Railway geometry large value overrun monitoring method and device

Abstract

The application discloses a track geometry large value overrun monitoring method and device, and relates to the field of track geometry large value overrun monitoring.The method comprises the following steps: establishing a wheel-rail interaction model of an operation vehicle and a target track according to target track and operation vehicle design parameters; establishing a correlation between different speed levels of the operation vehicle and a vertical acceleration threshold value of a frame and a vertical displacement threshold value of the frame; determining a target vertical acceleration threshold value of the frame and a target vertical displacement threshold value of the frame at a speed level corresponding to a vehicle speed of a target operation vehicle of the target track; and issuing an alarm information of a track geometry large value overrun event of the target track when a target vertical acceleration of the frame of the operation vehicle is greater than or equal to the target vertical acceleration threshold value of the frame and a target vertical displacement of the frame of the operation vehicle is greater than or equal to the target vertical displacement threshold value of the frame.The application is used to improve the efficiency and accuracy of track geometry large value overrun monitoring.

Description

Track geometry maximum value exceeding limit monitoring method and device Technical Field

[0001] This invention relates to the field of railway track measurement and track management technology, and in particular to a method and device for monitoring track geometry exceeding limits. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] In high-speed rail systems, the track serves as the direct carrier bearing train loads. Its geometric shape and position characteristics are closely related to the interaction between the train and the track, affecting not only passenger comfort but also being a key factor determining operational safety. Currently, detailed management standards have been established for track dynamic irregularities, with dynamic quality management based on local peak values ​​and the overall average value of a section (TQI). Local peak values ​​are divided into four levels (Levels I to IV), with Levels III and IV corresponding to temporary repairs and speed-limited operation, respectively. Exceeding Levels III and IV may jeopardize operational safety and is collectively referred to as exceeding the maximum geometric limit of the track.

[0004] Currently, the most important and comprehensive dynamic inspection method is to use high-speed comprehensive inspection trains to conduct periodic comprehensive checks on track conditions 2 to 3 times per month. Between two consecutive dynamic inspections, supplementary inspections are carried out daily on some operating EMU trains using onboard track inspection instruments, which indirectly assess track conditions through the train's acceleration response.

[0005] However, an analysis of recent years' track geometric deviations (exceeding the standards for emergency repairs or speed limits) reveals that a significant proportion of track geometric deviations did not meet the Level II standard during the last inspection. During this period, the onboard track inspection equipment also failed to issue any significant alarms. This poses a clear loophole to the safe operation of high-speed rail and urgently needs to be addressed.

[0006] To compensate for insufficient inspection frequency at a lower cost, track condition monitoring on operating high-speed trains has been a research hotspot. Existing research methods mainly include signal processing, inverse solving of dynamic models, or deep learning based on big data. However, existing research still has some shortcomings. For example, compared to accelerometers, gyroscopes installed on the car body or frame are too expensive; the stability of detection systems using axle box acceleration as input needs to be fully verified under different infrastructure and train speed conditions; the inversion accuracy of inverse dynamic solving largely depends on the simplification of the model and the rationality of the dynamic parameters, most of which remain in the theoretical stage and have not been practically verified; deep learning also has adaptability issues for different train models and track conditions. Although the common problem is that the accuracy and stability of the system cannot reach the level of mature measurement systems on track inspection vehicles, from the perspective of ensuring operational safety in real time, compared to accurately measuring the amplitude of track irregularities, track condition monitoring, as a supplementary means between two professional inspections, using relatively simple hardware devices to achieve real-time alarms for exceeding the geometric limits of the track is more important. Summary of the Invention

[0007] This invention provides a method for monitoring track geometry maximum limits, to improve the efficiency and accuracy of track geometry maximum limit monitoring. The method includes:

[0008] Based on the design parameters of the target track and the operating vehicle, a wheel-rail interaction model between the operating vehicle and the target track is established; the dynamic interaction model between the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response.

[0009] Based on a wheel-rail interaction model of the operating vehicle and the target track, a correlation is established between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame. The vertical acceleration threshold is used to describe the vertical acceleration of the frame when the track geometric irregularity wavelength is a first preset wavelength at the corresponding speed level. The vertical displacement threshold is used to describe the vertical displacement of the frame when the track geometric irregularity wavelength is a second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength.

[0010] Based on the speed of the target operating vehicle on the target track, determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to that speed.

[0011] The vertical displacement of the target vehicle frame on the target track is calculated based on the vertical acceleration of the target vehicle frame on the target track.

[0012] When the vertical acceleration of the target structure of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target structure, and the vertical displacement of the target structure of the operating vehicle is greater than or equal to the vertical displacement threshold of the target structure, an alarm message is issued indicating that the target track has experienced a track geometry over-limit event.

[0013] This invention also provides a track geometry maximum limit monitoring device to improve the efficiency and accuracy of track geometry maximum limit monitoring. The device includes:

[0014] The model building module is used to establish a wheel-rail interaction model between the operating vehicle and the target track based on the design parameters of the target track and the operating vehicle; the dynamic interaction model between the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response.

[0015] The correlation establishment module is used to establish the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame based on the wheel-rail interaction model of the operating vehicle and the target track. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the frame is used to describe the vertical displacement of the frame when the wavelength of the track geometric irregularity is a second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength.

[0016] The threshold determination module is used to determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to the target operating vehicle speed on the target track.

[0017] The target frame vertical displacement calculation module is used to calculate the vertical displacement of the target frame of the operating vehicle on the target track based on the vertical acceleration of the target frame of the operating vehicle on the target track.

[0018] The monitoring module is used to issue an alarm message indicating that a track geometry over-limit event has occurred on the target track when the vertical acceleration of the target frame of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target frame and the vertical displacement of the target frame of the operating vehicle is greater than or equal to the vertical displacement threshold of the target frame.

[0019] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for monitoring the maximum value exceeding the orbital geometry limit.

[0020] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for monitoring the maximum value exceeding the orbital geometry limit.

[0021] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for monitoring the maximum value exceeding the orbital geometry limit.

[0022] In this embodiment of the invention, a wheel-rail interaction model of the operating vehicle and the target track is established based on the design parameters of the target track and the operating vehicle. The dynamic interaction model of the operating vehicle and the target track is used to simulate the influence of large-value over-limits on the vehicle's dynamic response. Based on the wheel-rail interaction model of the operating vehicle and the target track, a correlation is established between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the frame is used to describe the vertical displacement of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength. Based on the speed of the target operating vehicle on the target track, the corresponding speed is determined. The system calculates the target frame vertical acceleration threshold and target frame vertical displacement threshold at different speed levels. Based on the target frame vertical acceleration of the operating vehicle on the target track, the vertical displacement of the target frame is calculated. When the target frame vertical acceleration of the operating vehicle is greater than or equal to the target frame vertical acceleration threshold, and the target frame vertical displacement of the operating vehicle is greater than or equal to the target frame vertical displacement threshold, an alarm message indicating a track geometric maximum limit exceedance event is issued. By combining the frame vertical acceleration and frame vertical displacement, the system can accurately monitor track geometric maximum limit exceedances, improving the efficiency and accuracy of track geometric maximum limit exceedance monitoring. This solves the problems of high cost, low stability, and low adaptability in existing methods for compensating for insufficient track detection frequency. It provides a technical means for real-time monitoring of line service status and ensuring continuous safe train operation. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0024] Figure 1 is an example diagram of the distribution of track irregularity variation in an embodiment of the present invention;

[0025] Figure 2A is an example diagram of a typical large value exceeding the limit A dynamic detection data feature in an embodiment of the present invention;

[0026] Figure 2B is an example diagram of a typical large value exceeding the limit B dynamic detection data feature in an embodiment of the present invention;

[0027] Figure 3 is an example diagram of the wavelength distribution exceeding the limit of orbital geometry in an embodiment of the present invention;

[0028] Figure 4 is an example diagram of a high-speed train-track dynamic interaction model in an embodiment of the present invention;

[0029] Figure 5 is a schematic diagram of an embodiment of the present invention in which the unevenness of the left and right rails is simulated using a simple harmonic function with the same phase.

[0030] Figure 6 is a specific example of the variation law of the peak vertical acceleration of a vehicle body in an embodiment of the present invention;

[0031] Figure 7 is a specific example of the variation law of the peak vertical acceleration of a vehicle body with a 20Hz low-pass filter in an embodiment of the present invention;

[0032] Figure 8 is a specific example of the variation law of the peak vertical acceleration of a frame in an embodiment of the present invention;

[0033] Figure 9 is a specific example of the variation law of the peak vertical displacement of the vehicle body in an embodiment of the present invention;

[0034] Figure 10 is a schematic diagram illustrating the variation law of the peak vertical displacement of a frame in an embodiment of the present invention;

[0035] Figure 11 is a flowchart illustrating a method for evaluating the vertical acceleration of a frame according to an embodiment of the present invention;

[0036] Figure 12 is a specific example of the vertical displacement calculation process of a frame in an embodiment of the present invention;

[0037] Figure 13 is a specific example diagram of the vertical acceleration of a frame in an embodiment of the present invention;

[0038] Figure 14 is a specific example diagram of the vertical acceleration SAWC (2-9m) of a frame in an embodiment of the present invention;

[0039] Figure 15 is a schematic diagram of the vertical displacement of a frame in an embodiment of the present invention;

[0040] Figure 16 is a specific example of the comparison between the measured unevenness and the restored vertical displacement of the frame in an embodiment of the present invention;

[0041] Figure 17 is a specific example diagram of a measured triangular pit in an embodiment of the present invention;

[0042] Figure 18 is a specific example diagram of the measured vertical acceleration (SAWC) of a frame in an embodiment of the present invention;

[0043] Figure 19 is a specific example of the comparison between the measured unevenness and the restored vertical displacement of the frame in an embodiment of the present invention;

[0044] Figure 20 is a specific example diagram of a measured triangular pit in an embodiment of the present invention;

[0045] Figure 21 is a specific example diagram of the measured vertical acceleration (SAWC) of a frame in an embodiment of the present invention;

[0046] Figure 22 is a flowchart illustrating a method for monitoring track geometry exceeding limits in an embodiment of the present invention;

[0047] Figure 23 is a structural example diagram of a track geometry maximum value exceeding limit monitoring device according to an embodiment of the present invention;

[0048] Figure 24 is a schematic diagram of a computer device used for monitoring the maximum geometric limit of the track in an embodiment of the present invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0050] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0051] In the description of this specification, the terms "comprising," "including," "having," and "containing" are open-ended terms, meaning that they include but are not limited to. The terms "an embodiment," "a specific embodiment," "some embodiments," and "for example," etc., refer to specific features, structures, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. The order of steps involved in the various embodiments is used to illustrate the implementation of this application, and the order of steps is not limited and can be adjusted appropriately as needed.

[0052] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.

[0053] To compensate for insufficient inspection frequency at a lower cost, track condition monitoring on operating high-speed trains has been a research hotspot. Existing research methods mainly include signal processing, inverse solving of dynamic models, or deep learning based on big data. However, existing research still has some shortcomings. For example, compared to accelerometers, gyroscopes installed on the car body or frame are too expensive; the stability of detection systems using axle box acceleration as input needs to be fully verified under different infrastructure and train speed conditions; the inversion accuracy of inverse dynamic solving largely depends on the simplification of the model and the rationality of the dynamic parameters, most of which remain in the theoretical stage and have not been practically verified; deep learning also has adaptability issues for different train models and track conditions. Although the common problem is that the accuracy and stability of the system cannot reach the level of mature measurement systems on track inspection vehicles, from the perspective of ensuring operational safety in real time, compared to accurately measuring the amplitude of track irregularities, track condition monitoring, as a supplementary means between two professional inspections, using relatively simple hardware devices to achieve real-time alarms for exceeding the geometric limits of the track is more important.

[0054] To address the aforementioned problems, this invention provides a method for monitoring track geometry maximum limits, thereby improving the efficiency and accuracy of track geometry maximum limit monitoring. Referring to Figure 22, the method may include:

[0055] Step 2201: Based on the design parameters of the target track and the operating vehicle, establish a wheel-rail interaction model between the operating vehicle and the target track; the dynamic interaction model between the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response;

[0056] Step 2202: Based on the wheel-rail interaction model of the operating vehicle and the target track, establish the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame; the vertical acceleration threshold is used to describe the vertical acceleration of the frame when the track geometric irregularity wavelength of the model is a first preset wavelength at the corresponding speed level; the vertical displacement threshold is used to describe the vertical displacement of the frame when the track geometric irregularity wavelength of the model is a second preset wavelength at the corresponding speed level; the second preset wavelength is greater than the first preset wavelength;

[0057] Step 2203: Based on the speed of the target operating vehicle on the target track, determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to that speed.

[0058] Step 2204: Calculate the vertical displacement of the target vehicle frame on the target track based on the vertical acceleration of the target vehicle frame on the target track;

[0059] Step 2205: When the vertical acceleration of the target frame of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target frame, and the vertical displacement of the target frame of the operating vehicle is greater than or equal to the vertical displacement threshold of the target frame, an alarm message is issued indicating that the target track has experienced a track geometry over-limit event.

[0060] In this embodiment of the invention, a wheel-rail interaction model of the operating vehicle and the target track is established based on the design parameters of the target track and the operating vehicle. The dynamic interaction model of the operating vehicle and the target track is used to simulate the influence of large-value over-limits on the vehicle's dynamic response. Based on the wheel-rail interaction model of the operating vehicle and the target track, a correlation is established between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the frame is used to describe the vertical displacement of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength. Based on the speed of the target operating vehicle on the target track, the corresponding speed is determined. The system calculates the target frame vertical acceleration threshold and target frame vertical displacement threshold at different speed levels. Based on the target frame vertical acceleration of the operating vehicle on the target track, the vertical displacement of the target frame is calculated. When the target frame vertical acceleration of the operating vehicle is greater than or equal to the target frame vertical acceleration threshold, and the target frame vertical displacement of the operating vehicle is greater than or equal to the target frame vertical displacement threshold, an alarm message indicating a track geometric maximum limit exceedance event is issued. By combining the frame vertical acceleration and frame vertical displacement, the system can accurately monitor track geometric maximum limit exceedances, improving the efficiency and accuracy of track geometric maximum limit exceedance monitoring. This solves the problems of high cost, low stability, and low adaptability in existing methods for compensating for insufficient track detection frequency. It provides a technical means for real-time monitoring of line service status and ensuring continuous safe train operation.

[0061] In practice, firstly, based on the design parameters of the target track and the operating vehicle, a wheel-rail interaction model of the operating vehicle and the target track is established; the dynamic interaction model of the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response.

[0062] In one embodiment, based on the target track and the design parameters of the operating vehicle, a wheel-rail interaction model between the operating vehicle and the target track is established, including:

[0063] Based on the vehicle-track dynamic coupling theory, a wheel-rail interaction model between the operating vehicle and the target track is established according to the design parameters of the target track and the operating vehicle. The model includes a vehicle sub-model and a track sub-model. The vehicle sub-model is established based on the dynamic parameters of the target operating vehicle's EMU (Electric Multiple Unit).

[0064] In the above embodiments, the model can also be called a vehicle-track coupled dynamics simulation model. Based on the vehicle-track dynamics coupled dynamics theory, a high-speed train-track dynamic interaction model can be established. The vehicle sub-model is established using the dynamic parameters of the CRH380A high-speed train, consisting of one car body, two bogies, and four wheelsets. Each component considers lateral, heave, roll, pitch, and yaw degrees of freedom, for a total of 35 degrees of freedom for the entire vehicle, as shown in Figure 4. The components are connected by primary and secondary suspensions simplified to spring / damping units, and the nonlinear characteristics of the suspension components are considered. The track sub-model consists of rails, fasteners, and a substructure. The rails are simplified as Euler beams on a continuous elastic discrete-point support foundation, considering lateral, vertical, and torsional motions. Fasteners are simulated using spring-damping units, and the substructure is simplified to uniformly distributed spring-damping units. In the wheel-rail interaction relationship, the normal contact is solved using Hertz theory, and the tangential contact is solved using the FastSim algorithm based on the simplified Kalker theory.

[0065] In specific implementation, after establishing a wheel-rail interaction model between the operating vehicle and the target track based on the design parameters of the target track and the operating vehicle, a correlation is established between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame based on the wheel-rail interaction model of the operating vehicle and the target track. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the frame is used to describe the vertical displacement of the frame when the wavelength of the track geometric irregularity is a second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength.

[0066] In one embodiment, based on the wheel-rail interaction model between the operating vehicle and the target track, the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame is established, including:

[0067] For different operating vehicle speed levels, based on the wheel-rail interaction model of the train and the target track, the vertical acceleration of the first frame when the track geometric irregularity wavelength is a first preset wavelength and the vertical displacement of the first frame when the track geometric irregularity wavelength is a second preset wavelength are determined; the second preset wavelength is greater than the first preset wavelength.

[0068] The vertical acceleration and vertical displacement of the first frame are respectively used as the vertical acceleration threshold and vertical displacement threshold of the frame at this speed level.

[0069] Establish the correlation between the speed level and the vertical acceleration threshold and vertical displacement threshold of the frame at the speed level.

[0070] In one embodiment, the first preset wavelength is 3m; the second preset wavelength can be 9m; at speed levels of (160,250]km / h and (250,350]km / h, the vertical acceleration thresholds for the 2-9m frame can be 0.10 and 0.11, respectively; at speed levels of (160,250]km / h and (250,350]km / h, the vertical displacement thresholds for the frame can be 7.0mm and 5.0mm, respectively.

[0071] In the above embodiments, by establishing the correlation between the speed level and the vertical acceleration threshold and vertical displacement threshold of the frame at the speed level, it is possible to determine whether the target track has experienced a maximum geometric limit event.

[0072] In practice, based on the wheel-rail interaction model of the operating vehicle and the target track, after establishing the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the structure, the target structure vertical acceleration threshold and target structure vertical displacement threshold are determined according to the speed of the target operating vehicle on the target track at the corresponding speed level.

[0073] In practice, after determining the target frame vertical acceleration threshold and target frame vertical displacement threshold at the speed level corresponding to the target operating vehicle speed on the target track, the vertical displacement of the target frame of the operating vehicle on the target track is calculated based on the vertical acceleration of the target frame of the operating vehicle on the target track.

[0074] In one embodiment, calculating the vertical displacement of the target vehicle frame on the target track based on the vertical acceleration of the target vehicle frame on the target track includes:

[0075] The continuous wavelet transform coefficient spectrum of the vertical acceleration of the target vehicle frame on the target track is determined;

[0076] The root mean square of the synchronous compressed wavelet transform coefficients within the preset frequency band is used as the scale-averaged wavelet coefficients.

[0077] The scale-averaged wavelet coefficients are resampled in the same space to obtain the scale-averaged wavelet coefficients in the spatial domain.

[0078] The scale-averaged wavelet coefficients in the spatial domain are smoothed and filtered to obtain the first processed data;

[0079] The first processed data is subjected to anti-aliasing low-pass filtering and debiasing filtering to obtain the second processed data;

[0080] The second processed data is integrated to obtain the vertical displacement of the target vehicle frame on the target track.

[0081] This application primarily addresses short-to-medium wavelength irregularities with wavelengths ranging from 3 to 9 meters, such as the typical large-value overruns (A) shown in Figures 2A and 2B, totaling 15 instances, including 11 on ballasted tracks and 4 on ballastless tracks. These large-value overruns have relatively short wavelengths, often causing subtle sag in the train body, and develop rapidly, resulting in a large number of occurrences. When such large-value overruns occur, the train body response is not significant, making it difficult to detect in a timely manner using the sway meter mounted on operating EMUs. Currently, the inspection cycle for EMUs is twice a month, which can be increased to four times a month under more frequent conditions. However, for large-value overruns occurring between adjacent inspections, there is still no effective means to detect these defects in a timely manner. If the line continues to operate at high speed for several consecutive days under such circumstances, it will seriously endanger the safety of passenger train operations.

[0082] To address the aforementioned issues, in practice, after calculating the vertical displacement of the target vehicle's target frame based on its vertical acceleration, an alarm message indicating that a track geometry over-limit event has occurred is issued when the vertical acceleration of the target vehicle's target frame is greater than or equal to a target frame vertical acceleration threshold, and when the vertical displacement of the target vehicle's target frame is greater than or equal to a target frame vertical displacement threshold.

[0083] In the above embodiments, the alarm information for the occurrence of a track geometry over-limit event on the target track can be issued in a timely manner to supplement the inspection by the on-board track inspection instrument mounted on the operating EMU. It can accurately monitor the track geometry over-limit by combining the vertical acceleration of the structure and the inverse vertical displacement of the structure, providing technical means for real-time monitoring of the service status of the line and ensuring the continuous safe operation of trains.

[0084] The following is a specific embodiment to illustrate the application of the method of the present invention. This embodiment provides a method for monitoring track geometry maximum exceedance based on the acceleration of the operating vehicle frame, which may include the following steps:

[0085] (1) The applicant discovered the following instances of exceeding the maximum geometric limit in the orbit after data analysis:

[0086] In one year, a total of 20 major over-limit violations were detected on high-speed railways across the country, including 16 on ballasted track and 4 on ballastless track. The majority of violations occurred on ballasted track lines, with a maximum of four major over-limit violations occurring at the same location. The statistics by deviation type are shown in Table 1, totaling 31 major over-limit violations. These items are all related to vertical track geometric irregularities (elevation, levelness, and triangular irregularities) or the vertical response of the vehicle body (vertical acceleration).

[0087] Table 1

[0088] Deviation Type Quantity (items) Horizontal 1 Long Wave Height 3 4 2m Height 8 Vehicle Body Vertical Acceleration 7 Triangular Pit 1 2 surface

[0089] Figure 1 shows the changes in track geometry irregularities compared to the previous test, with 65% of the locations showing changes exceeding 4 mm. This indicates that a large proportion of the track geometry changes abruptly between the two tests.

[0090] (2) Wavelength characteristics analysis based on synchronous compressed wavelet transform

[0091] Large-value exceedances often represent abrupt changes in orbital geometry over a short mileage range. Fourier transform is insensitive to such narrow-range signal variations; short-time Fourier transform has a fixed time resolution and cannot effectively reflect the degree of signal abrupt changes; wavelet transform also suffers from insufficient low-frequency spatial resolution, poor high-frequency resolution, and poor energy concentration. Therefore, synchronous compressed wavelet transform is used to analyze the time-frequency distribution characteristics of large-value exceedance detection data in orbital geometry. By combining phase information near the instantaneous frequency of the signal with wavelet transform data to reconstruct the time-frequency distribution, it can significantly improve time-frequency resolution and energy concentration, thereby enhancing the readability of the time-frequency distribution.

[0092] The track irregularity data sampled at spatial intervals of 0.25m are subjected to synchronous compressed wavelet transform to obtain the synchronous compressed wavelet transform spectrum T. s (ξ l ,x m ), where ξ l Let x be the l-th spatial sampling frequency. m Let m be the spatial mileage at point m. Then, extract the synchronous compressed wavelet transform spectrum T within a 10m range before and after the point where the mileage exceeds the maximum value limit. s (ξ l ,x m The mean of the sum of squares of each spatial sampling frequency is calculated using the following formula, i.e., a second compression is performed along the mileage direction to obtain the global wavelet power spectrum G. s (ζ l (globalwavelet power spectrum, GWPS) represents the wavelength distribution of orbital irregularities within a narrow range.

[0093]

[0094] In the formula, ω l Let x be the l-th discrete angular frequency. m Let M be the mileage translation factor of the m-th point within the narrow interval, and M be the total number of sampling points within the narrow interval.

[0095] Taking two typical locations with large value exceeding the limit as examples, the global wavelet power spectrum is shown in Figure 2A as the characteristic of dynamic detection data of typical large value exceeding the limit A, and in Figure 2B as the characteristic of dynamic detection data of typical large value exceeding the limit B.

[0096] ① For the typical large-value over-limit A, the characteristic wavelength is approximately 6.0m. The maximum value of the unevenness at 42m increased from -6.7mm to -12.6mm within half a month (between two tests), reaching the Class III over-limit (11mm), a change of 5.9mm. However, the peak vertical acceleration of the vehicle body was only -0.7m / s². 2 Furthermore, the vehicle-mounted circuit checker did not trigger any alarms of Level I or above between the two adjacent testing intervals.

[0097] ② For the typical large-value over-limit B, the characteristic wavelength is approximately 42.5m. The maximum value of the vertical irregularity at 42m increased from 3.9mm to 4.9mm within half a month, a relatively small change and not exceeding the limit. The peak value of the vertical irregularity at 70m increased from 7.4mm to 9.9mm, constituting a Class I over-limit (6mm). However, the peak value of the vehicle's vertical acceleration increased from 1.2m / s². 2 Increased to 2.2 m / s 2 This constitutes a Class IV exceedance (2.0 m / s). 2 Furthermore, the vehicle-mounted line inspection instrument triggered five Level II vertical alarms between two adjacent testing intervals.

[0098] In summary, the characteristics of large value exceeding limits can be summarized as follows: when the wavelength of the unevenness is short, although the amplitude is large, the vertical acceleration response of the vehicle body may not be significant; when the wavelength of the unevenness is long, although the amplitude is small, the vertical acceleration amplitude of the vehicle body may be large. This rule is closely related to the vehicle body's sensitive wavelength.

[0099] (3) Characteristics and classification of the maximum geometric limit of the orbit.

[0100] Figure 3 shows the wavelength distribution of 20 track irregularities exceeding the limit. Based on the waveform and wavelength characteristics of the track irregularities and the vertical acceleration response of the vehicle body, the large-value over-limits can be divided into two categories.

[0101] The first type is mid-to-long-wave irregularities with wavelengths around 20-50m, mainly manifested as excessive vertical acceleration of the train body, while the amplitude of the irregularity is generally not yet exceeded. For example, in Figure 3, there are six typical large-value over-limit B instances, all caused by differential settlement at the junction of ballasted track and culverts. Trains may experience large-value over-limit vertical acceleration under unrestricted speed conditions. These large-value over-limits can be directly monitored using an onboard track inspection instrument.

[0102] The second type is short-to-medium wavelength irregularities with wavelengths around 3–9 m, such as the typical large-value overruns A shown in Figures 2A and 2B, totaling 15 locations, including 11 on ballasted tracks and 4 on ballastless tracks. These large-value overruns have shorter wavelengths, often causing less noticeable sag on the train body, and develop rapidly, resulting in a large number of occurrences. When these large-value overruns occur, the train body response is not significant, making them difficult to detect in a timely manner using the sway meter mounted on operating EMUs. Currently, the inspection cycle for EMUs is twice a month, which can be increased to four times a month under more frequent conditions. However, for large-value overruns occurring between adjacent inspections, there is still no effective means to detect these defects in a timely manner. If the line continues to operate at high speed for several days under these circumstances, it will seriously endanger the safety of passenger train operations. To compensate for the current deficiencies in track condition monitoring methods, this paper will focus on the second type of large-value overruns in subsequent research.

[0103] (4) Then, construct a vehicle-track coupled dynamics simulation model.

[0104] A model of high-speed train-track dynamic interaction is established based on the vehicle-track dynamic coupling dynamics theory.

[0105] The vehicle sub-model is established using the dynamic parameters of the CRH380A high-speed train, consisting of one car body, two bogies, and four wheelsets. Each component considers lateral, heave, roll, pitch, and yaw degrees of freedom, for a total of 35 degrees of freedom for the entire vehicle, as shown in Figure 4. The components are connected by a simplified primary and secondary suspension system consisting of spring / damping units, and the nonlinear characteristics of the suspension components are considered.

[0106] The track sub-model consists of rails, fasteners, and a substructure. The rails are simplified as Euler beams on a continuous elastic discrete-point support foundation, considering lateral, vertical, and torsional motions. The fasteners are simulated using spring-damped elements, and the substructure is simplified as uniformly distributed spring-damped elements.

[0107] In the wheel-rail interaction relationship, the normal contact can be solved using Hertz theory, while the tangential contact can be solved using the FastSim algorithm based on the simplified Kalker theory.

[0108] The track geometry exceeding the limits often exhibits a low-collapse type of single-wave elevation irregularity. Therefore, the elevation irregularities of the left and right tracks are simulated using in-phase simple harmonic functions, as shown in Figure 5. The irregularity wavelength increases from 1m to 200m, and the amplitude increases from 1mm to 20mm. The simulated train speed increases from 200km / h to 350km / h.

[0109] (5) Comparative analysis of the vertical acceleration sensitivity of the vehicle body and frame

[0110] The simulation results of the vehicle body's vertical acceleration are shown in Figure 6. Under the same height and roughness amplitude conditions, when the vehicle speed is 250 km / h, the response amplitude is larger when the roughness wavelength is below 3 m, near 10 m and 17 m; when the vehicle speed is 350 km / h, the response amplitude is larger when the roughness wavelength is below 3 m, near 10 m and 22 m.

[0111] The second type of large-value over-limit characteristic band is 3-9m, and the vertical acceleration of the vehicle body has a relatively small amplitude in this band.

[0112] The vehicle's vertical acceleration was subjected to a 20Hz low-pass filter according to specifications, and the results are shown in Figure 7. At speeds of 250km / h and 350km / h, the 20Hz low-pass filtered vertical acceleration showed significant attenuation below wavelengths of 3.5m and 4.9m, respectively.

[0113] In conclusion, the vehicle body vertical acceleration evaluation method is insufficient to effectively evaluate the mid-to-short wave roughness characteristics below 10m.

[0114] The simulation results of the vertical acceleration of the frame are shown in Figure 8. Under the same height irregularity amplitude, the vertical acceleration response of the frame is mainly concentrated below the wavelength of 10m. It can be predicted that using the vertical acceleration of the frame to evaluate the large value exceeding the limit of medium and short wavelength irregularities of 3-9m will be more targeted.

[0115] (6) Comparative analysis of the sensitivity of the car body and frame to vertical displacement

[0116] The simulation results of the vehicle body vertical displacement are shown in Figure 9. Under the same irregularity amplitude, the peak value of the vehicle body vertical displacement first increases and then slowly decreases with the increase of wavelength. Combining the contour lines in the figure, it can be seen that when the irregularity wavelength increases to about 60m, the peak value of the vehicle body vertical displacement reaches the same level as the input irregularity amplitude, and the peak value of the vehicle body vertical displacement reaches its maximum value near 100m.

[0117] The simulation results of the vertical displacement of the frame are shown in Figure 10. Under the same irregularity amplitude, the peak value of the vertical displacement of the frame shows a characteristic of first increasing and then slowly decreasing with the increase of wavelength. Combining the contour lines in the figure, it can be seen that when the irregularity wavelength increases to about 25m, the peak value of the vertical displacement of the frame reaches the same level as the input irregularity amplitude, and the peak value of the vertical displacement of the frame reaches its maximum value near 60m.

[0118] When there is no gap between the wheel and the rail, the vertical displacement of the axle box can be considered to be consistent with the elevation irregularity. The vibration of the car body and frame is affected by the primary and secondary suspension systems of the train, and their vertical displacement does not completely follow the elevation irregularity. Only when the wavelength is sufficiently large can the vertical displacement of the car body and frame reach the same level as the irregularity amplitude. When an elevation irregularity excitation with a wavelength of 3–9 m is input, the vertical displacement of the car body and frame is smaller than the irregularity amplitude.

[0119] (7) Evaluation method for vertical acceleration of the frame

[0120] Based on time-frequency analysis, the vertical acceleration of the frame was evaluated by extracting components in the 2–9 m band. The processing flow is shown in Figure 11.

[0121] The continuous wavelet transform coefficient spectrum W of the vertical acceleration s(t) of the structure s (a,b) is:

[0122]

[0123] In the formula, t represents time. Let be the complex conjugate of the mother wavelet function, and a and b be the scaling factor and time shift factor, respectively.

[0124] The wavelet transform coefficient spectrum is prone to energy diffusion along the scale direction, causing ambiguity in the time spectrum, but its phase information is unaffected by scale. When the wavelet transform coefficient spectrum W at any point... s When (a,b)≠0, the instantaneous frequency ω of the vertical acceleration s(t) of the structure. s (a,b) is:

[0125]

[0126] This transforms the wavelet transform coefficient spectrum from the time-scale domain (b, a) to the time-frequency domain (b, ω). s (a,b)), ω s (a,b) is abbreviated as ω(a,b). In reality, the vertical acceleration of the structure is a discrete signal sampled at 5000Hz; therefore, both the scale parameter and the frequency parameter are discrete values, with a scale step size Δa. k =a k -a k-1 Frequency step size Δω=ω l -ω l-1 The time-scale distribution of the wavelet transform is redistributed as follows:

[0127]

[0128] In the formula, T s To synchronously compress the wavelet transform values, ω l Let a be the l-th discrete angular frequency. k For the k-th discrete scale, b n This is the nth time sampling point.

[0129] As can be seen from the above equation, synchronous compression concentrates the time-frequency energy after continuous wavelet transform into the instantaneous frequency direction, thereby improving the time-frequency resolution.

[0130] Since the wavelengths of the second type of large-value exceedance are distributed in the range of approximately 3–9 m, and considering that the wheelbase of the EMU bogie is generally 2.5 m or 2.7 m, and the baseline length of the triangular pit is 3 m, the evaluation band is extended to 2–9 m, thus obtaining the upper limit of the spatial frequency ξ. u and lower limit ξ d These are 1 / 2 and 1 / 9 m⁻¹, respectively. To accommodate the effects of vehicle speed changes, the spatial frequency upper and lower limits are converted to the angular frequency upper and lower limits using the following formula.

[0131]

[0132] In the formula, v n The speed at point n is expressed in km / h. -1 .

[0133] The root mean square of the synchronous compressed wavelet transform coefficients within a specified frequency band is defined as the scale-averaged wavelet coefficient (SAWC), calculated as follows:

[0134]

[0135] In the formula, L n This specifies the number of discrete angular frequency sampling points within the specified frequency band at point n.

[0136] The scale-averaged wavelet coefficients of the vertical acceleration of the structure in the time domain are resampled in the same space to obtain the scale-averaged wavelet coefficients C in the spatial domain. j Then, a Savitzky-Golay smoothing filter was applied to C. j A smoothing filter with a window length of 2m is applied, and this is used as the evaluation result of the vertical acceleration of the structure. The polynomial order is taken as 2.

[0137] (8) Method for solving vertical displacement of the frame

[0138] The vertical displacement of the frame is solved by the second integral of the vertical acceleration of the frame. Considering the influence of the vehicle's variable speed operation, the processing flow is shown in Figure 12.

[0139] The measured vertical acceleration sampling frequency of the structure is as high as 5000Hz. Resampling at a constant spatial distance of 0.25m will reduce the sampling frequency, thus reducing subsequent computational load. To prevent low-frequency aliasing, an anti-aliasing low-pass filter is first applied to the equal-time sampled signal. Specifically, a linear-phase FIR low-pass filter is designed using the Parks-McClellan algorithm. Then, a debiased filter is used to remove the DC component from the acceleration signal, thereby weakening the trend term generated by the second-order time-domain integral. Its transfer function is as follows:

[0140]

[0141] In the formula, ρ represents the filter coefficients.

[0142] The mileage is obtained by accumulating vehicle speed using the following formula. Mapping acceleration signals from the time domain to the spatial domain.

[0143]

[0144] In the formula, Δt is the time sampling interval of the acceleration signal, and x0 is the initial mileage.

[0145] Then, the preprocessed vertical acceleration and other spatial parameters of the structure are resampled to obtain spatial integrals. Based on the rectangular integral, the transfer function of the quadratic integral filter can be derived as follows:

[0146]

[0147] In the formula, ΔT j is the time interval between the j-th and j-1th equal spatial sampling points.

[0148] The cutoff wavelength for the large values ​​of uneven heights is mainly 42m. Therefore, the same method is used to design a linear phase FIR high-pass filter to obtain the vertical displacement of the structure within the 42m wavelength range.

[0149] (9) A joint evaluation method based on acceleration and displacement response:

[0150] Extensive experimental data revealed that within the track irregularity wavelength range of 2–9 m, the energy carried by the structural acceleration is easily affected by variable cross-section track structures such as turnouts and temperature regulators, thus exhibiting a certain degree of randomness. Therefore, a joint evaluation of structural vertical acceleration and vertical displacement is proposed to improve the accuracy of the method. First, considering the wavelength characteristics of the second type of large-value exceedance, the structural vertical acceleration is evaluated using scale-averaged wavelet coefficients to identify locations with large vertical impact responses within the 2–9 m band. Then, considering the large amplitude of the second type of large-value exceedance, the method for solving the structural vertical acceleration and vertical displacement is processed. Based on the first evaluation, a second evaluation is performed using the structural vertical displacement, thereby achieving accurate identification of large-value exceedances in track geometry. The evaluation threshold will be discussed in the following section.

[0151] Table 2 shows the dynamic operation management values ​​for local peak values ​​at 42m elevation unevenness in the standard. It can be seen that the management values ​​for levels III and IV under the 350km / h condition are more stringent than those under the 250km / h condition, and the management values ​​for levels III and IV are closer.

[0152] Table 2

[0153] Speed ​​rating: Level I, Level II, Level III, Level IV (160, 250] km / h 581114 (250, 350] km / h 56810 surface

[0154] Figure 13 shows the simulation results of the vertical acceleration of the frame under Level III and Level IV conditions. As the wavelength of the irregularity increases, the vertical acceleration of the frame gradually decreases, and the deceleration tends to level off. When the wavelength is greater than 2m, the peak values ​​of the vertical acceleration of the frame under Level III conditions with varying degrees of irregularity are comparable at speeds of 250km / h and 350km / h. The Level IV standard at 250km / h is 4mm larger than that at 350km / h, resulting in a larger amplitude of the vertical acceleration response of the frame.

[0155] Figure 14 shows the simulation results of the vertical acceleration SAWC of the 2–9m frame under Level III and Level IV conditions. When the wavelength is greater than 2m, the peak value of the vertical acceleration SAWC of the frame gradually decreases with increasing wavelength. When the wavelength increases to 10m, the peak value of SAWC has dropped to about 0.01. The shortest wavelength of the second type of over-limit is about 3m, and the baseline length of the triangular pit is also 3m. Therefore, the acceleration SAWC threshold can be determined with reference to the frame response under the 3m condition. The peak values ​​of the vertical acceleration SAWC of the frame at this wavelength under various uneven height levels are shown in Table 3. Based on this table, the vertical acceleration SAWC thresholds of the 2–9m frame can be taken as 0.10 and 0.11 at speed levels of (160, 250] km / h and (250, 350] km / h, respectively.

[0156] Table 3

[0157] Vehicle Speed ​​ / (km / h) Ⅰ Ⅱ Ⅲ Ⅳ 2000.03 0.05 0.07 0.11 2500.04 0.07 0.10 0.15 3000.05 0.07 0.09 0.11 3500.07 0.08 0.11 0.13 surface

[0158] Figure 15 shows the simulation results of the vertical displacement of the frame under Level III and Level IV conditions. It can be seen that the vertical displacement of the frame at 350 km / h under both Level III and Level IV conditions is consistently less than that at 250 km / h under Level III conditions. At 250 km / h, the unevenness of the height between Level III and Level IV at a wavelength of 10 m causes the peak vertical displacement of the frame to reach 7.3 mm and 9.3 mm, respectively; at 350 km / h, the peak values ​​are 4.6 mm and 5.7 mm, respectively. Therefore, the vertical displacement of the frame under Level III conditions is rounded down as the threshold value, and taken as 7.0 mm and 5.0 mm at speed levels of (160, 250] km / h and (250, 350] km / h, respectively.

[0159] In summary, the key technical points of this invention are: 1. Comparative analysis results of the sensitivity of the car body and frame vertical displacement; 2. Monitoring of track geometric maximum limits by combining frame vertical acceleration and vertical displacement. This specific embodiment utilizes an onboard track inspection instrument mounted on an operating EMU for supplementary inspection. By combining frame vertical acceleration and the inverted frame vertical displacement, it can accurately monitor track geometric maximum limits, providing a technical means to monitor the real-time service status of the track and ensure the continuous safe operation of trains.

[0160] The application effects of this specific embodiment are described in detail below:

[0161] (1) Verification of the effectiveness of the embodiments of the present invention using a ballasted track:

[0162] Taking a ballasted high-speed railway with a design speed of 250 km / h as an example, the measured track irregularities are compared with the measured vertical displacement of the structure as shown in Figure 16, and the measured triangular pit is shown in Figure 17. The amplitude of the vertical irregularity at K227+545 reaches 8.7 mm, which is only a Class II over-limit, while the amplitude of the triangular pit is -11.9 mm, which reaches a Class IV over-limit.

[0163] The train passed at a speed of 240 km / h, and the measured vertical acceleration of the framework was processed according to the method presented in this paper. The SAWC of the vertical acceleration of the framework from 2 to 9 m is shown in Figure 18. It reaches 0.11 at K227+545, exceeding the threshold (0.10) for this speed level, and is therefore rated as exceeding the limit. The inversion results of the vertical displacement of the framework are shown in Figure 16. It can be seen that the vertical displacement of the framework closely resembles the characteristics of elevation irregularities, although the vertical displacement is slightly smaller than that of elevation irregularities, verifying the accuracy of the method for solving the vertical displacement of the framework. The vertical displacement of the framework reaches 7.4 mm at K227+545, exceeding the threshold (7.0 mm) for this speed level, and is also rated as exceeding the limit at this location. In summary, the two-step joint evaluation of the vertical acceleration and displacement response of the framework accurately identifies the maximum geometric limit exceeding the track limit.

[0164] (2) Verification of the effectiveness of the embodiments of the present invention using ballastless track:

[0165] Taking a ballastless high-speed railway designed for a speed of 350 km / h as an example, the measured track irregularities are shown in Figures 19 and 20. At K886+623, the amplitude of the vertical irregularity reaches 6.0 mm, which is a Class II over-limit. The amplitude of the triangular pit is -6.0 mm, also a Class II over-limit. This location is at the joint of a 32m simply supported beam, and the waveform characteristics of the vertical irregularity are similar to those of a low-collapse type with a large value over-limit, with a wavelength between 3 and 9m.

[0166] The train passed through at a speed of 303 km / h. The measured vertical acceleration of the structure was processed according to the method presented in this paper, and the results are shown in Figure 21. This section is a continuous simply supported beam bridge section. The angle of the beam joint is mapped onto the rail surface to form a series of continuous low-collapse unevennesses with characteristic wavelengths between 3 and 9 m and peak intervals of adjacent unevennesses of 32.7 m. The train was continuously disturbed by the low-collapse unevennesses at the beam joints in this section, resulting in a large amplitude of the vertical acceleration (SAWC) of the structure. There were 5 locations that exceeded the threshold (0.11) for this speed level, with the vertical acceleration (SAWC) at K886+623 (location ③) reaching 0.15. The vertical displacement inversion results of the structure are shown in Figure 19. The maximum vertical displacement of the structure corresponding to these 5 acceleration exceedance points is -4.1 mm (location ③) and the minimum is -1.9 mm (location ①), all of which did not exceed the threshold (5.0 mm) for this speed level. Therefore, this section was assessed as not having any major exceedances. In reality, this area only exhibited Level II exceedances due to elevation differences and triangular pits, and indeed, no major exceedances were found. In conclusion, a two-step joint evaluation of the framework's vertical acceleration and displacement response can reduce false alarms of major exceedances in track geometry.

[0167] Of course, it is understood that there may be other variations of the above detailed process, and all such variations should fall within the protection scope of this invention.

[0168] As described above, this invention aims to achieve real-time alarm for maximum geometric limits on railway tracks in an economical and simple manner. First, it analyzes the characteristics of maximum geometric limits on high-speed railway tracks over the past year from the perspectives of causes and wavelength. A vehicle-track coupled dynamics simulation model is established to study the impact of maximum limits on vehicle dynamic response. A monitoring technology combining vertical acceleration and vertical displacement of the track structure for maximum geometric limits is proposed, and the rationality of the method and threshold is verified through measured data. This aims to overcome the shortcomings of current methods for monitoring maximum geometric limits on tracks and provide technical means for real-time monitoring of track service status and ensuring the continuous safe operation of trains.

[0169] This invention also provides a track geometry maximum limit monitoring device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the track geometry maximum limit monitoring method, the implementation of this device can refer to the implementation of the track geometry maximum limit monitoring method; repeated details will not be elaborated further.

[0170] This invention also provides a track geometry maximum limit monitoring device to improve the efficiency and accuracy of track geometry maximum limit monitoring, as shown in Figure 23. The device includes:

[0171] The model building module 2301 is used to build a wheel-rail interaction model between the operating vehicle and the target track based on the design parameters of the target track and the operating vehicle; the dynamic interaction model between the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response.

[0172] The correlation establishment module 2302 is used to establish the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame based on the wheel-rail interaction model of the operating vehicle and the target track. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the frame is used to describe the vertical displacement of the frame when the wavelength of the track geometric irregularity is a second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength.

[0173] The threshold determination module 2303 is used to determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to the target operating vehicle speed on the target track.

[0174] The target frame vertical displacement calculation module 2304 is used to calculate the vertical displacement of the target frame of the operating vehicle on the target track based on the vertical acceleration of the target frame of the operating vehicle on the target track.

[0175] The monitoring module 2305 is used to issue an alarm message indicating that a track geometry over-limit event has occurred on the target track when the vertical acceleration of the target frame of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target frame and the vertical displacement of the target frame of the operating vehicle is greater than or equal to the vertical displacement threshold of the target frame.

[0176] In one embodiment, the model building module is specifically used for:

[0177] Based on the vehicle-track dynamic coupling theory, a wheel-rail interaction model between the operating vehicle and the target track is established according to the design parameters of the target track and the operating vehicle. The model includes a vehicle sub-model and a track sub-model. The vehicle sub-model is established based on the dynamic parameters of the target operating vehicle's EMU (Electric Multiple Unit).

[0178] In one embodiment, the association establishment module is specifically used for:

[0179] For different operating vehicle speed levels, based on the wheel-rail interaction model of the train and the target track, the vertical acceleration of the first frame when the track geometric irregularity wavelength is a first preset wavelength and the vertical displacement of the first frame when the track geometric irregularity wavelength is a second preset wavelength are determined; the second preset wavelength is greater than the first preset wavelength.

[0180] The vertical acceleration and vertical displacement of the first frame are respectively used as the vertical acceleration threshold and vertical displacement threshold of the frame at this speed level.

[0181] Establish the correlation between the speed level and the vertical acceleration threshold and vertical displacement threshold of the frame at the speed level.

[0182] In one embodiment, the target frame vertical displacement calculation module is specifically used for:

[0183] The continuous wavelet transform coefficient spectrum of the vertical acceleration of the target vehicle frame on the target track is determined;

[0184] The root mean square of the synchronous compressed wavelet transform coefficients within the preset frequency band is used as the scale-averaged wavelet coefficients.

[0185] The scale-averaged wavelet coefficients are resampled in the same space to obtain the scale-averaged wavelet coefficients in the spatial domain.

[0186] The scale-averaged wavelet coefficients in the spatial domain are smoothed and filtered to obtain the first processed data;

[0187] The first processed data is subjected to anti-aliasing low-pass filtering and debiasing filtering to obtain the second processed data;

[0188] The second processed data is integrated to obtain the vertical displacement of the target vehicle frame on the target track.

[0189] This invention provides an embodiment of a computer device for implementing all or part of the above-described method for monitoring maximum track geometric values. The computer device specifically includes the following components:

[0190] The computer device comprises a processor, memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to realize information transmission between related devices; the computer device can be a desktop computer, tablet computer, or mobile terminal, etc., and this embodiment is not limited to these. In this embodiment, the computer device can be implemented with reference to the embodiments for implementing the method for monitoring the maximum geometric limit of a track and the embodiments for implementing the device for monitoring the maximum geometric limit of a track, the contents of which are incorporated herein by reference, and repeated details will not be described again.

[0191] Figure 24 is a schematic block diagram of the system configuration of a computer device 1000 according to an embodiment of this application. As shown in Figure 24, the computer device 1000 may include a central processing unit 1001 and a memory 1002; the memory 1002 is coupled to the central processing unit 1001. It is worth noting that Figure 24 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunications functions or other functions.

[0192] In one embodiment, the track geometry maximum value exceedance monitoring function can be integrated into the central processing unit 1001. The central processing unit 1001 can be configured to perform the following control:

[0193] Based on the design parameters of the target track and the operating vehicle, a wheel-rail interaction model between the operating vehicle and the target track is established; the dynamic interaction model between the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response.

[0194] Based on a wheel-rail interaction model of the operating vehicle and the target track, a correlation is established between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame. The vertical acceleration threshold is used to describe the vertical acceleration of the frame when the track geometric irregularity wavelength is a first preset wavelength at the corresponding speed level. The vertical displacement threshold is used to describe the vertical displacement of the frame when the track geometric irregularity wavelength is a second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength.

[0195] Based on the speed of the target operating vehicle on the target track, determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to that speed.

[0196] The vertical displacement of the target vehicle frame on the target track is calculated based on the vertical acceleration of the target vehicle frame on the target track.

[0197] When the vertical acceleration of the target structure of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target structure, and the vertical displacement of the target structure of the operating vehicle is greater than or equal to the vertical displacement threshold of the target structure, an alarm message is issued indicating that the target track has experienced a track geometry over-limit event.

[0198] In another embodiment, the track geometry maximum limit monitoring device can be configured separately from the central processing unit 1001. For example, the track geometry maximum limit monitoring device can be configured as a chip connected to the central processing unit 1001, and the track geometry maximum limit monitoring function can be realized through the control of the central processing unit.

[0199] As shown in Figure 24, the computer device 1000 may further 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 include all the components shown in Figure 24; furthermore, the computer device 1000 may also include components not shown in Figure 24, as can be found in existing technologies.

[0200] As shown in Figure 24, the central processing unit 1001, sometimes also referred to as a controller or operation control, may include a microprocessor or other processor device and / or logic device. The central processing unit 1001 receives input and controls the operation of various components of the computer device 1000.

[0201] The memory 1002 may be, for example, one or more of a cache, flash memory, hard drive, removable medium, volatile memory, non-volatile memory, or other suitable device. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 1001 may execute the program stored in the memory 1002 to perform information storage or processing, etc.

[0202] Input unit 1004 provides input to central processing unit 1001. This input unit 1004 may be, for example, a keypad or touch input device. Power supply 1007 provides power to computer device 1000. Display 1006 displays images, text, and other display objects. This display may be, for example, an LCD display, but is not limited to this.

[0203] The memory 1002 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs, etc. The memory 1002 can 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 for storing application programs and function programs or processes for executing operations of the computer device 1000 via the central processing unit 1001.

[0204] 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 performing other functions of the computer device (such as messaging applications, address book applications, etc.).

[0205] The communication module 1003 is a transmitter / receiver 1003 that transmits and receives signals via the antenna 1008. The communication module (transmitter / receiver) 1003 is coupled to the central processing unit 1001 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.

[0206] Based on different communication technologies, multiple communication modules 1003 can be configured in the same computer device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 1003 is also coupled to a speaker 1009 and a microphone 1010 via an audio processor 1005 to provide audio output via the speaker 1009 and receive audio input from the microphone 1010, thereby realizing typical telecommunications functions. The audio processor 1005 may include any suitable buffer, decoder, amplifier, etc. Furthermore, the audio processor 1005 is also coupled to a central processing unit 1001, enabling on-device recording via the microphone 1010 and on-device playback of stored sound via the speaker 1009.

[0207] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for monitoring the maximum value exceeding the orbital geometry limit.

[0208] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for monitoring the maximum value exceeding the orbital geometry limit.

[0209] In this embodiment of the invention, a wheel-rail interaction model of the operating vehicle and the target track is established based on the design parameters of the target track and the operating vehicle. The dynamic interaction model of the operating vehicle and the target track is used to simulate the influence of large-value over-limits on the vehicle's dynamic response. Based on the wheel-rail interaction model of the operating vehicle and the target track, a correlation is established between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the frame is used to describe the vertical displacement of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength. Based on the speed of the target operating vehicle on the target track, the corresponding speed is determined. The system calculates the target frame vertical acceleration threshold and target frame vertical displacement threshold at different speed levels. Based on the target frame vertical acceleration of the operating vehicle on the target track, the vertical displacement of the target frame is calculated. When the target frame vertical acceleration of the operating vehicle is greater than or equal to the target frame vertical acceleration threshold, and the target frame vertical displacement of the operating vehicle is greater than or equal to the target frame vertical displacement threshold, an alarm message indicating a track geometric maximum limit exceedance event is issued. By combining the frame vertical acceleration and frame vertical displacement, the system can accurately monitor track geometric maximum limit exceedances, improving the efficiency and accuracy of track geometric maximum limit exceedance monitoring. This solves the problems of high cost, low stability, and low adaptability in existing methods for compensating for insufficient track detection frequency. It provides a technical means for real-time monitoring of line service status and ensuring continuous safe train operation.

[0210] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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.

[0211] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0212] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0213] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0214] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are 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 within the scope of protection of the present invention.

Claims

1. A method for monitoring excessive limits in track geometry, characterized in that, include: Based on the design parameters of the target track and the operating vehicle, a wheel-rail interaction model of the operating vehicle and the target track is established. The dynamic interaction model of the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the dynamic response of the vehicle. Based on the wheel-rail interaction model of the operating vehicle and the target track, the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame is established. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the track geometric irregularity wavelength is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the structure is used to describe the vertical displacement of the structure when the wavelength of the track geometric irregularity is the second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength; Based on the speed of the target operating vehicle on the target track, determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to that speed. The vertical displacement of the target vehicle frame on the target track is calculated based on the vertical acceleration of the target vehicle frame on the target track. When the vertical acceleration of the target frame of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target frame, and the vertical displacement of the target frame of the operating vehicle is greater than or equal to the vertical displacement threshold of the target frame, an alarm message is issued indicating that the target track has experienced a track geometry maximum value exceedance event. Based on the design parameters of the target track and the operating vehicle, a wheel-rail interaction model of the operating vehicle and the target track is established, including: based on the vehicle-track dynamic coupling dynamics theory, and according to the design parameters of the target track and the operating vehicle, a wheel-rail interaction model of the operating vehicle and the target track is established; the model includes a vehicle sub-model and a track sub-model; the vehicle sub-model is established based on the dynamic parameters of the target operating vehicle's EMU; based on the vertical acceleration of the target structure of the operating vehicle on the target track, the vertical displacement of the target structure of the operating vehicle on the target track is calculated, including: determining the continuous wavelet transform coefficient spectrum of the vertical acceleration of the target structure of the operating vehicle on the target track; using the root mean square of the synchronous compressed wavelet transform coefficients in a preset frequency band as the scale-averaged wavelet coefficients; performing equal spatial resampling on the scale-averaged wavelet coefficients to obtain the scale-averaged wavelet coefficients in the spatial domain; performing smoothing filtering on the scale-averaged wavelet coefficients in the spatial domain to obtain the first processed data; performing anti-aliasing low-pass filtering and debiased filtering on the first processed data to obtain the second processed data; performing integral calculation on the second processed data to obtain the vertical displacement of the target structure of the operating vehicle on the target track.

2. The method as described in claim 1, characterized in that, Based on the wheel-rail interaction model of the operating vehicle and the target track, the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame is established. This includes: for different speed levels of the operating vehicle, based on the wheel-rail interaction model of the train and the target track, determining the first vertical acceleration of the frame when the wavelength of the track geometric irregularity is a first preset wavelength at that speed level, and the first vertical displacement of the frame when the wavelength of the track geometric irregularity is a second preset wavelength at that speed level; the second preset wavelength is greater than the first preset wavelength; the first vertical acceleration of the frame and the first vertical displacement of the frame are respectively used as the vertical acceleration threshold and the vertical displacement threshold of the frame at that speed level; and establishing the correlation between that speed level and the vertical acceleration threshold and the vertical displacement threshold of the frame at that speed level.

3. A device for monitoring excessive limits in track geometry, characterized in that, include: The model building module is used to establish a wheel-rail interaction model between the operating vehicle and the target track based on the design parameters of the target track and the operating vehicle. The dynamic interaction model between the operating vehicle and the target track is used to simulate the influence of large-value over-limit on the vehicle's dynamic response. The correlation module is used to establish the correlation between different speed levels of the operating vehicle and the vertical acceleration threshold and vertical displacement threshold of the frame based on the wheel-rail interaction model between the operating vehicle and the target track. The vertical acceleration threshold of the frame is used to describe the vertical acceleration of the frame when the track geometric irregularity wavelength is a first preset wavelength at the corresponding speed level. The vertical displacement threshold of the structure is used to describe the vertical displacement of the structure when the wavelength of the track geometric irregularity is the second preset wavelength at the corresponding speed level. The second preset wavelength is greater than the first preset wavelength; The threshold determination module is used to determine the vertical acceleration threshold and vertical displacement threshold of the target structure at the speed level corresponding to the target operating vehicle speed on the target track. The target frame vertical displacement calculation module is used to calculate the vertical displacement of the target frame of the operating vehicle on the target track based on the vertical acceleration of the target frame of the operating vehicle on the target track. The monitoring module is used to issue an alarm message indicating that the target track has experienced a track geometry over-limit event when the vertical acceleration of the target frame of the operating vehicle is greater than or equal to the vertical acceleration threshold of the target frame and the vertical displacement of the target frame of the operating vehicle is greater than or equal to the vertical displacement threshold of the target frame. The model building module is specifically used for: establishing a wheel-rail interaction model between the operating vehicle and the target track based on the vehicle-track dynamic coupling theory and the design parameters of the target track and the operating vehicle; the model includes a vehicle sub-model and a track sub-model; the vehicle sub-model is established based on the dynamic parameters of the target operating vehicle's EMU (Electric Multiple Unit) system. The target frame vertical displacement calculation module is specifically used for: determining the continuous wavelet transform coefficient spectrum of the vertical acceleration of the target frame of the operating vehicle on the target track; using the root mean square of the synchronous compressed wavelet transform coefficients within a preset frequency band as the scale-averaged wavelet coefficients; performing equal spatial resampling on the scale-averaged wavelet coefficients to obtain the scale-averaged wavelet coefficients in the spatial domain; performing smoothing filtering on the scale-averaged wavelet coefficients in the spatial domain to obtain first processed data; performing anti-aliasing low-pass filtering and debiased filtering on the first processed data to obtain second processed data; and performing integral calculation on the second processed data to obtain the vertical displacement of the target frame of the operating vehicle on the target track.

4. The apparatus as described in claim 3, characterized in that, The correlation establishment module is specifically used for: determining the first frame vertical acceleration and the first frame vertical displacement when the track geometric irregularity wavelength is a first preset wavelength at the speed level, based on the wheel-rail interaction model of the train and the target track, for different operating vehicle speed levels. The second preset wavelength is greater than the first preset wavelength; The vertical acceleration and vertical displacement of the first frame are used as the vertical acceleration threshold and vertical displacement threshold of the frame at the speed level, respectively; the correlation between the speed level and the vertical acceleration threshold and vertical displacement threshold of the frame at the speed level is established.

5. 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, it implements the method of any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 2.

7. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 2.

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