a certain value up and down.

[0202] Based on the characteristic wavelength and the identification error range, the beam length identification range corresponding to the simply supported beam of each beam length is determined, that is, the interval from the characteristic wavelength minus the identification error to the characteristic wavelength plus the identification error, which serves as the basis for subsequent identification of the periodic irregularity of the simply supported beam of this beam length.

[0203] From the track unevenness data, the trough data that characterizes the unevenness of the simply supported beam is identified through specific methods (such as after processing with wavelet decomposition and other technologies). The specific operation may include first processing the unevenness data to extract effective signals, then finding the minimum value points as candidate points for the troughs, and then further screening out the trough data that meet the conditions (such as eliminating sampling points that are not in the bridge section, retaining sampling points whose absolute amplitude values ​​are greater than a certain threshold, etc.).

[0204] For each identified trough data, obtain the corresponding original adjacent trough interval of high and low unevenness (recorded as interval value). Compare the original adjacent trough interval of high and low unevenness of the trough data with the identification range of each beam length determined previously. If the original adjacent trough interval of high and low unevenness of a trough data is within the beam length identification range of a certain beam length, then it is identified that the trough data has the corresponding beam length (such as 32m or 24m) of the simply supported beam periodic unevenness. At this time, this trough data is identified as the section of the screened simply supported beam periodic unevenness, which can be used as the object of subsequent further analysis and processing.

[0205] If the interval between adjacent troughs of the original high and low unevenness of the trough data is not within the identification range of any beam length, the trough data is used as a pending section. For the pending section, further inspection can be carried out according to actual needs (such as using other auxiliary methods, combining more relevant data, etc.) to determine whether there is periodic unevenness of the simply supported beam, so as to avoid missing sections that may have problems.

[0206] For some special situations that may lead to missed detection, such as the existence of troughs near the mid-span of the same-hole beam affecting the intervals between adjacent troughs, errors in beam length identification leading to missed detection of some sections, and small amplitude of height irregularities near the middle beam seam of two consecutive simply supported beams, corresponding supplementary identification measures need to be taken.

[0207] Taking the example of the trough near the mid-span of the same hole beam affecting the interval between adjacent troughs, the intervals between the troughs of two adjacent suspected non-simply supported beam periodic irregularities can be summed. If the sum is within the identification range of the corresponding beam length (such as 32m or 24m), it is determined that there is still a simply supported beam periodic irregularity of the corresponding beam length at that location, and other troughs suspected of non-simply supported beam periodic irregularities are extracted again for subsequent processing.

[0208] In order to solve the missed detection caused by beam length identification error, a looser beam length identification range can be specified. When the distance between adjacent points of the suspected non-simply supported beam periodic irregularity meets the range, the distance between adjacent points and the nearest adjacent trough intervals of the original high and low irregularities on both sides are summed to obtain the assumed total length of the two-span beams. Then, based on the two-span beam length identification range (including the characteristic wavelength identification error amplification factor), it is determined whether there is a simply supported beam periodic irregularity at that location.

[0209] For the missed detection caused by the small amplitude of high and low unevenness near the middle beam joint of continuous two-hole simply supported beams, the distance between adjacent troughs of high and low unevenness is screened based on the identification range of the two-span beam length, and the section that meets the 32m beam length of the two-hole simply supported beam is extracted to determine the sampling points at both ends and the middle of the section. For the troughs where the amplitude of the low-frequency component of high and low unevenness in the bridge section is less than a certain value by wavelet decomposition, the high and low unevenness minimum points are searched near them and de-duplicated, and then the high and low unevenness sampling points near the middle sampling points are judged based on whether they are within the allowable retrieval range calculated based on the identification error of the two-span beam length of the 32m simply supported beam, whether there is a beam joint of the 32m simply supported beam and periodic unevenness on both sides.

[0210] Through the above steps, the periodic irregularities of simply supported beams can be identified and classified more comprehensively and accurately.

[0211] Specifically, after obtaining the effective adjacent trough interval L3 of the original high and low unevenness in the previous step, it is necessary to further extract and classify the suspected periodic unevenness locations of the simply supported beam according to the characteristic wavelength of the periodic unevenness.

[0212] ① Screening of 32m and 24m simply supported beams based on characteristic wavelength.

[0213] Specify the characteristic wavelength identification error δ of 32m and 24m simply supported beams respectively 32 m and δ 24 m. When the interval between adjacent troughs of the original unevenness L3 is [32.7-δ 32 ,32.7+δ 32 ]m, it is considered that there is a 32m simply supported beam periodic irregularity; when the interval L3 of adjacent troughs of the original high and low irregularity is within [24.7-δ 24 ,24.7+δ 24 ]m, it is considered that there is periodic unevenness of the 24m simply supported beam. The identification results are as follows Figure 7 As shown, Figure 7 This is a schematic diagram showing the preliminary screening of the periodic irregularities of 32m and 23m simply supported beams based on the characteristic wavelength in an embodiment of the present invention, and extracting other troughs suspected of periodic irregularities of non-simply supported beams for subsequent processing, and the sampling points and adjacent trough intervals are recorded as N4 and L4 respectively.

[0214] ②Solve the problem of missed inspection caused by the trough near the mid-span of the same hole beam

[0215] Typical troughs are also identified within the beam span due to factors such as uneven rail welds or joints between the piers on both sides of the same simply supported beam, resulting in a short interval between adjacent troughs, which does not meet the 32m and 24m simply supported beam length identification range in the previous step. In fact, there is periodic unevenness of the simply supported beam at this location. Figure 8aSchematic diagram showing the unevenness of the trough problem near the mid-span of the same hole beam in an embodiment of the present invention. Figure 8a As shown in the figure, K833+552 and K833+587 are the uneven trough positions at both ends of a 32m simply supported beam, and a trough is also identified at K833+567 between the two troughs. Figure 8b Schematic diagram showing the interval between adjacent troughs for the trough problem near the mid-span of the same hole beam in an embodiment of the present invention, as shown in FIG. Figure 8b As shown in the figure, the distances between the trough at K833+567 and the uneven troughs at both ends of the simply supported beam are 15m and 20m respectively, and the sum of the two distances is 35m, which satisfies [32.7-δ 32 ,32.7+δ 32 In view of the above situation, the sum of the trough spacings of two adjacent suspected non-simply supported beams with periodic irregularities is calculated and recorded as L sum,1 , when the sum of the intervals between two adjacent troughs is L sum,1 In [32.7-δ 32 ,32.7+δ 32 ]m, it is considered that there is still 32m simply supported beam periodic irregularity at this location; when the sum of the intervals between two adjacent troughs L sum,1 In [24.7-δ 24 ,24.7+δ 24 ]m, it is considered that there is still periodic unevenness of the 24m simply supported beam. The identification results are as follows Figure 8a As shown in the figure, the recognition accuracy is further improved. Other troughs suspected of periodic irregularities of non-simply supported beams are extracted for subsequent processing, and their sampling points and adjacent trough intervals are recorded as N5 and L5 respectively.

[0216] ③Solve the missed detection caused by the error in the identification of the length of the 32m simply supported beam

[0217] There are multiple minimum values ​​of unevenness near the end of the same 32m simply supported beam. Since the minimum point N2 with the largest amplitude of unevenness is selected for trough identification, the beam length identification of the two adjacent beams has errors exceeding [32.7-δ 32 ,32.7+δ 32 ]m beam length identification range requirements. In comparison, the continuous arrangement of 24m simply supported beams generally does not exceed 3 holes. The probability of the above situation occurring is small and does not require additional consideration.

[0218] Figure 9a A schematic diagram showing the unevenness of the beam length identification error of a 32m simply supported beam in an embodiment of the present invention; Figure 9b Schematic diagram showing the adjacent trough intervals for the 32m simply supported beam length identification error problem in an embodiment of the present invention; Figure 9a and Figure 9b As shown in the figure, the three joint positions K287+728, K287+757 and K287+794 have multiple minimum values ​​of unevenness, and the corresponding pier center distances of the two-hole 32m simply supported beams are identified as 28.5m and 36.75m, respectively, which exceed [32.7-δ 32 ,32.7+δ 32 ]m beam length recognition range requirements. In order to compensate for the above missed detection, a more relaxed beam length recognition range [L 32,1 ,L 32,2 ]m, when the distance L5 between adjacent points of the suspected non-simply supported beam periodic irregularity obtained in the previous step satisfies the looser beam length identification range [L 32,1 ,L 32,2 ]m, the distance is summed with the interval between adjacent troughs of the nearest original unevenness on both sides to obtain the assumed total length of the two-span beam L double,1 and L double,2 . Specify the identification range of the two-span beam length [32.7×2-λδ 32 ,32.7×2+λδ 32 ]m, where λ represents the error amplification factor of simply supported beam characteristic wavelength identification. double,1 and L double,2 When the identification range of the two-span beam length is met, it is determined that there is periodic unevenness of the simply supported beam at that location.

[0219] After supplementary identification according to the above method, the identification results of the interval distance between adjacent troughs are as follows: Fig.10 As shown, Fig.10 FIG. 1 is a schematic diagram showing the final recognition result of the distance between adjacent troughs after supplementary recognition in an embodiment of the present invention. Figure 7 From the corresponding recognition results of step ①, it can be seen that in sections such as K280+800~K344+400 and K541+100~548+400, points with large deviations in the distance between adjacent troughs can also be accurately identified.

[0220] ④Solve the problem of missed inspection caused by small amplitude of unevenness near the middle beam joint of two consecutive 32m simply supported beams

[0221] Fig.11 Schematic diagram showing the supplementary identification results of the intermediate beam gap problem of two consecutive 32m simply supported beams in an embodiment of the present invention; Fig.11 As shown in the figure, observing the distance L2 between adjacent troughs of high and low unevenness, it can be seen that most of the distances L2 between adjacent troughs of high and low unevenness are concentrated at 65m, which is about the length of the two-span 32m simply supported beam. Analysis of the reasons found that after the 5-layer wavelet decomposition, the minimum point N of the low-frequency component of the wavelet decomposition of high and low unevenness in the bridge section was eliminated. bior,3 The absolute value of the amplitude is less than the threshold Y lim,1When sampling points are selected for each beam length, some beam joints with small amplitudes will be deleted. When the amplitude of the unevenness near the beam joints at both ends of a continuous two-hole beam is too large, and the amplitude of the unevenness near the middle beam joint is too small, the sampling points of the middle beam joint will be filtered out, resulting in the above phenomenon. In comparison, a 24m simply supported beam is generally arranged with no more than 3 holes in a row, and the probability of the above situation occurring is small, and no additional consideration is required.

[0222] In order to make up for the above missed detection, based on the two-span beam length recognition range [32.7×2-λδ 32 ,32.7×2+λδ 32 ]m, the distance L2 between adjacent troughs of high and low irregularities was screened, and the sections that meet the beam length of two-hole 32m simply supported beams were extracted. The sampling points at both ends of each section were recorded as N 2,double,a and N 2,double,c , the distance between adjacent troughs in each segment is recorded as L 2,double , the sampling point in the middle of each segment is recorded as N 2,double,b Then, for the bridge section, the wavelet 5-layer decomposition is used to find all the troughs N with amplitudes less than 0 of the low-frequency components of the high and low irregularities. bior,3 , one by one near the trough L lim,1 Search for the minimum value of the unevenness within the range of m, record it as N6. And remove the duplicates of these minimum points of unevenness, get all the unevenness sampling points and record them as N7. Next, find the sampling point N in the middle of each segment 2,double,b The uneven sampling points nearby are based on the identification error λδ of the two spans of the 32m simply supported beam. 32 , the allowable search range of the attachment in the middle of each segment can be calculated, which is denoted as N 2,double,d and N 2,double,e When all the high and low unevenness sampling points N7 are located in the above allowable search range, it is judged that there is a 32m simply supported beam joint at this location, and the sampling point is recorded as N8. There is a 32m simply supported beam periodic unevenness on each side, and the length of the beam on both sides is recorded as L. 8,1 and L 8,2 The recognition results are as follows: Fig.11 As shown, it can be seen that the recognition effect is further improved.

[0223] Fig.12a It is a schematic diagram showing the high and low unevenness of the periodic unevenness of the simply supported beam in the section K302+600-K304+500 in an embodiment of the present invention; Figure 12b Schematic diagram showing the interval distance between adjacent troughs of periodic unevenness of a simply supported beam in the section K302+600-K304+500 in an embodiment of the present invention; according to the above method, the periodic high and low unevenness of the simply supported beam is identified as follows Fig.12a and Figure 12bAs shown in the figure, a total of 5 continuous 32m simply supported beam sections were identified, among which there were 3 24m simply supported beam sections, and each 24m simply supported beam section had only 2 24m simply supported beams arranged. It can be seen that the recognition effect was fully verified due to the consideration of the influence of various factors.

[0224] (4) Calculation of the camber of a simply supported beam due to periodic irregularities

[0225] Collect track geometry data related to simply supported beams, including height and unevenness data, which are the basis for calculating the camber. These data are usually obtained through professional track inspection equipment during train operation or special track inspection.

[0226] Determine the relevant parameters of the simply supported beam, such as beam length (for example, the actual length of commonly used simply supported beams of different specifications such as 32m and 24m), beam seam width and other information. These parameters are necessary for the subsequent accurate calculation of the camber amount. According to the range covered by the track inspection data and the specific section of the simply supported beam that needs to be analyzed, clarify the interval for the camber amount calculation. For example, is it for a certain continuous section of simply supported beams, or the range where a few specific holes of simply supported beams are located?

[0227] Using the collected unevenness data, find the unevenness values ​​corresponding to the two ends of the simply supported beam (such as near the beam pier position) and the mid-span position of the beam within the determined calculation range. Calculate the difference between the unevenness value at the mid-span position of the beam and the average unevenness value at both ends of the beam. For example, first find the average value of the unevenness values ​​at both ends of the beam, then subtract the average value from the unevenness value at the mid-span position of the beam to obtain a preliminary difference data.

[0228] If there is a beam joint within the calculation range, and the existence of the beam joint affects the height unevenness data and the calculation of the camber amount (for example, data mutations may occur at the beam joint, etc.), then special processing of the data at the beam joint is required.

[0229] It may be necessary to adjust the difference data calculated previously according to the width and position of the beam joint and the relevant empirical formula or correction coefficient. The specific adjustment method needs to be determined based on the actual situation and relevant standards and experience.

[0230] The difference data obtained after the previous steps (after considering the influence of beam gaps) is combined with the beam length and other related parameters of the simply supported beam to calculate the camber of the simply supported beam periodic unevenness according to a specific calculation formula. The calculation formula may be derived based on mechanical principles, track geometry, etc. The specific form will vary depending on different technical backgrounds and analysis methods, but the general idea is to obtain the value of the camber through the combination of the reasonable difference data obtained previously and parameters such as beam length.

[0231] The calculated camber value of the periodic unevenness of the simply supported beam is analyzed. For example, it is determined whether the camber value exceeds the normal range (which can be determined according to the allowable camber value range specified in relevant industry standards and specifications). If it exceeds the normal range, it means that the periodic unevenness of the simply supported beam is relatively serious, which may have a significant impact on the train operation.

[0232] The camber results are combined with other relevant indicators (such as vehicle body vertical acceleration, vertical stability index, etc.) to more comprehensively evaluate the comprehensive impact of simply supported beam periodic irregularities on train operation, thereby providing a basis for decision-making on railway track maintenance and inspection.

[0233] Specifically, the camber of the simply supported beam periodic irregularity can be considered as the difference between the amplitude of the mid-span irregularity caused by the camber of the simply supported beam and the amplitude of the irregularity of the beam joints on both sides. Figure 4a As shown in the figure, there are many short-wave components in the high and low unevenness near the mid-span of the simply supported beam. This local fluctuation is not conducive to the identification of the camber at the mid-span. In contrast, the five-layer wavelet decomposition of the high and low unevenness low-frequency component Y bior Most shortwave irregularities have been smoothed out, such as Figure 4c As shown in the figure, it is closer to the waveform characteristics of the high and low unevenness caused by the arch of the bridge. Based on the identification results of the periodic unevenness of the simply supported beam, the trough sampling point positions N on both sides of each beam hole can be obtained. beam,a and N beam,c , from which the sampling point position N in the middle span can be calculated beam,b , the wavelet decomposition of the uneven low-frequency component Y at the mid-span sampling point bior The amplitude is recorded as Y bior,beam,b For beam joints, the trough sampling point positions N on both sides of each beam hole can be directly extracted. beam,a and N beam,c The corresponding high and low unevenness amplitudes are recorded as Y beam,a and Y beam,c .

[0234] Fig.13 FIG. 1 is a schematic diagram of a method for calculating the periodic unevenness of a simply supported beam according to an embodiment of the present invention; Fig.13 As shown in the figure, the calculation of the camber of the periodic unevenness of a simply supported beam should be based on the high and low unevenness at the beam joints on both sides of the simply supported beam to establish a measurement baseline, and the low-frequency components of the high and low unevenness decomposed by wavelet are used as the measured object, and the vector distance at the middle position is measured. Since the camber of a simply supported beam is very small relative to the beam length, the following formula can be used to simplify the calculation:

[0235] Y bior,beam,b -(Y beam,a +Y beam,c ) / twenty one)

[0236] Part 2: Evaluation Method for Periodic Irregularity of Simply Supported Beams Incorporating Vehicle Dynamics Response

[0237] For the inspection data of a ballastless high-speed railway line with a speed of 350 kilometers per hour, the identification method of periodic irregularities of simply supported beams based on height irregularities proposed in the previous section was used. A total of 12,325 holes of 32m simply supported beams and 653 holes of 24m simply supported beams with periodic irregularities of simply supported beams were identified, and the camber of the simply supported beams of each hole was calculated. For a ballasted high-speed railway with a speed of 250 kilometers per hour, a total of 3187 holes of 32m simply supported beams and 136 holes of 24m simply supported beams were identified. The sections with ballastless line inspection speeds of 290-310km / h and ballasted line inspection speeds of 240-250km / h were selected respectively. In order to avoid the influence of the vertical centrifugal acceleration in the vertical curve section on the statistical results of the vertical acceleration distribution law of the vehicle body, the peak values ​​of the vertical acceleration of the vehicle body within the span of each hole were counted respectively, and a scatter plot of the two was drawn, as shown below. Fig.14a and Fig.14b As shown, Fig.14a It is a schematic diagram showing the relationship between the vertical acceleration peak value of the simply supported beam vehicle body of a ballastless track and the camber of the simply supported beam in an embodiment of the present invention; Fig.14b The figure is a schematic diagram showing the relationship between the peak value of the vertical acceleration of the simply supported beam of the ballasted track and the camber of the simply supported beam in the embodiment of the present invention. It can be seen that for these two lines, the maximum camber of the 32m simply supported beam is greater than that of the 24m simply supported beam. With the increase of the camber of the simply supported beam, the vertical acceleration of the vehicle body of the two beam lengths shows a linear increasing trend, and the peak value of the vertical acceleration of the vehicle body of the 32m simply supported beam is greater than that of the 24m simply supported beam as a whole.

[0238] The characteristic wavelength of the periodic irregularity of a simply supported beam belongs to the medium and long wave category. The above analysis shows that the vertical acceleration response of the vehicle body is most sensitive to the periodic irregularity of the simply supported beam. Therefore, based on the identification results based on high and low irregularities, the vertical acceleration response of the vehicle body is integrated to conduct a secondary evaluation of the significant periodic section of the simply supported beam.

[0239] (1) Evaluation of vehicle vertical acceleration peak value

[0240] There is a correlation between the peak value of the vertical acceleration of the car body and the degree of periodic irregularity of the simply supported beam. By setting different acceleration peak thresholds corresponding to the corresponding levels of periodic irregularity of the simply supported beam, the severity of the impact of the periodic irregularity of the simply supported beam in each section on the train operation can be judged, thereby providing a basis for whether to take subsequent maintenance measures.

[0241] Through the acceleration sensors and other related equipment installed on the train body, the vertical acceleration data of the train body is collected in real time during the train operation. These data can reflect the vertical vibration caused by the track conditions (including factors such as the periodic unevenness of the simply supported beam) when the train passes through different track sections.

[0242] Based on relevant railway industry standards, specifications, and a large amount of actual operation data and research results, the corresponding relationship between different half-peak values ​​of car body vertical vibration acceleration and the level of periodic irregularity of simply supported beams is determined. For example, it may be stipulated that when the half-peak value of car body vertical vibration acceleration is within a certain range (such as less than a certain value A), the corresponding level of periodic irregularity of simply supported beams is a lower level (such as level I), indicating that the impact on train operation and track structure is relatively small; when the half-peak value is in another range (such as greater than value A and less than value B), the corresponding level is medium (such as level II); when the half-peak value exceeds value B, it corresponds to a higher level (such as level III), etc., indicating that the impact on train operation comfort and track safety is relatively serious.

[0243] For each track section that the train passes through, the collected vehicle body vertical acceleration data is analyzed and processed. The half-peak value of the vehicle body vertical acceleration in each section is calculated. The specific calculation method may be based on the collected acceleration data sequence, and a specific algorithm (such as taking the absolute value and then averaging, etc., specifically based on relevant specifications or the actual calculation logic) is used to obtain the half-peak value of the vertical acceleration of the section.

[0244] The calculated half-peak value of the vertical acceleration of the vehicle body of each section is compared with the threshold value in the previously determined corresponding relationship. According to the comparison result, the periodic irregularity level of the simply supported beam of the track section is determined. For example, if the half-peak value of the vertical acceleration calculated for a section is value C, and value C is greater than value A and less than value B, then according to the corresponding relationship, the periodic irregularity level of the simply supported beam of the section is determined to be level II.

[0245] According to the determined level of periodic irregularity of simply supported beams, railway operation departments or relevant maintenance personnel can formulate corresponding maintenance strategies. For sections with lower levels, more conventional maintenance measures such as regular monitoring may be adopted; for sections with higher levels, more targeted maintenance operations such as timely arrangement of inspections and track adjustments may be required to ensure the safety and stability of train operation and the comfort of passengers.

[0246] Specifically, the maintenance rules of a certain high-speed railway line put forward management requirements for the local peak and multi-wave irregularities of track dynamic geometric irregularities. Some of the details are as follows:

[0247] Regarding the allowable deviation management of track dynamic quality, the vertical vibration acceleration of the car body adopts a 20Hz low-pass filter, and the allowable deviation management values ​​of levels I, II, III and IV are 1.0, 1.5, 2.0 and 2.5m / s respectively. 2 .

[0248] The following three-wave, multi-wave and long-wave track irregularities should be handled as soon as possible: in the line section where the permissible speed is 250km / h<max≤350km / h, when the height or track amplitude reaches 4mm; when the height of a 120m long wave reaches 7mm and the vertical vibration acceleration of the car body reaches 1.5m / s 2 120m long wave rail reaches 6mm and the lateral vibration acceleration of the car body reaches 0.9m / s 2 When the permissible speed is 200km / h≤max≤250km / h, the height or track amplitude reaches 5mm. When the height of the 70m long wave reaches 6mm and the vertical vibration acceleration of the car body reaches 1.5m / s 2 70m long wave rail reaches 6mm and the vertical vibration acceleration of the car body reaches 0.9m / s 2 hour.

[0249] Referring to the above rules, based on the identification results of the periodic irregularity of the simply supported beam based on the height irregularity, the peak value evaluation of the vertical acceleration of the vehicle body is processed as follows:

[0250] ① When the half-peak value of the vertical vibration acceleration of the vehicle body in the periodic unevenness section of the simply supported beam exceeds the allowable deviation management value, it should be included in the management as a priority. Fig.15 Schematic diagram showing the relevant data near the beam joint when a 32m simply supported beam has periodic unevenness in a certain simply supported beam section in an embodiment of the present invention, as shown in FIG. Fig.15 As shown, there is periodic unevenness of a 32m simply supported beam in this section. The maximum height unevenness near the beam joint reaches -4.57mm, which does not exceed the Class I standard of 5mm. The maximum vertical acceleration of the vehicle body reaches 0.11g, which exceeds the Class I standard by 0.1g.

[0251] ② For line sections with an allowable speed of 250km / h<max≤350km / h, when the amplitude of the high and low unevenness of four consecutive (i.e. three consecutive waves) or more (i.e. multiple waves) simply supported beam periodic unevenness at the trough of the beam joint reaches 4mm, it should be included in the management as a priority.

[0252] ③ For line sections with an allowable speed of 200km / h≤max≤250km / h, when the amplitude of the high and low unevenness of four consecutive (i.e. three consecutive waves) or more (i.e. multiple waves) simply supported beam periodic unevenness at the trough of the beam joint reaches 5mm, it should be included in the management as a priority. Fig.16 Schematic diagram showing a situation in which a certain simply supported beam section has continuous multiple waves of height irregularities exceeding the limit in an embodiment of the present invention, as shown in FIG. Fig.16 As shown, there is periodic unevenness of simply supported beams in this section. Among them, the amplitude of high and low unevenness near the trough of beam seams in 5 places (4 consecutive waves) from K429+835 to K429+996 exceeds 5mm, which should be paid special attention to.

[0253] (2) Vertical stability index evaluation

[0254] The vertical stability index is calculated according to relevant regulations. Through the relevant sensors (such as acceleration sensors, etc.) installed on the train body, the vibration data of the vertical direction of the train body is collected during the operation of the train, which serves as the basis for the subsequent calculation of the index.

[0255] First, calculate the acceleration spectrum of the vehicle body within 5 seconds. For vibrations within a certain frequency range (such as 0.5 to 40 Hz), calculate the stability index component according to a specific formula. During calculation, the stability index component is equal to the product of the vehicle body vibration acceleration and the frequency correction coefficient. The frequency correction coefficient is determined according to the relevant regulations based on the different frequency ranges. According to the formula, the square root of the sum of the squares of the stability index components within the above frequency range is taken to obtain the vertical stability index value.

[0256] According to the evaluation criteria for railway passenger riding comfort and the research on the influence of simply supported beam periodic irregularities, the corresponding relationship between different vertical stability index values ​​and the train running stability state and the simply supported beam periodic irregularity grade is clarified. For example, the vertical stability index value in a certain range corresponds to excellent train running stability and low level of simply supported beam periodic irregularities; in another range, it corresponds to good stability and corresponding level of simply supported beam periodic irregularities, etc. Different ranges correspond to different levels. For each track section that the train passes through, the vertical stability index value of the track section is calculated using the previous steps.

[0257] The calculated vertical stability index value of each track section is compared with the threshold value in the previously determined corresponding relationship. Based on the comparison result, the simple supported beam periodic irregularity level of the track section is determined. For example, if the vertical stability index value calculated for a track section meets the range corresponding to a certain level, the section is determined to be a simple supported beam periodic irregularity level of this level.

[0258] According to the determined level of periodic irregularity of simply supported beams, railway operation departments or relevant maintenance personnel can formulate corresponding maintenance strategies. For sections with low levels, routine maintenance measures such as regular monitoring can be taken; for sections with high levels, targeted maintenance operations such as inspection and track adjustment need to be arranged in a timely manner to ensure the safety and stability of train operation and the comfort of passengers.

[0259] Specifically, the stability index is an important indicator for evaluating the riding comfort of railway passengers. It is a weighted average of the human body's response, which is very suitable for engineering applications. According to the calculation method of the stability index of a certain locomotive vehicle dynamics performance evaluation and test identification specification, the stability index is calculated every 5 seconds, and the sliding calculation is performed every 1 second.

[0260] First, calculate the vehicle acceleration spectrum within 5s, and then calculate the stability index component when the frequency is, as follows:

[0261]

[0262] In the formula: i=1,2,3,···,n; A i is the vehicle body vibration acceleration, (m / s 2 );f i is the vibration frequency, (Hz), the calculation frequency range of the stability index is 0.5~40Hz; F(f i ) is the frequency correction factor, see the frequency correction factor table described in Table 1.

[0263] Table 1

[0264]

[0265] According to Table 1, the standard frequency correction coefficient curves in the vertical and horizontal directions can be drawn respectively, such as Fig.17 As shown, Fig.17 It is a schematic diagram of the frequency correction coefficient curve in the embodiment of the present invention. It can be seen that the most important frequency affecting comfort is 5.9 Hz in the vertical direction and 5.4 Hz in the horizontal direction, and the vibration signal component with a frequency above 20 Hz in the vertical direction and above 26 Hz in the horizontal direction has very little effect on the stability index.

[0266] Finally, the stability index is calculated as follows:

[0267]

[0268] Where: W i is the frequency f i The corresponding stability indicator component.

[0269] The stability index levels used for passenger cars and EMUs are shown in the stability evaluation grade table in Table 2. The same evaluation grade is used in the vertical and horizontal directions in the table. When the stability index W ≤ 2.5, the running stability of the train is evaluated as excellent.

[0270] Table 2

[0271] Stability level assessment bus Level 1 excellent W≤2.5 Level 2 good 2.5＜W≤2.75 Level 3 qualified 2.75＜W≤3.0

[0272] At present, the stability warning mechanism for shaking and swaying implemented by high-speed EMUs stipulates that when the vertical stability index exceeds 2.75 / 3.0 for 10 consecutive times in the passenger compartment (driver's cab), it is considered that a vertical stability warning / alarm has occurred. In actual use, the vertical stability warning mechanism has been optimized to address the problem of high frequency of vertical stability warnings in continuous simply supported beam bridge sections. The vertical stability warning uses the bridge main frequency + main frequency amplitude (i.e. bridge factor) for bridge filtering. If the vertical stability exceeds 2.75 for 10 consecutive times and the bridge factor exceeds 0.07g for 10 consecutive times, a vertical stability warning is reported.

[0273] The above explanation shows that when the height unevenness does not exceed the track management standards, there are still many cases where the operating EMUs will trigger vertical stability warnings due to the periodic unevenness of the simply supported beam, and then the bridge factor is introduced to narrow the warning range. To a certain extent, the frequency of warnings is reduced by lowering the comfort evaluation standard.

[0274] Referring to the above rules, based on the identification results of periodic irregularities of simply supported beams based on height irregularities, the vertical stability index evaluation is processed as follows:

[0275] The vertical stability index is calculated with a window length of 5s, and the sliding calculation is performed every 1s. The vertical stability calculation results are compared with Table 2, and the sections exceeding the evaluation threshold are selected for priority attention. The evaluation results of a section are as follows: Fig.18a , Fig.18b and Fig.18c shown. Fig.18a It is a schematic diagram showing the unevenness of a certain section based on the evaluation result of the vertical stability index in an embodiment of the present invention; Fig.18b It is a schematic diagram showing the vertical acceleration of a vehicle body in a certain section based on the evaluation result of the vertical stability index in an embodiment of the present invention; Fig.18c The figure is a schematic diagram showing the vertical stability index of a certain section based on the evaluation results of the vertical stability index in the embodiment of the present invention. The two sections K411+053~K412+281 and K412+502~K416+000 were identified to have periodic unevenness of simply supported beams. The vertical stability results show that the vertical stability index of K412+904~K413.565 and K413+628~K413.753 exceeds the level 1 standard (2.5), indicating that these two sections need priority attention.

[0276] Based on the summary of the characteristics of periodic unevenness of simply supported beams, this specific embodiment designs a wavelet filter to extract the periodic components in high and low unevenness, and fully considers the influence of multiple factors on the recognition effect, and optimizes the recognition logic of periodic unevenness of simply supported beams based on high and low unevenness in a targeted manner. Combined with the evaluation method of ride comfort in the existing specifications, the severity of the periodic unevenness of simply supported beams is indirectly evaluated through the vehicle dynamics response. The technical solution is scientific and reasonable, fully tapping the potential of multi-source detection data, further improving the maintenance and management efficiency of the periodic unevenness of simply supported beams, and providing technical support for maintaining the high smoothness of high-speed railway tracks and rationally formulating maintenance and repair plans.

[0277] Compared with the existing research, some studies use bandpass filtering to extract the periodic components in the high and low unevenness, but the periodic unevenness characteristics after bandpass filtering will be diffused to the non-periodic unevenness section, and the peak and trough amplitudes of the periodic unevenness obtained after filtering will be homogenized, resulting in a large number of missed judgments and misjudgments. When the amplitude of the high and low unevenness does not exceed the maintenance management limit, there is no mature evaluation method to evaluate the severity of the periodic unevenness of the simply supported beam, and it is difficult to guide the railway department when to intervene in maintenance. The present invention can achieve:

[0278] 1. Extraction of periodic components of simply supported beams. After decomposing the high and low irregularities through 5 layers of wavelet, the low-frequency signal obtained is used to characterize the periodic components of simply supported beams.

[0279] 2. Identification and classification of periodic irregularities of simply supported beams. The distance between adjacent troughs is calculated based on the identification results of the troughs of suspected periodic irregularities of simply supported beams, and the sections with periodic irregularities of 32m and 24m simply supported beams are preliminarily screened out through characteristic wavelengths. The existence of troughs near the mid-span of the same hole beam, the identification error of the beam length of the 32m simply supported beam, and the small amplitude of high and low irregularities near the middle beam seam of two consecutive holes of 32m simply supported beams are fully considered, and the judgment logic is optimized to improve the accuracy of identification and classification of periodic irregularities of simply supported beams.

[0280] 3. Calculation of the camber of the periodic unevenness of the simply supported beam. The measurement baseline is established with the unevenness at the beam joints on both sides of the simply supported beam, the low-frequency components of the unevenness obtained after 5-layer wavelet decomposition are taken as the measured objects, and the vector distance at the mid-span position of the simply supported beam is regarded as the camber of the periodic unevenness of the simply supported beam.

[0281] 4. Evaluation of periodic irregularities of simply supported beams integrated with vehicle dynamic response. The severity of periodic irregularities of simply supported beams is evaluated by using a variety of methods, including the peak value evaluation of vehicle vertical acceleration, continuous multi-wave peak value evaluation of high and low irregularities, and vertical stability index evaluation.

[0282] In an embodiment of the present invention, wavelet decomposition technology is used to extract a low-frequency signal representing the periodic unevenness of a simply supported beam from track height unevenness data; trough data representing the height unevenness of a simply supported beam is identified from the low-frequency signal; based on the characteristic wavelength of the periodic unevenness of the simply supported beam, different sections of the periodic unevenness of the simply supported beam are screened out according to the trough data; based on the vehicle dynamics response data when a train passes through each section, the periodic unevenness grade of the simply supported beam in each section is determined; the periodic unevenness grade of the simply supported beam is used to characterize the degree of influence of the periodic unevenness of the simply supported beam on the track structure state and the train running comfort. The embodiment of the present invention uses wavelet decomposition technology to extract low-frequency signals containing periodic characteristics of simply supported beams from track height unevenness data, which can effectively retain the periodic components of simply supported beams, improve the recognition accuracy of periodic unevenness of simply supported beams, and avoid interference from short-wave unevenness components; based on the characteristic wavelength of periodic unevenness of simply supported beams, different sections of periodic unevenness of simply supported beams are screened out according to identified trough data, and simply supported beams of different spans can be accurately distinguished, avoiding the problems of missed judgment and misjudgment caused by the use of bandpass filtering technology under the prior art; according to the vehicle dynamics response data when the train passes through each section, the periodic unevenness levels of simply supported beams in different sections can be quantitatively evaluated, and the severity of periodic unevenness of simply supported beams can be comprehensively evaluated, providing a scientific basis for repair and maintenance.

[0283] Of course, it is understandable that the above detailed process may have other variations, and the relevant variations should all fall within the protection scope of the present invention.

[0284] The present invention also provides a device for evaluating the periodic unevenness of a simply supported beam, as described in the following embodiments. Since the principle of solving the problem by the device is similar to the method for evaluating the periodic unevenness of a simply supported beam, the implementation of the device can refer to the implementation of the method for evaluating the periodic unevenness of a simply supported beam, and the repeated parts will not be repeated.

[0285] Fig. 20 is a schematic diagram of the structure of a device for evaluating periodic irregularity of a simply supported beam in an embodiment of the present invention. The embodiment of the present invention also provides a device for evaluating periodic irregularity of a simply supported beam, which is used to automatically identify and quantitatively evaluate periodic irregularity of a simply supported beam, thereby improving the identification precision and accuracy of periodic irregularity of a simply supported beam. Fig. 20 As shown, the device comprises:

[0286] The low-frequency signal extraction module 2001 is used to extract the low-frequency signal representing the periodic irregularity of the simply supported beam from the track height irregularity data by using the wavelet decomposition technology;

[0287] The trough data identification module 2002 is used to identify the trough data representing the unevenness of the simply supported beam from the low-frequency signal;

[0288] A section screening module 2003 is used to screen out different sections of the periodic irregularity of the simply supported beam according to the trough data based on the characteristic wavelength of the periodic irregularity of the simply supported beam;

[0289] The module 2004 for determining the periodic irregularity level of a simply supported beam is used to determine the periodic irregularity level of a simply supported beam in each section according to the vehicle dynamic response data when the train passes through each section; the periodic irregularity level of a simply supported beam is used to characterize the degree of influence of the periodic irregularity of a simply supported beam on the track structure state and the train running comfort.

[0290] In one embodiment, wavelet decomposition technology is used to extract low-frequency signals representing periodic irregularities of simply supported beams from track height irregularities data, including:

[0291] Wavelet decomposition technology is used to perform multi-level decomposition on the track unevenness data based on a preset number of wavelet decomposition layers, and a low-frequency signal characterizing the periodic unevenness of a simply supported beam is extracted; the multi-level decomposition is used to smooth the short-wave signals in the track unevenness data.

[0292] In one embodiment, it further includes:

[0293] The original roughness adjacent trough intervals are pre-calculated as follows:

[0294] Extract the minimum point from the low-frequency signal as the first low-frequency sampling point;

[0295] Eliminate the sampling points that are not in the bridge section from the first sampling points to obtain the second low-frequency sampling points;

[0296] Retaining the sampling points whose absolute amplitude values ​​among the second sampling points are greater than the preset first threshold as the third low-frequency sampling points;

[0297] For each third low-frequency sampling point, the minimum value point of the track height irregularity data within a preset adjacent wavelength range of the third low-frequency sampling point is recorded as an original sampling point;

[0298] Calculate the distance between adjacent sampling points of the original sampling points to obtain the interval between adjacent troughs of the original roughness;

[0299] Identify the trough data that characterizes the unevenness of the simply supported beam from the low-frequency signal, including:

[0300] When the trough intervals of adjacent signals in the low-frequency signal exceed the pre-calculated adjacent trough intervals of the original height irregularity, the data of the adjacent signals are used as the identified trough data representing the height irregularity of the simply supported beam.

[0301] In one embodiment, based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are screened out according to the trough data, including:

[0302] Determine a first beam length recognition range of a first simply supported beam periodic irregularity type and a second beam length recognition range of a second simply supported beam periodic irregularity type according to a characteristic wavelength of a simply supported beam periodic irregularity and recognition errors of different preset characteristic wavelengths;

[0303] For each trough data, if the adjacent trough interval of the original high and low irregularities corresponding to the trough data is within the first beam length identification range or the second beam length identification range, it is identified that the trough data at this location has periodic irregularities of a simply supported beam;

[0304] The trough data at the location where the simply supported beam has periodic irregularities is taken as the screened section of the simply supported beam with periodic irregularities; the trough data at the location where the simply supported beam has no periodic irregularities is taken as the undetermined section.

[0305] In one embodiment, the vehicle dynamics response data includes vehicle body vertical acceleration data;

[0306] Obtaining: determining, based on the vehicle body vertical acceleration data, a first correspondence between different vehicle body vertical vibration acceleration half-peak values ​​and simply supported beam periodic irregularity levels;

[0307] Based on the first corresponding relationship, the periodic irregularity grade of the simply supported beam in each section is determined according to the half-peak value of the vertical vibration acceleration of the vehicle body when the vehicle passes through each section.

[0308] In one embodiment, the vehicle dynamics response data includes amplitude data of continuous multiple waves of height irregularities of the vehicle body at the trough of the beam gap;

[0309] Acquisition: According to the amplitude data of the high and low roughness of the continuous multi-wave of the vehicle body at the trough of the beam gap, the second corresponding relationship between the continuous multi-wave amplitudes of different vehicle bodies and the periodic roughness grades of the simply supported beam is determined;

[0310] Based on the second corresponding relationship, the periodic irregularity levels of simply supported beams in the multiple continuous sections are determined according to the continuous multiple wave amplitudes of the vehicle body when the vehicle passes through the multiple continuous sections.

[0311] In one embodiment, the vehicle dynamics response data includes vertical stability data;

[0312] Obtaining: Based on the vertical stability data, the third correspondence between different vertical stability indicators and the periodic irregularity grades of the simply supported beam is determined;

[0313] Based on the third corresponding relationship, the periodic irregularity grade of the simply supported beam in each section is determined according to different vertical stability indicators when the vehicle passes through each section.

[0314] In one embodiment, it further includes:

[0315] For each section, a weighted calculation is performed on the periodic irregularity grade of the simply supported beam of each section determined according to different vehicle dynamics response data to obtain weighted data of the periodic irregularity grade of the simply supported beam.

[0316] The embodiment of the present invention provides an embodiment of a computer device for implementing all or part of the contents of the above-mentioned evaluation method for periodic irregularity of a simply supported beam. The computer device specifically includes the following contents:

[0317] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between related devices; the computer device can be a desktop computer, a tablet computer and a mobile terminal, etc., but the present embodiment is not limited thereto. In the present embodiment, the computer device can be implemented with reference to the embodiment of the method for evaluating the periodic irregularity of a simply supported beam and the embodiment of the device for evaluating the periodic irregularity of a simply supported beam, and the contents thereof are incorporated herein, and the repeated parts are not repeated.

[0318] Fig.21 FIG. 1 is a schematic block diagram of the system structure of the computer device 1000 according to an embodiment of the present application. Fig.21 As shown, the computer device 1000 may include a central processor 1001 and a memory 1002; the memory 1002 is coupled to the central processor 1001. It is worth noting that Fig.21 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0319] In one embodiment, the evaluation function of the periodic irregularity of a simply supported beam may be integrated into the central processor 1001. The central processor 1001 may be configured to perform the following control:

[0320] Wavelet decomposition technology is used to extract low-frequency signals representing the periodic irregularity of simply supported beams from track height irregularity data.

[0321] Identify the trough data representing the height irregularity of the simply supported beam from the low-frequency signal;

[0322] Based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are screened out according to the trough data;

[0323] The periodic irregularity grade of the simply supported beam in each section is determined according to the vehicle dynamics response data when the train passes through each section; the periodic irregularity grade of the simply supported beam is used to characterize the influence of the periodic irregularity of the simply supported beam on the track structure state and the train running comfort.

[0324] In another embodiment, the evaluation device for the periodic irregularity of a simply supported beam can be configured separately from the central processor 1001. For example, the evaluation device for the periodic irregularity of a simply supported beam can be configured as a chip connected to the central processor 1001, and the evaluation function of the periodic irregularity of a simply supported beam can be realized through the control of the central processor.

[0325] like Fig.21 As shown, the computer device 1000 may also include: a communication module 1003, an input unit 1004, an audio processor 1005, a display 1006, and a power supply 1007. It is worth noting that the computer device 1000 does not necessarily have to include Fig.21 In addition, the computer device 1000 may also include Fig.21 For components not shown, reference may be made to the prior art.

[0326] like Fig.21 As shown, the central processor 1001 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The central processor 1001 receives inputs and controls the operations of various components of the computer device 1000 .

[0327] The memory 1002 may be, for example, a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices, or one or more thereof. The memory may store the above-mentioned information related to the device, and may also store a program for executing the related information. The CPU 1001 may execute the program stored in the memory 1002 to implement information storage or processing, etc.

[0328] The input unit 1004 provides input to the CPU 1001. The input unit 1004 is, for example, a key or a touch input device. The power supply 1007 is used to provide power to the computer device 1000. The display 1006 is used to display display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0329] The memory 1002 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 1002 may also be some other type of device. The memory 1002 includes a buffer memory 1021 (sometimes referred to as a buffer). The memory 1002 may include an application / function storage unit 1022, which is used to store application programs and function programs or processes for executing the operation of the computer device 1000 through the central processor 1001.

[0330] The memory 1002 may also include a data storage unit 1023 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the computer device. The driver storage unit 1024 of the memory 1002 may include various drivers for the computer device for communication functions and / or for executing other functions of the computer device (such as messaging applications, address book applications, etc.).

[0331] The communication module 1003 is a transmitter / receiver that sends and receives signals via the antenna 1008. The communication module (transmitter / receiver) 1003 is coupled to the central processor 1001 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0332] Based on different communication technologies, multiple communication modules 1003 may be provided in the same computer device, such as a cellular network module, a Bluetooth module and / or a wireless local area network module, etc. The communication module (transmitter / receiver) 1003 is also coupled to a speaker 1009 and a microphone 1010 via an audio processor 1005 to provide an audio output via the speaker 1009 and receive an audio input from the microphone 1010, thereby realizing a common telecommunication function. The audio processor 1005 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 1005 is also coupled to the central processor 1001, so that recording can be performed on the local machine through the microphone 1010, and the sound stored on the local machine can be played through the speaker 1009.

[0333] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for evaluating the periodic irregularity of a simply supported beam is implemented.

[0334] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the above-mentioned method for evaluating the periodic irregularity of a simply supported beam is implemented.

[0335] In an embodiment of the present invention, wavelet decomposition technology is used to extract a low-frequency signal representing the periodic unevenness of a simply supported beam from track height unevenness data; trough data representing the height unevenness of a simply supported beam is identified from the low-frequency signal; based on the characteristic wavelength of the periodic unevenness of the simply supported beam, different sections of the periodic unevenness of the simply supported beam are screened out according to the trough data; based on the vehicle dynamics response data when a train passes through each section, the periodic unevenness grade of the simply supported beam in each section is determined; the periodic unevenness grade of the simply supported beam is used to characterize the degree of influence of the periodic unevenness of the simply supported beam on the track structure state and the train running comfort. The embodiment of the present invention uses wavelet decomposition technology to extract low-frequency signals containing periodic characteristics of simply supported beams from track height unevenness data, which can effectively retain the periodic components of simply supported beams, improve the recognition accuracy of periodic unevenness of simply supported beams, and avoid interference from short-wave unevenness components; based on the characteristic wavelength of periodic unevenness of simply supported beams, different sections of periodic unevenness of simply supported beams are screened out according to identified trough data, and simply supported beams of different spans can be accurately distinguished, avoiding the problems of missed judgment and misjudgment caused by the use of bandpass filtering technology under the prior art; according to the vehicle dynamics response data when the train passes through each section, the periodic unevenness levels of simply supported beams in different sections can be quantitatively evaluated, and the severity of periodic unevenness of simply supported beams can be comprehensively evaluated, providing a scientific basis for repair and maintenance.

[0336] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0337] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0338] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0339] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0340] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for evaluating periodic irregularity of a simply supported beam, characterized in that: include: Wavelet decomposition technology is used to extract low-frequency signals representing the periodic irregularity of simply supported beams from track height irregularity data. Identify the trough data representing the height irregularity of the simply supported beam from the low-frequency signal; Based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are screened out according to the trough data; According to the vehicle dynamic response data when the train passes through each section, the periodic irregularity level of the simply supported beam in each section is determined; The simply supported beam periodic irregularity grade is used to characterize the influence of the simply supported beam periodic irregularity on the track structure state and the train running comfort.

2. The method according to claim 1, characterized in that Wavelet decomposition technology is used to extract low-frequency signals representing the periodic irregularity of simply supported beams from track height irregularity data, including: Wavelet decomposition technology is used to perform multi-level decomposition on the track unevenness data based on a preset number of wavelet decomposition layers, and a low-frequency signal characterizing the periodic unevenness of a simply supported beam is extracted; the multi-level decomposition is used to smooth the short-wave signals in the track unevenness data.

3. The method according to claim 1, characterized in that Also includes: The original roughness adjacent trough intervals are pre-calculated as follows: Extract the minimum point from the low-frequency signal as the first low-frequency sampling point; Eliminate the sampling points that are not in the bridge section from the first sampling points to obtain the second low-frequency sampling points; Retaining the sampling points whose absolute amplitude values ​​among the second sampling points are greater than the preset first threshold as the third low-frequency sampling points; For each third low-frequency sampling point, the minimum value point of the track height irregularity data within a preset adjacent wavelength range of the third low-frequency sampling point is recorded as an original sampling point; Calculate the distance between adjacent sampling points of the original sampling points to obtain the interval between adjacent troughs of the original high and low roughness; Identify the trough data that characterizes the unevenness of the simply supported beam from the low-frequency signal, including: When the trough intervals of adjacent signals in the low-frequency signal exceed the pre-calculated adjacent trough intervals of the original height irregularity, the data of the adjacent signals are used as the identified trough data representing the height irregularity of the simply supported beam.

4. The method according to claim 3, characterized in that Based on the characteristic wavelength of the periodic irregularity of the simply supported beam, different sections of the periodic irregularity of the simply supported beam are screened out according to the trough data, including: Determine a first beam length recognition range of a first simply supported beam periodic irregularity type and a second beam length recognition range of a second simply supported beam periodic irregularity type according to a characteristic wavelength of a simply supported beam periodic irregularity and recognition errors of different preset characteristic wavelengths; For each trough data, if the adjacent trough interval of the original high and low irregularities corresponding to the trough data is within the first beam length identification range or the second beam length identification range, it is identified that the trough data at this location has periodic irregularities of a simply supported beam; The trough data at the location where the simply supported beam has periodic irregularities is taken as the screened section of the simply supported beam with periodic irregularities; the trough data at the location where the simply supported beam has no periodic irregularities is taken as the undetermined section.

5. The method according to claim 1, characterized in that The vehicle dynamics response data includes vehicle body vertical acceleration data; Obtaining: determining, based on the vehicle body vertical acceleration data, a first correspondence between different vehicle body vertical vibration acceleration half-peak values ​​and simply supported beam periodic irregularity levels; Based on the first corresponding relationship, the periodic irregularity grade of the simply supported beam in each section is determined according to the half-peak value of the vertical vibration acceleration of the vehicle body when the vehicle passes through each section.

6. The method according to claim 1, characterized in that The vehicle dynamics response data includes amplitude data of the height and low roughness of the continuous multi-wave of the vehicle body at the trough of the beam gap; Acquisition: According to the amplitude data of the high and low roughness of the continuous multi-wave of the vehicle body at the trough of the beam gap, the second corresponding relationship between the continuous multi-wave amplitudes of different vehicle bodies and the periodic roughness grades of the simply supported beam is determined; Based on the second corresponding relationship, the periodic irregularity levels of simply supported beams in the multiple continuous sections are determined according to the continuous multiple wave amplitudes of the vehicle body when the vehicle passes through the multiple continuous sections.

7. The method according to claim 1, characterized in that The vehicle dynamics response data includes vertical stability data; Obtaining: Based on the vertical stability data, the third correspondence between different vertical stability indicators and the periodic irregularity grades of the simply supported beam is determined; Based on the third corresponding relationship, the periodic irregularity grade of the simply supported beam in each section is determined according to different vertical stability indicators when the vehicle passes through each section.

8. The method according to claim 1, characterized in that Also includes: For each section, a weighted calculation is performed on the periodic irregularity grade of the simply supported beam of each section determined according to different vehicle dynamics response data to obtain weighted data of the periodic irregularity grade of the simply supported beam.

9. An evaluation device for periodic irregularity of a simply supported beam, characterized in that: include: The low-frequency signal extraction module is used to extract the low-frequency signal representing the periodic irregularity of the simply supported beam from the track height irregularity data by using wavelet decomposition technology; The trough data recognition module is used to identify the trough data representing the unevenness of the simply supported beam from the low-frequency signal; A section screening module, for screening different sections of the periodic irregularity of the simply supported beam according to the trough data based on the characteristic wavelength of the periodic irregularity of the simply supported beam; A module for determining the periodic irregularity level of a simply supported beam, which is used to determine the periodic irregularity level of a simply supported beam in each section according to the vehicle dynamics response data when the train passes through each section; The simply supported beam periodic irregularity grade is used to characterize the influence of the simply supported beam periodic irregularity on the track structure state and the train running comfort.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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