Rail grinding quality assessment method and device

Abstract

The application discloses a rail grinding quality evaluation method and device, which can be used in the field of railway track detection and comprises the following steps: respectively calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time domain sound pressure signal according to the wavelet coefficients, processing in the mode of determining the wavelet energy set according to the synchronous compression transform result, determining the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding, and determining the track surface irregularity improvement index; determining the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding according to the car body transverse acceleration time domain signals collected in the train compartment before rail grinding and the car body transverse acceleration time domain signals collected in the train compartment after rail grinding; determining the rail profile improvement index; and calculating the comprehensive improvement index of the rail after grinding. The application can timely grasp the rail grinding quality and improve the accuracy of the rail grinding quality evaluation.

Description

Technical Field

[0001] This invention relates to the field of railway track inspection, and more particularly to a method and apparatus for evaluating the quality of rail grinding. Background Technology

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

[0003] Rails are the track equipment that directly bears and transmits train loads. Under the repeated action of train loads over a long period, rails will develop defects such as wavy wear and abnormal rail profile wear, which in turn induce abnormal vibrations between the wheel and rail, increase noise radiation at the wheel-rail interface, accelerate fatigue damage to wheel-rail components, and may even endanger traffic safety. Rail grinding is currently the main technical means of repairing rail surface defects. Its principle is to eliminate surface defects of the rail through mechanical cutting, while restoring the rail cross-section to the design profile. Affected by many factors such as dynamic balance deviation of the grinding wheel, fixture positioning error, mismatch between grinding speed and rail hardness, and uneven depth of the hardened layer at the rail head, the ground rail may have certain defects in rail profile and surface roughness, which will adversely affect the wheel-rail contact state and vehicle dynamic performance. Therefore, it is necessary to conduct timely quality assessments of rail grinding.

[0004] Currently, the inspection and evaluation of rail grinding quality mostly utilizes small tools such as rail profile measuring instruments and rail corrugation measuring trolleys. Rail profile measuring instruments are used to check the dimensional deviations of the rail cross-section, often employing a discrete cross-section measurement method, resulting in low inspection efficiency and necessitating sampling inspections. Rail corrugation measuring trolleys are used to measure the unevenness of the rail top surface along the longitudinal direction of the track. Based on their principles, they can be divided into contact trolleys based on the inertial reference method and non-contact trolleys based on the laser chord measurement method. Since significant grinding marks inevitably appear after rail grinding, this not only exacerbates the wear on the measuring head of the contact trolley but also interferes with the laser measurement of the non-contact trolley. Furthermore, the inspection speed of rail corrugation measuring trolleys is only 3–5 km / h, making rapid evaluation of long track sections difficult.

[0005] Compared to the aforementioned small tools, vehicle-mounted inspection methods such as axle box acceleration detection and rail profile laser imaging can achieve rapid assessment of rail grinding quality. However, these vehicle-mounted inspection systems need to be installed on bogies outside the train carriages. Due to limitations in installation costs and traffic safety risk management, they are currently only equipped on a very small number of specialized inspection trains, and inspections are conducted on a fixed cycle of 1-2 times per month, limiting their ability to conduct timely assessments after rail grinding. Furthermore, the current vehicle-mounted systems assess rail profile and surface roughness relatively independently, lacking comprehensive assessment methods and indicators that take both into account. Summary of the Invention

[0006] This invention provides a method for assessing the quality of rail grinding, enabling timely monitoring of rail grinding quality over long sections and improving the accuracy of rail grinding quality assessment. The method includes:

[0007] For the time-domain sound pressure signals collected inside the train carriage before rail grinding and the time-domain sound pressure signals collected inside the train carriage after rail grinding, wavelet coefficients are calculated by continuous wavelet transform. The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then determined based on the synchronous compression transform result to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in the specified frequency band.

[0008] Based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding, the rail surface irregularity improvement index is determined. The rail surface irregularity improvement index is used to quantify the rail surface irregularity improvement effect.

[0009] For the time-domain signals of lateral acceleration of the train body collected inside the train car before rail grinding and the time-domain signals of lateral acceleration of the train body collected inside the train car after rail grinding, wavelet coefficients are calculated by continuous wavelet transform. The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then determined based on the synchronous compression transform result to obtain the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding. The second wavelet energy set is used to represent the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band.

[0010] The rail profile improvement index is determined based on the second wavelet energy set before and after rail grinding; the rail profile improvement index is used to quantify the rail profile improvement effect.

[0011] The comprehensive improvement index of the rail after grinding is calculated based on the rail surface irregularity improvement index and the rail profile improvement index; the comprehensive improvement index is used to quantify the effect of rail grinding.

[0012] This invention also provides a rail grinding quality assessment device to promptly assess the rail grinding quality over long sections, thereby improving the accuracy of rail grinding quality assessment. The device includes:

[0013] The first processing module is used to process the time-domain sound pressure signal collected inside the train car before rail grinding and the time-domain sound pressure signal collected inside the train car after rail grinding by calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time-domain sound pressure signal based on the wavelet coefficients, and determining the wavelet energy set based on the synchronous compression transform result, to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in a specified frequency band.

[0014] The unevenness assessment module is used to determine the rail surface unevenness improvement index based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The rail surface unevenness improvement index is used to quantify the rail surface unevenness improvement effect.

[0015] The second processing module is used to process the time-domain signals of lateral acceleration of the train body collected inside the train car before rail grinding and the time-domain signals of lateral acceleration of the train body collected inside the train car after rail grinding by calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time-domain sound pressure signal based on the wavelet coefficients, and determining the wavelet energy set based on the synchronous compression transform result, to obtain the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding. The second wavelet energy set is used to represent the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band.

[0016] The profile evaluation module is used to determine the rail profile improvement index based on the second wavelet energy set before and after rail grinding; the rail profile improvement index is used to quantify the rail profile improvement effect.

[0017] The comprehensive evaluation module is used to calculate the comprehensive improvement index of the rail after grinding based on the rail surface irregularity improvement index and the rail profile improvement index; the comprehensive improvement index is used to quantify the effect of rail grinding.

[0018] 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 rail grinding quality assessment method.

[0019] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described rail grinding quality assessment method.

[0020] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described rail grinding quality assessment method.

[0021] In this embodiment of the invention, for the time-domain sound pressure signal collected inside the train car before rail grinding and the time-domain sound pressure signal collected inside the train car after rail grinding, wavelet coefficients are calculated using continuous wavelet transform, and the synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then determined based on the synchronous compression transform result to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in a specified frequency band. Based on the first wavelet energy set before and after rail grinding, a rail surface irregularity improvement index is determined. The rail surface irregularity improvement index is used to quantify the rail surface irregularity improvement effect. For the time-domain signal of the lateral acceleration of the train body collected inside the train car before rail grinding, and... After rail grinding, the time-domain signal of lateral acceleration of the train body, collected inside the carriage, is processed by continuous wavelet transform to calculate wavelet coefficients. Based on these wavelet coefficients, the synchronous compression transform result of the time-domain sound pressure signal is determined. The wavelet energy set is then determined based on the synchronous compression transform result, resulting in the second wavelet energy set before and after rail grinding. The second wavelet energy set represents the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band. Based on these second wavelet energy sets, a rail profile improvement index is determined, which quantifies the rail profile improvement effect. Finally, based on the rail surface irregularity improvement index and the rail profile improvement index, a comprehensive improvement index is calculated for the rail after grinding, which quantifies the rail grinding effect. This method determines the difference in sound pressure signals collected inside the train carriage before and after rail grinding, and calculates the rail surface irregularity improvement index. By using noise signals inside the train carriage to capture rail surface irregularity excitations and comparing noise levels before and after grinding, the improvement effect of rail surface irregularity after grinding can be obtained. Based on this, appropriate weights are assigned to vibration and noise signals to calculate the comprehensive improvement effect of rail grinding, enabling timely monitoring of rail grinding quality and improving the accuracy of rail grinding quality assessment. Attached Figure Description

[0022] 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:

[0023] Figure 1 This is a flowchart of the rail grinding quality assessment method provided in this embodiment of the invention;

[0024] Figure 2This is a schematic diagram of the measured sound pressure data inside the train carriage before rail grinding, provided in an embodiment of the present invention.

[0025] Figure 3 This is a schematic diagram of the time-frequency distribution of sound pressure inside a train carriage before rail grinding, provided in an embodiment of the present invention.

[0026] Figure 4 This is a schematic diagram of the sound pressure wavelet energy collection inside the train carriage before rail grinding, provided in an embodiment of the present invention.

[0027] Figure 5 This is a schematic diagram comparing the sound pressure wavelet energy sets inside the train carriage before and after rail grinding, provided in an embodiment of the present invention.

[0028] Figure 6 This is a schematic diagram of the Track Surface Roughness Improvement Index (TSI) provided in an embodiment of the present invention;

[0029] Figure 7 This is a schematic diagram showing the comparison of the lateral acceleration of the vehicle body before and after rail grinding, provided in an embodiment of the present invention.

[0030] Figure 8 This is a schematic diagram comparing the wavelet energy sets of the lateral acceleration of the vehicle body before and after rail grinding, provided in an embodiment of the present invention.

[0031] Figure 9 This is a schematic diagram of the rail profile improvement index (TPI) provided in an embodiment of the present invention;

[0032] Figure 10 This is a schematic diagram of the Total Improvement Index (TGI) for rail grinding provided in an embodiment of the present invention;

[0033] Figure 11 This is a schematic diagram of the rail grinding quality assessment device provided in an embodiment of the present invention;

[0034] Figure 12 This is a structural block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0035] 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.

[0036] 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.

[0037] 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.

[0038] The existing technology has the following problems:

[0039] (1) Rail profile measuring instruments can only check the deviation of rail cross-section dimensions. They generally adopt a discrete measurement method for each section, so their inspection efficiency is low and they are mostly carried out by manual sampling inspection.

[0040] (2) The rail corrugation measuring trolley can only be used to measure the unevenness of the top surface of the rail along the longitudinal direction of the line. In the case of rail grinding, the grinding marks formed by the rail grinding will interfere with the laser measurement of the non-contact trolley and will also significantly aggravate the wear of the measuring ball head of the contact trolley. In addition, the inspection speed of the rail corrugation trolley is only 3 to 5 km / h, which is still difficult to carry out rapid assessment of long track sections.

[0041] (3) Vehicle-mounted inspection methods such as axle box acceleration detection and rail profile laser imaging can achieve rapid assessment of rail grinding quality. However, these vehicle-mounted inspection systems need to be installed on a very small number of professional inspection trains. Currently, they can only be operated on a fixed inspection cycle (such as 1-2 times per month). The cost and convenience of use cannot meet the needs of rapid assessment of rail grinding quality.

[0042] Based on this, this embodiment of the invention provides a method for evaluating the quality of rail grinding. Figure 1 A flowchart for the rail grinding quality assessment method, such as... Figure 1 As shown, it includes:

[0043] Step 101: For the time-domain sound pressure signal collected inside the train car before rail grinding and the time-domain sound pressure signal collected inside the train car after rail grinding, wavelet coefficients are calculated by continuous wavelet transform. The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then processed according to the synchronous compression transform result to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in the specified frequency band.

[0044] Step 102: Determine the rail surface irregularity improvement index based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The rail surface irregularity improvement index is used to quantify the rail surface irregularity improvement effect.

[0045] Step 103: For the time-domain signal of the lateral acceleration of the train body collected inside the train car before rail grinding and the time-domain signal of the lateral acceleration of the train body collected inside the train car after rail grinding, wavelet coefficients are calculated by continuous wavelet transform. The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then processed according to the synchronous compression transform result to obtain the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding. The second wavelet energy set is used to represent the degree of concentration of the lateral acceleration time-domain signal in the specified frequency band.

[0046] Step 104: Determine the rail profile improvement index based on the second wavelet energy set before and after rail grinding; the rail profile improvement index is used to quantify the rail profile improvement effect.

[0047] Step 105: Calculate the comprehensive improvement index of the rail after grinding based on the rail surface irregularity improvement index and the rail profile improvement index; the comprehensive improvement index is used to quantify the effect of rail grinding.

[0048] Current methods for assessing rail grinding quality have several drawbacks in practical applications: ① On-site inspection using small tools is inefficient, making rapid assessment of long sections difficult; ② Rail grinding marks cause severe wear on contact inspection equipment and interfere with laser displacement measurement and laser imaging of non-contact inspection equipment, thus affecting inspection accuracy; vehicle-mounted inspection devices are complex and can only be installed on specialized inspection trains for fixed-cycle operations. This invention uses frequently operating trains as the inspection platform, utilizing easily captured vibration and noise signals within the train carriages to inspect rail grinding effectiveness. This not only achieves highly timely assessment of rail grinding quality over long sections but also scientifically matches rail grinding quality with the dynamic state of rail vehicles, effectively improving the level of rail maintenance and support.

[0049] The rail grinding quality assessment method proposed in this invention determines the difference in sound pressure signals collected inside the train carriage before and after rail grinding, and calculates the rail surface irregularity improvement index. It uses noise signals inside the train carriage to capture rail surface irregularity excitation, and by comparing the noise before and after grinding, the improvement effect of rail surface irregularity after grinding can be obtained. Based on this, corresponding weights are assigned to vibration and noise signals respectively to calculate the comprehensive improvement effect of the rail after grinding, enabling timely monitoring of rail grinding quality and improving the accuracy of rail grinding quality assessment.

[0050] In specific implementation, the rail grinding quality evaluation method proposed in this embodiment of the invention comprises three parts: Part 1: evaluating the improvement effect of rail surface irregularities after rail grinding, that is, extracting the mid-to-high frequency components directly related to rail surface irregularity excitation from the sound pressure signal collected inside the train car, comparing the differences of these components before and after rail grinding, and calculating the rail surface irregularity improvement index; Part 2: evaluating the rail profile improvement effect after grinding, that is, extracting the low frequency components related to rail profile deviation from the acceleration signal collected inside the train car, comparing the differences of these components before and after rail grinding, and calculating the rail profile improvement index; Part 3: establishing a comprehensive rail grinding improvement index that comprehensively considers the degree of rail surface irregularities and rail profile improvement, that is, assigning corresponding weights to the rail surface irregularity improvement index and the rail profile improvement index respectively, and calculating the comprehensive improvement effect of the rail after grinding.

[0051] In one embodiment, the time-domain sound pressure signal collected before rail grinding and the time-domain sound pressure signal collected after rail grinding are obtained in the following manner:

[0052] Determine the sampling frequency of the time-domain sound pressure signal;

[0053] Based on the sampling frequency of the time-domain sound pressure signal, the time-domain sound pressure signal before rail grinding and the time-domain sound pressure signal after rail grinding are collected.

[0054] In one embodiment, determining the synchronous compression transform result of the time-domain sound pressure signal based on wavelet coefficients includes:

[0055] The instantaneous frequency of the sound pressure signal is calculated based on the wavelet coefficients;

[0056] The synchronous compression transformation result of the sound pressure signal is determined based on the instantaneous frequency of the sound pressure signal.

[0057] In one embodiment, the rail surface irregularity improvement index is determined based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding, including:

[0058] The first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding are compared to determine the comparison results of the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

[0059] The rail surface irregularity improvement index is determined by comparing the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

[0060] In one embodiment, the rail surface irregularity improvement index is determined based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding, including:

[0061] The first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding are compared to determine the comparison results of the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

[0062] The rail surface irregularity improvement index is determined by comparing the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

[0063] In one specific embodiment, rail surface irregularities such as wavy wear exacerbate mid-to-high frequency excitation during wheel-rail contact, thereby inducing abnormal wheel-rail vibration and noise. During the propagation of wheel vibration energy to the vehicle body, the mid-to-high frequency components of 50Hz and above are sufficiently attenuated by the primary and secondary suspension systems, making it difficult to effectively extract the wheel-rail impact characteristics induced or exacerbated by rail surface irregularities. In contrast, wheel-rail noise transmitted into the train car can retain the mid-to-high frequency information of wheel-rail contact excitation to a considerable extent; therefore, the sound pressure signal inside the train car is selected as the data source for the improvement effect of rail surface irregularities after rail grinding.

[0064] To obtain the mid-to-high frequency components of the noise inside the train carriage that are related to the shortwave irregularity excitation of the rail surface, the sampling frequency of the sound pressure signal was set to 5 kHz. For the acquired time-domain sound pressure signal s(t), the wavelet coefficients W were calculated using continuous wavelet transform. s (a,b):

[0065]

[0066] In the formula, a is the scaling factor and b is the time step. ψ The wavelet mother function is used here; the Morlet function is employed.

[0067] For satisfying W s For any point (a,b)≠0, the instantaneous frequency of the sound pressure signal is:

[0068]

[0069] Synchronous compression transformation T of sound pressure signal s (ω,b) can be written as:

[0070]

[0071] In the formula, a k and ω l Discrete values ​​of a and ω, respectively, Δa k Δa and Δω are the step sizes, respectively, satisfying Δa k =a k -a k-1 and Δω=ω l -ω l-1 .

[0072] Based on this, wavelet energy sets are used to quantitatively analyze the noise level inside the train carriage. The wavelet energy set represents the degree of concentration of sound pressure signal energy in a specified frequency band f1 to f2, and can be expressed as:

[0073]

[0074] In the formula, N S To specify the number of sampling points within the frequency band f1 to f2, l1 and l2 are the time sequence numbers of f1 and f2, respectively.

[0075] The wavelet energy set T before and after rail grinding is calculated using equation (4). s前 [f1,f2] and T s后 [f1,f2], and further compare the changes in wavelet energy sets before and after rail grinding within a specified section length range (selected as 50m here), to obtain the rail surface irregularity improvement index TSI:

[0076]

[0077] In the formula, K is the number of sampling points along the mileage scale within the specified line segment k1:k2, and k1 and k2 are the start and end point numbers in the mileage sequence, respectively.

[0078] Studies have shown that the frequency components of the sound pressure signal inside the train carriage in the range of 400 to 700 Hz are closely related to short-wave irregularities of the rail surface, such as rail corrugation. Therefore, the frequency range of the rail surface irregularity improvement index in equation (5) is determined to be 400 to 700 Hz.

[0079] To illustrate the calculation method of the track surface irregularity improvement index, let's take the measured sound pressure data inside a train carriage as an example. Figure 2 The figure shows the measured sound pressure data inside the train carriages in the section of track from 993.95 to 994.45 km before rail grinding. The data for this section were subjected to synchronous compressed wavelet transform using equations (1) to (3) to obtain... Figure 3The cloud map showing the distribution of sound pressure inside the train carriage with line mileage and frequency shows that the energy of sound pressure inside the train carriage is mainly concentrated in the 400-700Hz range between the two dashed lines.

[0080] Figure 4 This is a schematic diagram of the wavelet energy set of sound pressure inside the train car before rail grinding provided in this embodiment of the invention. The sound pressure inside the train car is calculated using equation (4) in the range of 400-700H, and the results are as follows. Figure 4 As shown.

[0081] Figure 5 This is a schematic diagram comparing the wavelet energy set of sound pressure inside the train car before and after rail grinding, provided in an embodiment of the present invention. Rail grinding was performed on a section of the line from 994.0 to 994.4 km, and noise data inside the train car was collected after rail grinding. The wavelet energy set of sound pressure inside the train car was calculated using equations (1) to (4). Figure 5 As shown.

[0082] Figure 6 The schematic diagram of the Rail Surface Roughness Improvement Index (TSI) provided in this embodiment of the invention shows that the track within the grinding range (994.0~994.4km) is divided into 8 units with 50m unit sections. The Rail Surface Roughness Improvement Index (TSI) is calculated using equation (5), and the results are as follows. Figure 6 As shown.

[0083] In one specific embodiment, the rail profile is closely related to the wheel-rail matching state. Abnormal wear of the rail profile and deviation in rail grinding may cause deviation in the equivalent taper of the wheel-rail contact. If the equivalent taper is too high or too low, it will cause phenomena such as vehicle shaking and swaying. Therefore, the abnormal vibration of the vehicle body caused by the deviation of the rail profile can be captured by the acceleration sensor arranged in the train car.

[0084] Previous studies have shown that the dominant vibration frequencies of vehicle body swaying and shaking are mostly in the low-frequency range below 20Hz. Therefore, the sampling frequency of the vehicle body lateral acceleration signal is set to 200Hz. For the time-domain signal p(t) of the vehicle body lateral acceleration, the wavelet power set T before and after rail grinding is calculated by equations (1) to (5). p前 [f1,f2] and T p后 [f1,f2]. Since the vehicle will generate fluctuations below 0.5Hz when passing through the curve, which will interfere with the rail profile evaluation, the frequency band range in equation (4) is determined to be 0.5 to 20Hz.

[0085] The rail profile improvement index (TPI) is calculated using the following formula:

[0086]

[0087] To illustrate the calculation method of the rail profile improvement index, let's take measured vehicle acceleration data as an example. Figure 7 The figure shows the measured data of the lateral acceleration of the car body in the section of the track from 993.95 to 994.45 km before rail grinding. Synchronous compressed wavelet transform was performed using equations (1) to (3), and the wavelet energy set of the lateral acceleration of the car body in the range of 0.5 to 20 Hz was calculated using equation (4). The results are shown in [the figure]. Figure 8 A schematic diagram comparing the wavelet energy collection of lateral acceleration of the vehicle body before and after rail grinding.

[0088] Figure 9 The schematic diagram of the rail profile improvement index (TPI) provided in this embodiment of the invention shows that the grinding mileage (994.0~994.4km) is divided into sections of 50m each. The rail profile improvement index (TPI) of each section is further obtained by formula (6), as follows: Figure 9 As shown.

[0089] In one embodiment, the comprehensive improvement index of the rail after grinding is calculated based on the rail surface irregularity improvement index and the rail profile improvement index, including:

[0090] The weights of the rail surface irregularity improvement index and the rail profile improvement index are determined separately.

[0091] The comprehensive improvement index of the rail after grinding is calculated based on the weights of the rail surface irregularity improvement index, the rail profile improvement index, the rail surface irregularity improvement index, and the rail profile improvement index.

[0092] In one embodiment, after calculating the comprehensive improvement index of the rail after grinding based on the rail surface irregularity improvement index, the rail profile improvement index, the weights of the rail surface irregularity improvement index and the rail profile improvement index, the method further includes:

[0093] Determine the assessment level of the comprehensive improvement index; the assessment level is used to quantify the balance between the improvement effect of rail surface unevenness and the improvement effect of rail profile in the rail grinding effect, and different assessment levels correspond to different secondary adjustment methods;

[0094] Based on the assessment level, the comprehensive improvement index is adjusted a second time using the adjustment method corresponding to the assessment level.

[0095] In one specific embodiment, after calculating the comprehensive improvement index of the rail after grinding based on the rail surface irregularity improvement index, the rail profile improvement index, the weights of the rail surface irregularity improvement index and the rail profile improvement index, the process further includes:

[0096] Determine the assessment level of the comprehensive improvement index; the assessment level is used to quantify the balance between the improvement effect of rail surface unevenness and the improvement effect of rail profile in the rail grinding effect, and different assessment levels correspond to different secondary adjustment methods;

[0097] Based on the assessment level, the comprehensive improvement index is adjusted a second time using the adjustment method corresponding to the assessment level.

[0098] By assigning appropriate weights to the rail surface short-wave irregularity improvement index (TSI) and the rail profile improvement index (TPI), the rail grinding comprehensive improvement index (TGI) can be calculated:

[0099] TGI=γTSI+(1-γ)TSI (7)

[0100] In the formula, γ is the influence coefficient of track surface irregularity.

[0101] To account for the differences in the impact of short-wave irregularities on rail surface and rail profile deviations on vehicle performance in different track sections, the γ value is set as a constant related to the radius of the horizontal curve: ① When the curve radius is less than or equal to 3500m (including transition curves), the γ value is set to 0.4; ② When the curve radius is greater than 3500m (including transition curves), the γ value is set to 0.5.

[0102] Since the comprehensive improvement index for rail grinding alone cannot account for the balance between 1) rail surface irregularities and 2) rail profile improvements, situations may arise where rail surface irregularities are significantly improved while rail profiles deteriorate slightly, yet the calculated comprehensive improvement index for rail grinding also shows a significant improvement. Therefore, a balance assessment is needed that combines the individual improvement effects of rail surface irregularities and rail profiles. Table 1 presents the balance assessment method and its classification.

[0103] Table 1. Classification of Rail Grinding Comprehensive Improvement Index (TGI) Evaluation Levels

[0104] rating level Evaluation Rules A TSI ≥ 1.5 and TPI ≥ 1.5 B TSI ≥ 1.0 and TPI ≥ 1.0 (excluding cases with rating grade A) C TSI < 1.0 or TPI < 1.0

[0105] Taking the measured line as an example, the eight units within the grinding mileage range (994.0~994.4km) are all within the curve range with a radius of less than 3500m, and the γ value is set to 0.4. The rail grinding comprehensive improvement index (TGI) of these eight units is calculated according to equation (7), as follows: Figure 10 The diagram shows the Comprehensive Improvement Index (TGI) for rail grinding.

[0106] Based on Table 1, the uniformity of the improvement in rail grinding quality across the eight sections was assessed, and combined with... Figure 10 The TGI values ​​are used to determine the rail grinding quality improvement effect of each section, as shown in Table 2.

[0107] Table 2. Effects of Rail Grinding on Quality Improvement

[0108] Section number TSI TPI Polishing improves the effect ① 4.0 1.1 B2.3 ② 4.0 1.1 B2.3 ③ 2.4 1.1 B1.6 ④ 5.2 1.3 B2.9 ⑤ 7.1 1.6 A3.8 ⑥ 3.4 1.3 B2.1 ⑦ 1.6 1.0 B1.2 ⑧ 2.0 1.0 B1.4

[0109] This invention also provides a rail grinding quality assessment device, as described in the following embodiments. Since the principle by which this device solves the problem is similar to the rail grinding quality assessment method, the implementation of this device can refer to the implementation of the rail grinding quality assessment method; repeated details will not be elaborated further.

[0110] Figure 11 This is a schematic diagram of the rail grinding quality assessment device provided in an embodiment of the present invention, as shown below. Figure 1 As shown, the device includes:

[0111] The first processing module 1101 is used to process the time-domain sound pressure signal collected in the train car before rail grinding and the time-domain sound pressure signal collected in the train car after rail grinding by calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time-domain sound pressure signal based on the wavelet coefficients, and determining the wavelet energy set based on the synchronous compression transform result, so as to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in a specified frequency band.

[0112] The irregularity assessment module 1102 is used to determine the rail surface irregularity improvement index based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The rail surface irregularity improvement index is used to quantify the rail surface irregularity improvement effect.

[0113] The second processing module 1103 is used to process the time-domain signal of the lateral acceleration of the train body collected inside the train car before rail grinding and the time-domain signal of the lateral acceleration of the train body collected inside the train car after rail grinding by calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time-domain sound pressure signal based on the wavelet coefficients, and determining the wavelet energy set based on the synchronous compression transform result, to obtain the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding. The second wavelet energy set is used to represent the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band.

[0114] The profile evaluation module 1104 is used to determine the rail profile improvement index based on the second wavelet energy set before and after rail grinding; the rail profile improvement index is used to quantify the rail profile improvement effect.

[0115] The comprehensive evaluation module 1105 is used to calculate the comprehensive improvement index of the rail after grinding based on the rail surface irregularity improvement index and the rail profile improvement index; the comprehensive improvement index is used to quantify the effect of rail grinding.

[0116] In one embodiment, the time-domain sound pressure signal collected before rail grinding and the time-domain sound pressure signal collected after rail grinding are obtained in the following manner:

[0117] Determine the sampling frequency of the time-domain sound pressure signal;

[0118] Based on the sampling frequency of the time-domain sound pressure signal, the time-domain sound pressure signal before rail grinding and the time-domain sound pressure signal after rail grinding are collected.

[0119] In one embodiment, the first processing module 1101 is specifically used for:

[0120] The instantaneous frequency of the sound pressure signal is calculated based on the wavelet coefficients;

[0121] The synchronous compression transformation result of the sound pressure signal is determined based on the instantaneous frequency of the sound pressure signal.

[0122] In one embodiment, the first processing module 1101 is specifically used for:

[0123] The first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding are compared to determine the comparison results of the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

[0124] The rail surface irregularity improvement index is determined by comparing the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

[0125] In one embodiment, the roughness assessment module 1102 is specifically used for:

[0126] The comparison results are divided into multiple segments according to a preset length, and the improvement results of the unevenness in each segment are determined.

[0127] Based on the improvement results of irregularities in each section, the improvement results of track surface irregularities are determined.

[0128] In one embodiment, the comprehensive evaluation module 1105 is specifically used for:

[0129] The weights of the rail surface irregularity improvement index and the rail profile improvement index are determined separately.

[0130] The comprehensive improvement index of the rail after grinding is calculated based on the weights of the rail surface irregularity improvement index, the rail profile improvement index, the rail surface irregularity improvement index, and the rail profile improvement index.

[0131] In one embodiment, the comprehensive evaluation module 1105 is further configured to:

[0132] Determine the assessment level of the comprehensive improvement index; the assessment level is used to quantify the balance between the improvement effect of rail surface unevenness and the improvement effect of rail profile in the rail grinding effect, and different assessment levels correspond to different secondary adjustment methods;

[0133] Based on the assessment level, the comprehensive improvement index is adjusted a second time using the adjustment method corresponding to the assessment level.

[0134] Based on the aforementioned inventive concept, such as Figure 12 As shown, the present invention also proposes a computer device 1200, including a memory 1210, a processor 1220, and a computer program 1230 stored in the memory 1210 and executable on the processor 1220. When the processor 1220 executes the computer program 1230, it implements the aforementioned rail grinding quality assessment method.

[0135] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described rail grinding quality assessment method.

[0136] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described rail grinding quality assessment method.

[0137] In summary, in this embodiment of the invention, for the time-domain sound pressure signal collected inside the train car before rail grinding and the time-domain sound pressure signal collected inside the train car after rail grinding, wavelet coefficients are calculated using continuous wavelet transform, and the synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then determined based on the synchronous compression transform result, resulting in the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in a specified frequency band. Based on the first wavelet energy set before and after rail grinding, a rail surface irregularity improvement index is determined, which is used to quantify the rail surface irregularity improvement effect. For the time-domain sound pressure signal of the car body lateral acceleration collected inside the train car before rail grinding... The time-domain signals of lateral acceleration of the train body, collected inside the train carriage after rail grinding, are analyzed. Wavelet coefficients are calculated using continuous wavelet transform. Based on these wavelet coefficients, the synchronous compression transform result of the time-domain sound pressure signal is determined. The wavelet energy set is then processed according to the synchronous compression transform result, resulting in the second wavelet energy set before and after rail grinding. The second wavelet energy set represents the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band. Based on these second wavelet energy sets, a rail profile improvement index is determined. This index quantifies the rail profile improvement effect. Finally, based on the rail surface irregularity improvement index and the rail profile improvement index, a comprehensive improvement index is calculated for the rail after grinding. This comprehensive improvement index quantifies the rail grinding effect. This method determines the difference in sound pressure signals collected inside the train carriage before and after rail grinding, and calculates the rail surface irregularity improvement index. By using noise signals inside the train carriage to capture rail surface irregularity excitations and comparing noise levels before and after grinding, the improvement effect of rail surface irregularity after grinding can be obtained. Based on this, appropriate weights are assigned to vibration and noise signals to calculate the comprehensive improvement effect of rail grinding, enabling timely monitoring of rail grinding quality and improving the accuracy of rail grinding quality assessment.

[0138] 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.

[0139] 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, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0140] 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, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0141] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0142] 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 evaluating the quality of rail grinding, characterized in that, include: For the time-domain sound pressure signals collected inside the train carriage before rail grinding and the time-domain sound pressure signals collected inside the train carriage after rail grinding, wavelet coefficients are calculated by continuous wavelet transform. The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then determined based on the synchronous compression transform result to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in the specified frequency band. Based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding, the rail surface irregularity improvement index is determined. The rail surface irregularity improvement index is used to quantify the rail surface irregularity improvement effect. For the time-domain signals of lateral acceleration of the train body collected inside the train car before rail grinding and the time-domain signals of lateral acceleration of the train body collected inside the train car after rail grinding, wavelet coefficients are calculated by continuous wavelet transform. The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients. The wavelet energy set is then determined based on the synchronous compression transform result to obtain the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding. The second wavelet energy set is used to represent the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band. The rail profile improvement index is determined based on the second wavelet energy set before and after rail grinding; the rail profile improvement index is used to quantify the rail profile improvement effect. The comprehensive improvement index of the rail after grinding is calculated based on the rail surface irregularity improvement index and the rail profile improvement index; the comprehensive improvement index is used to quantify the effect of rail grinding.

2. The method as described in claim 1, characterized in that, The time-domain sound pressure signal collected before rail grinding and the time-domain sound pressure signal collected after rail grinding were obtained in the following manner: Determine the sampling frequency of the time-domain sound pressure signal; Based on the sampling frequency of the time-domain sound pressure signal, the time-domain sound pressure signal before and after rail grinding is collected.

3. The method as described in claim 1, characterized in that, The synchronous compression transform result of the time-domain sound pressure signal is determined based on the wavelet coefficients, including: The instantaneous frequency of the sound pressure signal is calculated based on the wavelet coefficients; The synchronous compression transformation result of the sound pressure signal is determined based on the instantaneous frequency of the sound pressure signal.

4. The method as described in claim 1, characterized in that, Based on the first wavelet energy set before and after rail grinding, the rail surface irregularity improvement index is determined, including: The first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding are compared to determine the comparison results of the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section. The rail surface irregularity improvement index is determined by comparing the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding in a specified section.

5. The method as described in claim 4, characterized in that, Based on the comparison of the first wavelet energy set before and after rail grinding in a designated section, the rail surface irregularity improvement index is determined, including: The comparison results are divided into multiple segments according to a preset length, and the improvement results of the unevenness in each segment are determined. Based on the results of the irregularity improvement in each section, the results of the track surface irregularity improvement are determined.

6. The method as described in claim 1, characterized in that, Based on the rail surface irregularity improvement index and the rail profile improvement index, the comprehensive improvement index of the rail after grinding is calculated, including: The weights of the rail surface irregularity improvement index and the rail profile improvement index are determined separately. The comprehensive improvement index of the rail after grinding is calculated based on the weights of the rail surface irregularity improvement index, the rail profile improvement index, the rail surface irregularity improvement index, and the rail profile improvement index.

7. The method as described in claim 6, characterized in that, Based on the weights of the rail surface irregularity improvement index, rail profile improvement index, and rail surface irregularity improvement index, and the weight of the rail profile improvement index, the comprehensive improvement index of the rail after grinding is calculated, which also includes: Determine the assessment level of the comprehensive improvement index; the assessment level is used to quantify the balance between the improvement effect of rail surface unevenness and the improvement effect of rail profile in the rail grinding effect, and different assessment levels correspond to different secondary adjustment methods; Based on the assessment level, the comprehensive improvement index is adjusted a second time using the adjustment method corresponding to the assessment level.

8. A rail grinding quality assessment device, characterized in that, include: The first processing module is used to process the time-domain sound pressure signal collected inside the train car before rail grinding and the time-domain sound pressure signal collected inside the train car after rail grinding by calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time-domain sound pressure signal based on the wavelet coefficients, and determining the wavelet energy set based on the synchronous compression transform result, to obtain the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The first wavelet energy set is used to represent the degree of concentration of the sound pressure signal in a specified frequency band. The unevenness assessment module is used to determine the rail surface unevenness improvement index based on the first wavelet energy set before rail grinding and the first wavelet energy set after rail grinding. The rail surface unevenness improvement index is used to quantify the rail surface unevenness improvement effect. The second processing module is used to process the time-domain signals of lateral acceleration of the train body collected inside the train car before rail grinding and the time-domain signals of lateral acceleration of the train body collected inside the train car after rail grinding by calculating wavelet coefficients through continuous wavelet transform, determining the synchronous compression transform result of the time-domain sound pressure signal based on the wavelet coefficients, and determining the wavelet energy set based on the synchronous compression transform result, to obtain the second wavelet energy set before rail grinding and the second wavelet energy set after rail grinding. The second wavelet energy set is used to represent the degree of concentration of the lateral acceleration time-domain signal in a specified frequency band. The profile evaluation module is used to determine the rail profile improvement index based on the second wavelet energy set before and after rail grinding; the rail profile improvement index is used to quantify the rail profile improvement effect. The comprehensive evaluation module is used to calculate the comprehensive improvement index of the rail after grinding based on the rail surface irregularity improvement index and the rail profile improvement index; the comprehensive improvement index is used to quantify the effect of rail grinding.

9. 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 7.

10. 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 7.

11. 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 7.

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