Method and device for calculating the trough depth of rail corrugation

Abstract

The present invention discloses a method and device for calculating the trough depth of rail corrugation, the method comprising: performing a second frequency domain integration on the acceleration vibration signal of the axle box to obtain a wheel-rail displacement signal; performing signal decomposition on the wheel-rail displacement signal based on the ACMD signal decomposition algorithm; using the second-order mode of the wheel-rail displacement signal as the dynamic response corrugation component of the rail, and calculating the trough depth of the dynamic response corrugation component of the rail; obtaining the on-site verification data of the rail; performing signal decomposition on the on-site verification data of the rail; using the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail; determining the target value of the trough depth of rail corrugation according to the similarity between the trough depth of the dynamic response corrugation component and the trough depth of the on-site verification corrugation component. The present invention is used to improve the accuracy and calculation efficiency of the calculation of the trough depth of rail corrugation, and save calculation costs.

Description

Technical Field

[0001] The invention relates to the technical field of railway track detection, and in particular to a method and a device for calculating the trough depth of rail corrugation. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No admission is made that the description herein is prior art by inclusion in this section.

[0003] Track short wave irregularity is a typical track disease, usually caused by factors such as bulges or depressions in rail welding joints, wave wear, abrasions or peeling of rail heads. Rail corrugation is one of the common short wave irregularity diseases, usually with a wavelength in the range of 40mm to 300mm. Through the excitation of the wheel-rail force, it can produce a more obvious dynamic response at the axle box of the train. In the research and application of analyzing and evaluating rail corrugation diseases using vibration signals collected by axle box acceleration, there are relatively mature collection and analysis systems and evaluation systems. In order to further study the characteristics of rail corrugation, such as corrugation wavelength, trough depth, energy of corrugation components, etc., as well as to study the correlation and evolution law between corrugation diseases on lines of different speed levels, and to improve the detection methods and evaluation system of track short wave diseases, it is necessary to explore the analysis and evaluation methods of rail corrugation in depth.

[0004] The existing more mature track short-wave irregularity signal analysis system can only perform corrugation analysis on the acceleration dynamic response signal collected by the axle box acceleration sensor of the high-speed comprehensive inspection train.

[0005] In order to analyze and compare the acceleration signal and the data verified on site by the corrugation measuring instrument at the same time and calculate the trough depth of rail corrugation, it is necessary to extract and separate the periodic components in the signal.

[0006] Normally, the response signal caused by rail corrugation will have a periodic component with strong energy, a peak on the spectrum, and may also have harmonic components and interference components with a certain amount of energy. For such multi-component signals, it is necessary to use signal separation to extract the main corrugation components.

[0007] Commonly used methods for separating multi-component rail corrugation are: ① filtering with digital filters, and ② Eigenmode Decomposition (EMD) method. However, ① filter cannot adaptively select the frequency band and bandwidth of the filter. Different problem data need to be processed by selecting the filter frequency band separately, which is not only complicated but also resource-consuming. ② EMD method is based on empirical mode. For a single corrugation component with high energy concentration, it can filter out trend terms and interference terms to extract the information contained in the corrugation peak frequency. However, for multi-component corrugation, there are multiple peaks and strong interference signals in the spectrum. The EMD method cannot accurately extract the corrugation signal, resulting in inaccurate calculation of the trough depth.

[0008] In summary, the existing technology cannot accurately extract rail corrugation from multi-component signals, so how to extract multi-component rail corrugation has become a problem that needs to be solved urgently. Summary of the invention

[0009] The embodiment of the present invention provides a method for calculating the trough depth of rail corrugation, which is used to improve the accuracy and efficiency of calculating the trough depth of rail corrugation and save calculation costs. The method includes:

[0010] Performing secondary frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by collecting data on the target rail by a rail detection vehicle;

[0011] Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain the second-order mode of the wheel-rail displacement signal;

[0012] The second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated;

[0013] Acquire on-site verification data of the rails; the on-site verification data of the rails include short-wave irregularity data of the rails; convert the short-wave irregularity data of the rails into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal;

[0014] Based on the ACMD signal decomposition algorithm, the conversion data is subjected to signal decomposition to obtain the first-order mode of the conversion data;

[0015] Taking the first-order mode of the converted data as the on-site verified corrugation component of the rail, and calculating the trough depth of the on-site verified corrugation component of the rail;

[0016] The target value of the trough depth of the rail corrugation is determined according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail.

[0017] The embodiment of the present invention further provides a device for calculating the trough depth of rail corrugation, which is used to improve the accuracy and efficiency of calculating the trough depth of rail corrugation and save calculation costs. The device includes:

[0018] The axle box acceleration vibration signal processing module is used to perform secondary frequency domain integration on the axle box acceleration vibration signal to obtain the wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by the rail detection vehicle performing data collection on the target rail;

[0019] The wheel-rail displacement signal decomposition module is used to decompose the wheel-rail displacement signal based on the ACMD signal decomposition algorithm to obtain the second-order mode of the wheel-rail displacement signal;

[0020] A module for calculating the trough depth of the dynamic response corrugation component of the rail, used for taking the second-order mode of the wheel-rail displacement signal as the dynamic response corrugation component of the rail, and calculating the trough depth of the dynamic response corrugation component of the rail;

[0021] The on-site verification data processing module is used to obtain on-site verification data of the rail; the on-site verification data of the rail includes short-wave irregularity data of the rail; the short-wave irregularity data of the rail is converted into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal;

[0022] An on-site review data signal decomposition module, used to perform signal decomposition on the conversion data based on an ACMD signal decomposition algorithm to obtain a first-order mode of the conversion data;

[0023] A module for calculating the trough depth of the on-site verification corrugation component of the rail, used for taking the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail;

[0024] The target value determination module of the trough depth is used to determine the target value of the trough depth of the rail corrugation according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail.

[0025] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for calculating the trough depth of rail corrugation when executing the computer program.

[0026] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for calculating the trough depth of rail corrugation is implemented.

[0027] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method for calculating the trough depth of rail corrugation is implemented.

[0028] In the embodiment of the present invention, the axle box acceleration vibration signal is subjected to a second frequency domain integration to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by a rail detection vehicle performing data acquisition on a target rail; based on an ACMD signal decomposition algorithm, the wheel-rail displacement signal is subjected to signal decomposition to obtain a second-order mode of the wheel-rail displacement signal; the second-order mode of the wheel-rail displacement signal is used as a dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated; the on-site verification data of the rail is obtained; the on-site verification data of the rail is obtained. The invention comprises short-wave irregularity data of the rail; converting the short-wave irregularity data of the rail into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal; performing signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data; using the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail; according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail, The target value of the trough depth of rail corrugation is determined, so that for multi-component rail corrugation, the ACMD signal decomposition algorithm can be used to extract the corrugation components in the axle box acceleration dynamic response signal and the on-site verification data, and calculate the trough depth of the corrugation. Compared with the technical solution of separating multi-component rail corrugation by digital filter in the prior art, it is no longer necessary to use a filter, and the rail corrugation can be calculated directly according to the axle box acceleration vibration signal and the on-site verification data, without selecting filter frequency bands for processing respectively, which solves the problem that the prior art needs to select filter frequency bands for processing when separating rail corrugation by filter, which leads to complex operation and easy consumption of resources, improves the calculation efficiency of the trough depth of rail corrugation, and saves the calculation cost of the trough depth of rail corrugation; compared with the technical solution of separating multi-component rail corrugation by intrinsic mode decomposition method in the prior art, it solves the problem that the intrinsic mode decomposition method in the prior art cannot accurately extract corrugation signals from multi-component corrugation, resulting in inaccurate calculation of the trough depth, and improves the accuracy of the calculation of the trough depth of rail corrugation. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0030] Figure 1 It is a specific schematic diagram of a method for calculating the trough depth of rail corrugation in an embodiment of the present invention;

[0031] Figure 2a and Figure 2b They are respectively a time domain example diagram and a frequency spectrum example diagram of an acceleration signal a(k) of an axle box in a corrugated grinding section in an embodiment of the present invention;

[0032] Figure 3a and Figure 3b The time domain example diagram and spectrum example diagram of a corrugated section displacement signal s(k) in an embodiment of the present invention are respectively;

[0033] Figure 4a and Figure 4b A time domain example diagram and a spectrum example diagram of each modal component obtained by performing signal decomposition of a wheel-rail displacement signal by an ACMD algorithm in an embodiment of the present invention;

[0034] Figure 5a and Figure 5b The time domain example diagram and the spectrum example diagram of the signal c(x) in the field review data of a corrugation section in an embodiment of the present invention are respectively;

[0035] Figure 6a and Figure 6b A time domain example diagram and a spectrum example diagram of a resampled and filtered on-site verification signal c(k) according to an embodiment of the present invention;

[0036] Figure 7a and Figure 7b A time domain example diagram and a spectrum example diagram of each modal component obtained by performing signal decomposition on the conversion data by an ACMD algorithm in an embodiment of the present invention;

[0037] Figure 8 This is a flowchart of a method for calculating the trough depth of rail corrugation in an embodiment of the present invention;

[0038] Fig. 9 This is a structural example diagram of a device for calculating the trough depth of rail corrugation in an embodiment of the present invention;

[0039] Fig.10 Schematic diagram of a computer device for calculating the trough depth of rail corrugation in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0041] The term "and / or" herein only describes an association relationship, indicating that three relationships may exist. For example, A and / or B may represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C may represent including any one or more elements selected from the set consisting of A, B, and C.

[0042] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps is not limited and can be appropriately adjusted as needed.

[0043] Track short wave irregularity is a typical track disease, usually caused by bulges or depressions in rail weld joints, wave wear, abrasions or peeling of rail heads, etc. Rail corrugation is one of the common short wave irregularity diseases, usually with a wavelength of 40mm to 300mm. It can produce a more obvious dynamic response at the axle box of the train through the excitation of the wheel-rail force.

[0044] Currently, the vibration signal measured by the acceleration sensor installed on the axle box can be used to analyze the short-wave irregularity disease, and the Steel Corrugation Index (SCI) can be used to evaluate the periodic rail corrugation component in the dynamic response vibration signal.

[0045] In the research and application of analyzing and evaluating rail corrugation by using vibration signals collected by axle box acceleration, there are relatively mature collection and analysis systems and evaluation systems. In order to further study the characteristics of rail corrugation, such as corrugation wavelength, trough depth, energy of corrugation components, etc., and to study the correlation and evolution law between corrugation diseases of lines with different speed levels, and to improve the detection means and evaluation system of short-wave rail diseases, it is necessary to explore the analysis and evaluation methods of rail corrugation in depth.

[0046] The existing more mature track short-wave irregularity signal analysis system determines whether there is corrugation by calculating the corrugation index and energy factor, and performs Fourier Transform (FT) on the problematic data with corrugation to calculate the peak frequency of the periodic component and the corresponding corrugation wavelength.

[0047] This method only performs corrugation analysis on the acceleration dynamic response signal collected by the axle box acceleration sensor of the high-speed comprehensive inspection train.

[0048] In order to analyze and compare the acceleration signal and the data verified on site by the corrugation measuring instrument at the same time and calculate the trough depth of rail corrugation, it is necessary to extract and separate the periodic components in the signal.

[0049] Normally, the response signal caused by rail corrugation will have a periodic component with strong energy, a peak on the spectrum, and may also have harmonic components and interference components with a certain amount of energy. For such multi-component signals, it is necessary to use signal separation to extract the main corrugation components.

[0050] Commonly used methods for separating multi-component rail corrugation include digital filter processing and intrinsic mode decomposition (EMD) method.

[0051] The filter cannot adaptively select the frequency band and bandwidth of the filter. Different problem data need to be processed separately. The EMD method is based on empirical mode. For a single wave grinding component with high energy concentration, it can filter out trend terms and interference terms to extract the information contained in the peak frequency of the wave grinding. However, for multi-component wave grinding, there are multiple peaks and strong interference signals in the spectrum. The EMD method cannot accurately extract the wave grinding signal, resulting in inaccurate calculation of the trough depth.

[0052] In summary, in-depth research on the characteristics of rail corrugation requires extraction of the corrugation components in the axle box acceleration dynamic response signal and the field verification data, and calculation of the trough depth of the corrugation. Existing technologies are unable to accurately extract rail corrugation from multi-component signals.

[0053] The embodiment of the present invention aims at the multi-component rail corrugation problem and proposes a method for extracting rail corrugation components from axle box acceleration signals and field verification data based on the ACMD algorithm and calculating the trough depth. The accuracy of the embodiment of the present invention is verified by analyzing the measured data. The method can be applied to the rail corrugation disease analysis of a large amount of measured data.

[0054] As described above, a method for calculating the trough depth of rail corrugation provided by an embodiment of the present invention can be used to improve the accuracy and efficiency of calculating the trough depth of rail corrugation and save calculation costs. Figure 8 , the method may include:

[0055] Step 801: performing a second frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by collecting data on the target rail by a rail detection vehicle;

[0056] Step 802: Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain the second-order mode of the wheel-rail displacement signal;

[0057] Step 803: taking the second-order mode of the wheel-rail displacement signal as the dynamic response corrugation component of the rail, and calculating the trough depth of the dynamic response corrugation component of the rail;

[0058] Step 804: obtaining on-site verification data of the rails; the on-site verification data of the rails include short-wave irregularity data of the rails; converting the short-wave irregularity data of the rails into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal;

[0059] Step 805: Based on the ACMD signal decomposition algorithm, perform signal decomposition on the above conversion data to obtain the first-order mode of the conversion data;

[0060] Step 806: using the first-order mode of the above-mentioned converted data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail;

[0061] Step 807: Determine a target value of the trough depth of the rail corrugation according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail.

[0062] In the embodiment of the present invention, the axle box acceleration vibration signal is subjected to a second frequency domain integration to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by a rail detection vehicle performing data acquisition on a target rail; based on an ACMD signal decomposition algorithm, the wheel-rail displacement signal is subjected to signal decomposition to obtain a second-order mode of the wheel-rail displacement signal; the second-order mode of the wheel-rail displacement signal is used as a dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated; the on-site verification data of the rail is obtained; the on-site verification data of the rail is obtained. The invention comprises short-wave irregularity data of the rail; converting the short-wave irregularity data of the rail into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal; performing signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data; using the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail; according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail, The target value of the trough depth of rail corrugation is determined, so that for multi-component rail corrugation, the ACMD signal decomposition algorithm can be used to extract the corrugation components in the axle box acceleration dynamic response signal and the on-site verification data, and calculate the trough depth of the corrugation. Compared with the technical solution of separating multi-component rail corrugation by digital filter in the prior art, it is no longer necessary to use a filter, and the rail corrugation can be calculated directly according to the axle box acceleration vibration signal and the on-site verification data, without selecting filter frequency bands for processing respectively, which solves the problem that the prior art needs to select filter frequency bands for processing when separating rail corrugation by filter, which leads to complex operation and easy consumption of resources, improves the calculation efficiency of the trough depth of rail corrugation, and saves the calculation cost of the trough depth of rail corrugation; compared with the technical solution of separating multi-component rail corrugation by intrinsic mode decomposition method in the prior art, it solves the problem that the intrinsic mode decomposition method in the prior art cannot accurately extract corrugation signals from multi-component corrugation, resulting in inaccurate calculation of the trough depth, and improves the accuracy of the calculation of the trough depth of rail corrugation.

[0063] In specific implementation, firstly, the axle box acceleration vibration signal is integrated twice in the frequency domain to obtain the wheel-rail displacement signal.

[0064] In the above embodiment, the axle box acceleration vibration signal in the discrete time domain may be subjected to secondary integration to obtain the corresponding displacement signal, ie, the wheel-rail displacement signal.

[0065] In the embodiment, the axle box acceleration vibration signal is subjected to a second frequency domain integration to obtain a wheel-rail displacement signal, including:

[0066] Perform a frequency domain integration on the axle box acceleration vibration signal to obtain the axle box speed signal;

[0067] Perform secondary frequency domain integration on the axle box speed signal to obtain the axle box displacement signal;

[0068] The axle box displacement signal is used as the wheel-rail displacement signal.

[0069] In one embodiment, the axle box acceleration vibration signal can be integrated in the second frequency domain according to the following formula to obtain the wheel-rail displacement signal:

[0070]

[0071] Among them, s(k) = ∫∫a(k)dk, s(k) represents the wheel-rail displacement signal; a(k) represents the axle box acceleration vibration signal, a(k) is a discrete time domain signal with a sampling frequency of Fs, and the integral frequency of a(k) is the full frequency domain of Fourier transform represents Fourier transform; represents the inverse transform of Fourier transform; ω is the circular frequency; j represents the imaginary unit; 1 / (jω) 2 Represents the integrating factor.

[0072] In the above embodiment, the vibration signal a(k) collected by the acceleration sensor installed on the axle box of the high-speed comprehensive inspection train is integrated once to obtain the velocity signal v(k)=∫a(k)dk, and integrated twice to obtain the displacement signal s(k)=∫∫a(k)dk.

[0073] For the measured time-domain discrete acceleration signal, due to its complex components, time-domain integration will lead to inaccurate time-domain discrete displacement signal due to cumulative errors. Therefore, the embodiment of the present invention adopts a frequency-domain integration method to complete the conversion between acceleration signal and displacement signal.

[0074] Furthermore, the displacement signal obtained after the step of obtaining the wheel-rail displacement signal usually has multiple components, including a displacement trend term, a possible periodic component (rail corrugation component), a non-periodic component or other interference components.

[0075] Rail corrugation is a type of short-wave track unevenness disease, with a common wavelength of 40 mm to 300 mm. When the train speed is 200 km / h to 300 km / h, the corresponding frequency is about 185 Hz to 2083 Hz, and most of the trend items are low-frequency components. Using only a filter to filter the signal after frequency integration will cause certain errors. Therefore, an embodiment of the present invention proposes a technical solution for decomposing the wheel-rail displacement signal based on an ACMD signal decomposition algorithm to obtain the second-order mode of the wheel-rail displacement signal, and separating the multi-component corrugation through the signal decomposition method.

[0076] In specific implementation, after performing secondary frequency domain integration on the axle box acceleration vibration signal to obtain the wheel-rail displacement signal, the wheel-rail displacement signal is decomposed based on the ACMD signal decomposition algorithm to obtain the second-order mode of the wheel-rail displacement signal.

[0077] In the embodiment, based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain the second-order mode of the wheel-rail displacement signal, including:

[0078] Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain all modes of the wheel-rail displacement signal;

[0079] The second-order mode of the wheel-rail displacement signal is extracted from all the modes of the wheel-rail displacement signal.

[0080] In one embodiment, the wheel-rail displacement signal can be decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the wheel-rail displacement signal:

[0081] s(k)=s1(k)+s2(k)+γ s (k)

[0082] Among them, s(k) represents the wheel-rail displacement signal; s1(k) is the first-order mode of the wheel-rail displacement signal, representing the trend term of the displacement; s2(k) is the second-order mode of the wheel-rail displacement signal, representing the main frequency component after filtering out the trend term; γ s (k) is the remaining modes of the wheel-rail displacement signal.

[0083] In the above embodiment, based on the ACMD signal decomposition algorithm, this adaptive modal decomposition method (ACMD) can adaptively determine the components existing in the signal, find the most suitable decomposition bandwidth at each peak frequency, and separate multi-component signals in different frequency bands as multiple signal modes.

[0084] For the dynamic response signal and on-site verification signal generated by rail corrugation, there are usually one or more peak frequencies, which represent the periodic components, and there may be other frequency components with a certain energy, which represent the interference terms. It is more appropriate to use the ACMD algorithm to decompose and extract the rail corrugation components.

[0085] In specific implementation, after the wheel-rail displacement signal is decomposed based on the ACMD signal decomposition algorithm to obtain the second-order mode of the wheel-rail displacement signal, the second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated.

[0086] In one embodiment, the second-order mode of the wheel-rail displacement signal can be used as the dynamic response corrugation component of the rail to calculate the trough depth of the dynamic response corrugation component of the rail according to the following formula:

[0087]

[0088] Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; The segment average wave depth represents the trough depth of the corrugation component of the dynamic response of the rail; s2(k) is the second-order mode of the wheel-rail displacement signal.

[0089] In the above embodiment, for rail corrugation, the trough depth can be defined as the peak value of the periodic component of corrugation. For sectional rail corrugation, the trough depth can be defined as the average corrugation depth of the section. Indicates that since the peak value of the sinusoidal signal is the root mean square (RMS) value times, and the corrugation component s2(k) can be approximately regarded as a periodic component of a single frequency, so It can be calculated according to the above formula.

[0090] At present, after the high-speed comprehensive inspection train identifies the track disease, it is usually necessary to conduct on-site verification on the line using equipment such as track inspection trolleys or corrugation measuring instruments to confirm the rail corrugation. On-site verification usually uses the data acquisition method of equidistant spatial sampling, and the obtained data c(x) usually contains the low-frequency long-wave irregularity components of the line.

[0091] In order to solve the above problems, in a specific implementation of the embodiment of the present invention, after taking the second-order mode of the above-mentioned wheel-rail displacement signal as the dynamic response corrugation component of the rail and calculating the trough depth of the dynamic response corrugation component of the rail, the on-site verification data of the rail is obtained; the above-mentioned on-site verification data of the rail includes short-wave unevenness data of the rail; the short-wave unevenness data of the rail is converted into conversion data consistent with the time sampling frequency of the above-mentioned axle box acceleration vibration signal.

[0092] In one embodiment, it further includes:

[0093] Performing bandpass filtering on the short-wave irregularity data of the rail to obtain low-frequency short-wave irregularity data within a preset wavelength range;

[0094] The short-wave irregularity data of the rail is converted into conversion data consistent with the time sampling frequency of the above-mentioned axle box acceleration vibration signal, including:

[0095] The low-frequency short-wave roughness data within a preset wavelength range is converted into conversion data consistent with the time sampling frequency of the above-mentioned axle box acceleration vibration signal.

[0096] In the embodiment, the low-frequency short-wave roughness data is short-wave roughness data with a wavelength of 40 mm to 300 mm, which can be called short-wave roughness data. Among them, the long-wave roughness signal has been filtered out by the filter, so the data analyzed in this application is short-wave roughness data.

[0097] In the above embodiment, the data collection method of equidistant spatial sampling is usually adopted for on-site verification, and the obtained data c(x) usually contains the problem of low-frequency long-wave unevenness components of the line. The embodiment of the present invention uses downsampling, resampling and other methods to convert the data c(k) with the same time sampling frequency as the acceleration signal according to the driving speed of the comprehensive inspection vehicle in the section, and then performs bandpass filtering to retain the frequency components with corresponding wavelengths of 40mm to 300mm.

[0098] In specific implementation, after converting the short-wave unevenness data of the rail into conversion data consistent with the time sampling frequency of the above-mentioned axle box acceleration vibration signal, the above-mentioned conversion data is decomposed based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data.

[0099] In the embodiment, like the acceleration vibration signal of the coaxial box, other components still exist within the filter passband after the field verification data is filtered, but when there is a strong corrugation component, the corrugation component has an obvious peak in the spectrum. Since the field verification adopts equidistant spatial sampling, the corrugation component can also be regarded as a periodic component with modulated amplitude and constant frequency. Therefore, the embodiment of the present invention adopts the ACMD signal decomposition algorithm to process the above conversion data.

[0100] In one embodiment, based on the ACMD signal decomposition algorithm, the above conversion data is subjected to signal decomposition to obtain the first-order mode of the conversion data, including:

[0101] Based on the ACMD signal decomposition algorithm, the above conversion data is decomposed to obtain all modes of the conversion data;

[0102] The first mode of the transformed data is extracted from all the modes of the transformed data.

[0103] In one embodiment, the above conversion data may be decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the conversion data:

[0104] c(k)=c1(k)+γ c (k)

[0105] Where c(k) represents the converted data; c1(k) is the first-order mode of the converted data, representing the main frequency component of the signal; γ c (k) is the remaining modes of the transformed data, representing the secondary frequency components and interference components.

[0106] In specific implementation, after performing signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data, the first-order mode of the conversion data is used as the on-site verification corrugation component of the rail, and the trough depth of the on-site verification corrugation component of the rail is calculated.

[0107] In one embodiment, the first-order mode of the above-mentioned conversion data can be used as the on-site verification corrugation component of the rail to calculate the trough depth of the on-site verification corrugation component of the rail according to the following formula:

[0108]

[0109] Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; It represents the segment average wave depth of the trough depth of the field verified wave wear component of the rail; c1(k) is the first-order mode of the converted data.

[0110] In specific implementation, after taking the first-order mode of the above-mentioned conversion data as the on-site verification corrugation component of the rail and calculating the trough depth of the on-site verification corrugation component of the rail, the target value of the trough depth of the rail corrugation is determined according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail.

[0111] In the embodiment, when the embodiment of the present invention is applied to the analysis of the axle box acceleration collected by the high-speed comprehensive detection train and the signal collected by the on-site verification, the multi-component corrugation in the signal can be effectively extracted and the trough depth can be calculated.

[0112] Due to the different dynamic responses of different comprehensive inspection vehicles, the inspection equipment and inspection process used in the on-site review are also different. The trough depths obtained by the two calculation methods are: the trough depth of the dynamic response of the rail and the corrugation component On-site verification of the corrugation components of the rails and the trough depth There are certain differences.

[0113] However, because the physical quantities are all trough depths, there is a certain degree of correlation. and The correlation and difference of rail corrugation are studied in depth, the dynamic responses of different trains are normalized, and the transmission errors of on-site verification equipment are corrected to achieve the purpose of accurately measuring and evaluating the rail corrugation condition.

[0114] In one embodiment, according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the field verification corrugation component of the rail, a target value of the trough depth of the rail corrugation is determined, including:

[0115] When the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail is greater than a preset value, a notification message is issued indicating that the inspection of the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail has passed;

[0116] The average value of the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail is used as the target value of the trough depth of the rail corrugation.

[0117] A specific embodiment is given below to illustrate the specific application of the method of the present invention. The main purpose of this specific embodiment is to specifically include:

[0118] (1) Extract the rail corrugation component from the measured axle box acceleration signal and calculate the trough depth;

[0119] (2) Extract the rail corrugation component from the field verified data and calculate the trough depth.

[0120] 1. In order to achieve the above purpose, Figure 1 As shown, the technical implementation idea of ​​this specific embodiment is:

[0121] For the discrete time domain axle box acceleration vibration signal, the corresponding displacement signal can be obtained by performing quadratic integration. Based on the ACMD signal decomposition algorithm, several modes of the displacement signal are adaptively extracted. For data with corrugation, its second-order mode can be regarded as the main component of corrugation, and the depth of the trough can be calculated. For the on-site verification data sampled in discrete space, it is processed by downsampling, filtering, etc. to make it consistent with the time sampling rate of the acceleration signal, and then based on the ACMD signal decomposition algorithm, several modes of the signal are adaptively extracted. For data with corrugation, its first-order mode can be regarded as the main component of corrugation, and its trough depth can be directly calculated. The acceleration signal is collected by the high-speed comprehensive inspection train, and the on-site verification data is measured by equipment such as the track inspection car or corrugation measuring instrument. By analyzing and comparing these two types of data, their correlation can be studied to improve the accuracy of track disease detection.

[0122] The ACMD signal decomposition algorithm proposed in this specific embodiment can adaptively decompose several order signal modes according to the distribution of the main peak value of the spectrum for discrete time domain signals, and each order mode contains a frequency modulation and amplitude modulation signal with relatively concentrated energy. The ACMD signal decomposition algorithm can be applied to the decomposition of high-speed rail vehicle dynamic response signals and on-site verification signals, and the rail corrugation components contained in the signals can be extracted, and the trough depth of corrugation can be calculated.

[0123] 2. In this specific embodiment, the following steps may be included:

[0124] ① Extract rail corrugation components from the axle box acceleration signal;

[0125] The vibration signal a(k) collected by the acceleration sensor installed on the axle box of the high-speed comprehensive inspection train is integrated once to obtain the velocity signal v(k) = ∫a(k)dk, and the displacement signal s(k) = ∫∫a(k)dk is integrated twice. For the measured time-domain discrete acceleration signal, due to the complex components, the time-domain integration will cause the time-domain discrete displacement signal to be inaccurate due to the accumulated error. Therefore, the frequency domain integration method is used to complete the conversion between the acceleration signal and the displacement signal. According to the properties of Fourier transform, the frequency domain integration of the acceleration signal can be expressed as formula (1).

[0126]

[0127] in, represents the Fourier transform, represents the inverse transform of Fourier transform, ω is the circular frequency, From formula (1), we know that by integrating in the frequency domain, the acceleration signal is transformed by Fourier transform and then multiplied by the integration factor 1 / (jω) 2 , and then perform inverse Fourier transform to get the displacement signal. For a discrete time domain signal with a sampling frequency of Fs, its integral frequency is the full frequency domain of Fourier transform, that is,

[0128] The displacement signal obtained after frequency integration usually has multiple components, including displacement trend items, possible periodic components (rail corrugation components), non-periodic components or other interference components. Rail corrugation is a type of short-wave track unevenness disease, with a common wavelength of 40mm to 300mm. When the train speed is 200km / h to 300km / h, the corresponding frequency is about 185Hz to 2083Hz, and the trend items are mostly low-frequency components. Using only a filter to filter the signal after frequency integration will bring certain errors. Therefore, the multi-component corrugation should be separated by signal decomposition methods. The ACMD signal decomposition algorithm proposed at this stage can decompose the frequency-modulated and amplitude-modulated signals with multiple components and rapid changes with time. The various modes obtained after decomposition represent the signal components with a certain bandwidth, a single frequency component, and frequency and amplitude changing with time on the spectrum diagram. For the dynamic response signal generated by rail corrugation, the train speed in the corrugation section can usually be regarded as constant. Therefore, the corrugation component can be regarded as a periodic component with modulated amplitude and constant frequency, which is suitable for processing using the ACMD signal decomposition algorithm.

[0129] The modes of displacement signal decomposed by ACMD algorithm can be expressed as follows, see formula (2):

[0130] s(k)=s1(k)+s2(k)+γ s (k) (2)

[0131] Among them, s1(k) is the first-order mode, representing the trend term of displacement, s2(k) is the second-order mode, representing the main frequency component after filtering out the trend term, and γ s (k) is the remaining order mode, representing the remaining minor frequency components and interference components. When the signal contains a strong corrugation component, the corrugation component shows a specific frequency peak on the spectrum. Therefore, the second-order mode s2(k) obtained after decomposition by the ACMD algorithm is the corrugation component.

[0132] For rail corrugation, the trough depth is defined as the peak value of the periodic component of the corrugation. For sectional rail corrugation, the trough depth can be calculated by the average corrugation depth of the section. Indicates that since the peak value of the sinusoidal signal is the root mean square (RMS) value times, and the corrugation component s2(k) can be approximately regarded as a periodic component of a single frequency, so It can be calculated according to formula (3).

[0133]

[0134] Where N is the number of sampling points in this section.

[0135] ② Extract rail corrugation components from on-site verification data:

[0136] After the high-speed comprehensive inspection train identifies the track disease, it is usually necessary to conduct on-site verification on the line through equipment such as track inspection trolleys or corrugation measuring instruments to confirm the rail corrugation. On-site verification usually adopts the data acquisition method of equidistant spatial sampling. The obtained data c(x) usually contains the low-frequency long-wave unevenness components of the line. According to the speed of the comprehensive inspection vehicle in this section, it is necessary to use downsampling, resampling and other methods to convert it into data c(k) with the same time sampling frequency as the acceleration signal, and then perform bandpass filtering to retain the frequency components with corresponding wavelengths of 40mm to 300mm. Like the acceleration signal, there are still other components within the filter passband range after filtering the on-site verification data, but when there is a strong corrugation component, the corrugation component has an obvious peak in the spectrum. Since the on-site verification adopts equidistant spatial sampling, the corrugation component can also be regarded as a periodic component with modulated amplitude and constant frequency, which is suitable for processing using the ACMD signal decomposition algorithm.

[0137] The various modes obtained by decomposing the on-site verification data using the ACMD algorithm can be expressed as follows, see formula (4):

[0138] c(k)=c1(k)+γ c (k) (4)

[0139] Where c1(k) is the first-order mode, representing the main frequency component of the signal, γ c (k) is the remaining order mode, representing the secondary frequency components and interference components. Since the trend term has been filtered out by the bandpass filter, the ACMD algorithm plays a role in extracting the main frequency components, filtering out the interference components in the passband, and improving the signal-to-noise ratio. The first-order mode c1(k) obtained after decomposition by the ACMD algorithm is the corrugation component.

[0140] Similar to ①, the trough depth of the corrugated mill obtained by on-site verification is It can be calculated according to formula (5).

[0141]

[0142] ③. The trough depth of the corrugation component of the dynamic response of the rail On-site verification of the corrugation components of the rails and the trough depth Analyze the correlation.

[0143] 3. As follows, a specific example is given, such as a group of data with multi-component rail corrugation diseases, to demonstrate that this specific embodiment can effectively extract the corrugation components in the signal.

[0144] The selected data is a section of a high-speed railway line with rail corrugation disease. The sampling frequency of the comprehensive inspection vehicle is Fs = 5000Hz, and the driving speed is 169km / h. The dynamic response analysis system is used to obtain the wavelength λ in the acceleration signal. a =74.0mm periodic corrugation component, corresponding to frequency f a =634.3Hz. The corrugation measuring instrument is used for verification on site, and the spatial sampling frequency is Fx=1000m -1 , the wave grinding wavelength is λ c =74.1mm, which is consistent with the test result. The following will apply this specific embodiment for in-depth analysis.

[0145] ①. Analysis of corrugation components in the axle box acceleration signal:

[0146] Make the time domain diagram and spectrum diagram of the acceleration signal in this section as follows Figure 2a and Figure 2b As shown in the figure, it can be seen that there are three spectrum peaks in this corrugation, and the main frequency peak frequency f a1 =634.3Hz, corresponding to wavelength λ a =74.0mm. The rest are harmonic components of this frequency, which are f a2 =1269.0Hz and f a3 =1902.9Hz. In addition, there are some interference components in the low frequency band.

[0147] Perform a second frequency domain integration on the acceleration signal to obtain the displacement signal, and make a time domain diagram and spectrum diagram of the displacement signal as shown in the following figure: Figure 3a and Figure 3b As shown in Figure 2, it can be seen that there is a strong trend term in the time domain displacement signal, and several local peaks on the spectrum diagram are also consistent with Figure 2b Corresponding in.

[0148] The displacement signal is decomposed by ACMD. The algorithm adaptively decomposes 7 signal modes and makes the time domain diagram and spectrum diagram of each mode as shown in the following figure. Figure 4a and Figure 4b As shown. It can be seen that mode 1 (i.e., the first-order mode, which will not be described in detail below) is the trend term obtained by frequency domain integration, which is mainly concentrated in the low-frequency part and is not needed in the analysis of short-wave roughness. Mode 2, mode 4, and mode 5 are the main frequencies f a1 =634.3Hz, f a2 =1269.0Hz and f a3 =1902.9Hz wave grinding component, this method clearly separates the three wave grinding components with different main frequencies. Mode 3 is a periodic component near the frequency band of f=200Hz. Since the energy concentration is not high, it can be determined as a strong interference component. Modes 6 and 7 have low energy and low concentration, and are determined to be interference components. Therefore, mode 2 or the superposition of mode 2 with mode 4 and mode 5 can be taken as the signal of the wave grinding component in this section. Taking mode 2 as the wave grinding component, the trough depth can be calculated Taking the superposition of mode 2, mode 4, and mode 5 as the corrugation component, we can calculate

[0149] ② Analysis of corrugation components in on-site review data

[0150] Make a spatial domain diagram and a spectrum diagram (the frequency is converted into wavelength according to the speed of the comprehensive inspection vehicle, the same below) of the on-site verification signal of the section (i.e., the on-site verification data of the rail includes the short-wave irregularity data of the rail, which can be called the on-site verification signal) as follows: Figure 5a and Figure 5b As shown in the figure, and the time domain diagram and spectrum diagram after resampling and filtering are shown in the figure Figure 6a and Figure 6b As shown in the figure, it can be seen that there is only one main peak in the typical corrugation wavelength range of 40mm to 300mm, and the peak frequency f c1 =633.8Hz, corresponding to wavelength λ a =74.0mm. In addition, there is also a certain degree of interference.

[0151] The ACMD decomposition is performed on the resampled and filtered field verification signal. The algorithm adaptively decomposes the five signal modes and makes the time domain diagram and spectrum diagram of each mode as shown in the figure. Figure 7a and Figure 7b As shown. It can be seen that mode 1 extracts Figure 6b The information near the peak frequency can be regarded as the corrugation component. The other modes contain information of different wavelength components. Since the signal energy concentration is low, they can be determined as interference components. Therefore, mode 1 is taken as the corrugation component signal and calculated.

[0152] From the above analysis, it can be concluded that the method proposed in this specific embodiment for decomposing the acceleration signal and the field verification signal based on the ACMD algorithm can extract the rail corrugation component in the signal and calculate the trough depth. The example in this section shows that the trough depth calculated by the acceleration signal and the field verification signal using this method is consistent, and this method can be applied to the rail corrugation disease analysis of a large amount of measured data.

[0153] Of course, it is understandable that the above detailed process may have other variations, and the relevant variations should all fall within the protection scope of the present invention.

[0154] In the embodiment of the present invention, the axle box acceleration vibration signal is subjected to a second frequency domain integration to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by a rail detection vehicle performing data acquisition on a target rail; based on an ACMD signal decomposition algorithm, the wheel-rail displacement signal is subjected to signal decomposition to obtain a second-order mode of the wheel-rail displacement signal; the second-order mode of the wheel-rail displacement signal is used as a dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated; the on-site verification data of the rail is obtained; the on-site verification data of the rail is obtained. The invention comprises short-wave irregularity data of the rail; converting the short-wave irregularity data of the rail into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal; performing signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data; using the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail; according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail, The target value of the trough depth of rail corrugation is determined, so that for multi-component rail corrugation, the ACMD signal decomposition algorithm can be used to extract the corrugation components in the axle box acceleration dynamic response signal and the on-site verification data, and calculate the trough depth of the corrugation. Compared with the technical solution of separating multi-component rail corrugation by digital filter in the prior art, it is no longer necessary to use a filter, and the rail corrugation can be calculated directly according to the axle box acceleration vibration signal and the on-site verification data, without selecting filter frequency bands for processing respectively, which solves the problem that the prior art needs to select filter frequency bands for processing when separating rail corrugation by filter, which leads to complex operation and easy consumption of resources, improves the calculation efficiency of the trough depth of rail corrugation, and saves the calculation cost of the trough depth of rail corrugation; compared with the technical solution of separating multi-component rail corrugation by intrinsic mode decomposition method in the prior art, it solves the problem that the intrinsic mode decomposition method in the prior art cannot accurately extract corrugation signals from multi-component corrugation, resulting in inaccurate calculation of the trough depth, and improves the accuracy of the calculation of the trough depth of rail corrugation.

[0155] The present invention also provides a device for calculating the trough depth of rail corrugation, as described in the following embodiments. Since the principle of the device to solve the problem is similar to the method for calculating the trough depth of rail corrugation, the implementation of the device can refer to the implementation of the method for calculating the trough depth of rail corrugation, and the repeated parts will not be repeated.

[0156] The embodiment of the present invention provides a device for calculating the trough depth of rail corrugation, which is used to improve the accuracy and efficiency of calculating the trough depth of rail corrugation and save calculation costs. Fig. 9 As shown, the device comprises:

[0157] The axle box acceleration vibration signal processing module 901 is used to perform secondary frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by collecting data on the target rail by the rail detection vehicle;

[0158] The wheel-rail displacement signal decomposition module 902 is used to decompose the wheel-rail displacement signal based on the ACMD signal decomposition algorithm to obtain the second-order mode of the wheel-rail displacement signal;

[0159] The module 903 for calculating the trough depth of the dynamic response corrugation component of the rail is used to use the second-order mode of the wheel-rail displacement signal as the dynamic response corrugation component of the rail to calculate the trough depth of the dynamic response corrugation component of the rail;

[0160] The on-site verification data processing module 904 is used to obtain on-site verification data of the rails; the on-site verification data of the rails include short-wave irregularity data of the rails; the short-wave irregularity data of the rails is converted into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal;

[0161] On-site verification data signal decomposition module 905, used to perform signal decomposition on the above conversion data based on ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data;

[0162] A module 906 for calculating the trough depth of the on-site verification corrugation component of the rail is used to calculate the trough depth of the on-site verification corrugation component of the rail by taking the first-order mode of the above-mentioned conversion data as the on-site verification corrugation component of the rail;

[0163] The target value determination module 907 for the trough depth is used to determine the target value of the trough depth of the rail corrugation according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail.

[0164] In one embodiment, the axle box acceleration vibration signal processing module is specifically used to:

[0165] Perform a frequency domain integration on the axle box acceleration vibration signal to obtain the axle box speed signal;

[0166] Perform secondary frequency domain integration on the axle box speed signal to obtain the axle box displacement signal;

[0167] The axle box displacement signal is used as the wheel-rail displacement signal.

[0168] In one embodiment, the axle box acceleration vibration signal processing module is specifically used to:

[0169] The axle box acceleration vibration signal is integrated in the second frequency domain according to the following formula to obtain the wheel-rail displacement signal:

[0170]

[0171] Among them, s(k) = ∫∫a(k)dk, s(k) represents the wheel-rail displacement signal; a(k) represents the axle box acceleration vibration signal, a(k) is a discrete time domain signal with a sampling frequency of Fs, and the integral frequency of a(k) is the full frequency domain of Fourier transform represents Fourier transform; represents the inverse transform of Fourier transform; ω is the circular frequency; j represents the imaginary unit; 1 / (jω) 2 Represents the integrating factor.

[0172] In one embodiment, the wheel-rail displacement signal decomposition module is specifically used to:

[0173] Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain all modes of the wheel-rail displacement signal;

[0174] The second-order mode of the wheel-rail displacement signal is extracted from all the modes of the wheel-rail displacement signal.

[0175] In one embodiment, the wheel-rail displacement signal decomposition module is specifically used to:

[0176] The wheel-rail displacement signal is decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the wheel-rail displacement signal:

[0177] s(k)=s1(k)+s2(k)+γ s (k)

[0178] Among them, s(k) represents the wheel-rail displacement signal; s1(k) is the first-order mode of the wheel-rail displacement signal, representing the trend term of the displacement; s2(k) is the second-order mode of the wheel-rail displacement signal, representing the main frequency component after filtering out the trend term; γ s (k) is the remaining modes of the wheel-rail displacement signal.

[0179] In one embodiment, the module for calculating the trough depth of the dynamic response corrugation component of the rail is specifically used for:

[0180] The second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail according to the following formula to calculate the trough depth of the dynamic response corrugation component of the rail:

[0181]

[0182] Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; The segment average wave depth represents the trough depth of the corrugation component of the dynamic response of the rail; s2(k) is the second-order mode of the wheel-rail displacement signal.

[0183] In one embodiment, it further includes:

[0184] Bandpass filter processing module, used for:

[0185] Performing bandpass filtering on the short-wave irregularity data of the rail to obtain low-frequency short-wave irregularity data within a preset wavelength range;

[0186] On-site review data processing module, specifically used for:

[0187] The low-frequency short-wave roughness data within a preset wavelength range is converted into conversion data consistent with the time sampling frequency of the above-mentioned axle box acceleration vibration signal.

[0188] In one embodiment, the on-site review data signal decomposition module is specifically used to:

[0189] Based on the ACMD signal decomposition algorithm, the above conversion data is decomposed to obtain all modes of the conversion data;

[0190] The first mode of the transformed data is extracted from all the modes of the transformed data.

[0191] In one embodiment, the on-site review data signal decomposition module is specifically used to:

[0192] The above conversion data is decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the conversion data:

[0193] c(k)=c1(k)+γ c (k)

[0194] Where c(k) represents the converted data; c1(k) is the first-order mode of the converted data, representing the main frequency component of the signal; γ c (k) is the remaining modes of the transformed data, representing the secondary frequency components and interference components.

[0195] In one embodiment, the module for calculating the trough depth of the on-site verification corrugation component of the rail is specifically used for:

[0196] The first-order mode of the above-mentioned converted data is used as the on-site verification corrugation component of the rail according to the following formula, and the trough depth of the on-site verification corrugation component of the rail is calculated:

[0197]

[0198] Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; It represents the segment average wave depth of the trough depth of the field verified wave wear component of the rail; c1(k) is the first-order mode of the converted data.

[0199] In one embodiment, the module for determining the target value of the trough depth is specifically used to:

[0200] When the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail is greater than a preset value, a notification message is issued indicating that the inspection of the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail has passed;

[0201] The average value of the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail is used as the target value of the trough depth of the rail corrugation.

[0202] An embodiment of the present invention provides an embodiment of a computer device for implementing all or part of the contents of the above-mentioned method for calculating the trough depth of rail corrugation. The above-mentioned computer device specifically includes the following contents:

[0203] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between related devices; the computer device can be a desktop computer, a tablet computer and a mobile terminal, etc., but the present embodiment is not limited thereto. In the present embodiment, the computer device can be implemented with reference to the embodiment of the method for calculating the trough depth of rail corrugation and the embodiment of the device for calculating the trough depth of rail corrugation, the contents of which are incorporated herein and the repeated parts are not repeated.

[0204] Fig.10 FIG. 1 is a schematic block diagram of the system structure of the computer device 1000 according to an embodiment of the present application. Fig.10 As shown, the computer device 1000 may include a central processor 1001 and a memory 1002; the memory 1002 is coupled to the central processor 1001. It is worth noting that Fig.10 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0205] In one embodiment, the function of calculating the trough depth of rail corrugation may be integrated into the central processor 1001 .

[0206] The central processing unit 1001 may be configured to perform the following control:

[0207] Performing secondary frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by collecting data on the target rail by a rail detection vehicle;

[0208] Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain the second-order mode of the wheel-rail displacement signal;

[0209] The second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated;

[0210] Acquire on-site verification data of the rails; the on-site verification data of the rails include short-wave irregularity data of the rails; convert the short-wave irregularity data of the rails into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal;

[0211] Based on the ACMD signal decomposition algorithm, the conversion data is subjected to signal decomposition to obtain the first-order mode of the conversion data;

[0212] Taking the first-order mode of the converted data as the on-site verified corrugation component of the rail, and calculating the trough depth of the on-site verified corrugation component of the rail;

[0213] The target value of the trough depth of the rail corrugation is determined according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail.

[0214] In another embodiment, the device for calculating the trough depth of rail corrugation can be configured separately from the central processor 1001. For example, the device for calculating the trough depth of rail corrugation can be configured as a chip connected to the central processor 1001, and the function of calculating the trough depth of rail corrugation can be realized through the control of the central processor.

[0215] like Fig.10 As shown, the computer device 1000 may also include: a communication module 1003, an input unit 1004, an audio processor 1005, a display 1006, and a power supply 1007. It is worth noting that the computer device 1000 does not necessarily have to include Fig.10 In addition, the computer device 1000 may also include Fig.10 For components not shown, reference may be made to the prior art.

[0216] like Fig.10 As shown, the central processor 1001 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The central processor 1001 receives inputs and controls the operations of various components of the computer device 1000 .

[0217] The memory 1002 may be, for example, a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices, or one or more thereof. The above-mentioned information related to the failure may be stored, and a program for executing the related information may also be stored. The central processing unit 1001 may execute the program stored in the memory 1002 to implement information storage or processing, etc.

[0218] The input unit 1004 provides input to the CPU 1001. The input unit 1004 is, for example, a key or a touch input device. The power supply 1007 is used to provide power to the computer device 1000. The display 1006 is used to display display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0219] The memory 1002 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 1002 may also be some other type of device. The memory 1002 includes a buffer memory 1021 (sometimes referred to as a buffer). The memory 1002 may include an application / function storage unit 1022, which is used to store application programs and function programs or processes for executing the operation of the computer device 1000 through the central processor 1001.

[0220] The memory 1002 may also include a data storage unit 1023 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the computer device. The driver storage unit 1024 of the memory 1002 may include various drivers for the computer device for communication functions and / or for executing other functions of the computer device (such as messaging applications, address book applications, etc.).

[0221] The communication module 1003 is a transmitter / receiver that sends and receives signals via the antenna 1008. The communication module (transmitter / receiver) 1003 is coupled to the central processor 1001 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0222] Based on different communication technologies, multiple communication modules 1003 may be provided in the same computer device, such as a cellular network module, a Bluetooth module and / or a wireless local area network module, etc. The communication module (transmitter / receiver) 1003 is also coupled to a speaker 1009 and a microphone 1010 via an audio processor 1005 to provide an audio output via the speaker 1009 and receive an audio input from the microphone 1010, thereby realizing a common telecommunication function. The audio processor 1005 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 1005 is also coupled to the central processor 1001, so that recording can be performed on the local machine through the microphone 1010, and the sound stored on the local machine can be played through the speaker 1009.

[0223] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for calculating the trough depth of rail corrugation is implemented.

[0224] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method for calculating the trough depth of rail corrugation is implemented.

[0225] In the embodiment of the present invention, the axle box acceleration vibration signal is subjected to a second frequency domain integration to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by a rail detection vehicle performing data acquisition on a target rail; based on an ACMD signal decomposition algorithm, the wheel-rail displacement signal is subjected to signal decomposition to obtain a second-order mode of the wheel-rail displacement signal; the second-order mode of the wheel-rail displacement signal is used as a dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated; the on-site verification data of the rail is obtained; the on-site verification data of the rail is obtained. The invention comprises short-wave irregularity data of the rail; converting the short-wave irregularity data of the rail into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal; performing signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data; using the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail; according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail, The target value of the trough depth of rail corrugation is determined, so that for multi-component rail corrugation, the ACMD signal decomposition algorithm can be used to extract the corrugation components in the axle box acceleration dynamic response signal and the on-site verification data, and calculate the trough depth of the corrugation. Compared with the technical solution of separating multi-component rail corrugation by digital filter in the prior art, it is no longer necessary to use a filter, and the rail corrugation can be calculated directly according to the axle box acceleration vibration signal and the on-site verification data, without selecting filter frequency bands for processing respectively, which solves the problem that the prior art needs to select filter frequency bands for processing when separating rail corrugation by filter, which leads to complex operation and easy consumption of resources, improves the calculation efficiency of the trough depth of rail corrugation, and saves the calculation cost of the trough depth of rail corrugation; compared with the technical solution of separating multi-component rail corrugation by intrinsic mode decomposition method in the prior art, it solves the problem that the intrinsic mode decomposition method in the prior art cannot accurately extract corrugation signals from multi-component corrugation, resulting in inaccurate calculation of the trough depth, and improves the accuracy of the calculation of the trough depth of rail corrugation.

[0226] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0227] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0228] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0229] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0230] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for calculating the trough depth of rail corrugation, characterized in that: include: Performing secondary frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by collecting data on the target rail by a rail detection vehicle; Performing a second frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal, including: performing a first frequency domain integration on the axle box acceleration vibration signal to obtain an axle box velocity signal; performing a second frequency domain integration on the axle box velocity signal to obtain an axle box displacement signal; and using the axle box displacement signal as the wheel-rail displacement signal; Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain the second-order mode of the wheel-rail displacement signal; Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain the second-order mode of the wheel-rail displacement signal, including: Based on the ACMD signal decomposition algorithm, the wheel-rail displacement signal is decomposed to obtain all modes of the wheel-rail displacement signal; The second-order mode of the wheel-rail displacement signal is extracted from all modes of the wheel-rail displacement signal; The second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail, and the trough depth of the dynamic response corrugation component of the rail is calculated; Acquire on-site verification data of the rails; the on-site verification data of the rails include short-wave irregularity data of the rails; convert the short-wave irregularity data of the rails into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal; Based on the ACMD signal decomposition algorithm, the conversion data is subjected to signal decomposition to obtain the first-order mode of the conversion data; Based on the ACMD signal decomposition algorithm, the conversion data is subjected to signal decomposition to obtain the first-order mode of the conversion data, including: Based on the ACMD signal decomposition algorithm, the conversion data is subjected to signal decomposition to obtain all modes of the conversion data; Extracting the first-order mode of the conversion data from all modes of the conversion data; Taking the first-order mode of the converted data as the on-site verified corrugation component of the rail, and calculating the trough depth of the on-site verified corrugation component of the rail; Determine a target value of the trough depth of the rail corrugation according to the similarity between the trough depth of the rail's dynamic response corrugation component and the trough depth of the rail's on-site verification corrugation component; determine the target value of the trough depth of the rail corrugation according to the similarity between the trough depth of the rail's dynamic response corrugation component and the trough depth of the rail's on-site verification corrugation component, including: when the similarity between the trough depth of the rail's dynamic response corrugation component and the trough depth of the rail's on-site verification corrugation component is greater than a preset value, issue a notification message indicating that the inspection of the trough depth of the rail's dynamic response corrugation component and the trough depth of the rail's on-site verification corrugation component has passed; and use the average value of the trough depth of the rail's dynamic response corrugation component and the trough depth of the rail's on-site verification corrugation component as the target value of the trough depth of the rail corrugation.

2. The method according to claim 1, characterized in that The axle box acceleration vibration signal is integrated in the second frequency domain according to the following formula to obtain the wheel-rail displacement signal: Among them, s(k) = ∫∫a(k)dk, s(k) represents the wheel-rail displacement signal; a(k) represents the axle box acceleration vibration signal, a(k) is a discrete time domain signal with a sampling frequency of Fs, and the integral frequency of a(k) is the full frequency domain of Fourier transform represents Fourier transform; represents the inverse transform of Fourier transform; ω is the circular frequency; j represents the imaginary unit; 1 / (jω) 2 Represents the integrating factor.

3. The method according to claim 1, characterized in that The wheel-rail displacement signal is decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the wheel-rail displacement signal: s(k)=s1(k)+s2(k)+γ s (k) Among them, s(k) represents the wheel-rail displacement signal; s1(k) is the first-order mode of the wheel-rail displacement signal, representing the trend term of the displacement; s2(k) is the second-order mode of the wheel-rail displacement signal, representing the main frequency component after filtering out the trend term; γ s (k) is the remaining modes of the wheel-rail displacement signal.

4. The method according to claim 1, characterized in that The second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail to calculate the trough depth of the dynamic response corrugation component of the rail according to the following formula: Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; The segment average wave depth represents the trough depth of the corrugation component of the dynamic response of the rail; s2(k) is the second-order mode of the wheel-rail displacement signal.

5. The method according to claim 1, characterized in that Also includes: Performing bandpass filtering on the short-wave irregularity data of the rail to obtain low-frequency short-wave irregularity data within a preset wavelength range; Converting the short-wave irregularity data of the rail into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal includes: The low-frequency short-wave roughness data in a preset wavelength range is converted into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal.

6. The method according to claim 1, characterized in that The conversion data is decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the conversion data: c(k)=c1(k)+γ c (k) Where c(k) represents the converted data; cx(k) is the first-order mode of the converted data, representing the main frequency component of the signal; γ c (k) is the remaining modes of the transformed data, representing the secondary frequency components and interference components.

7. The method according to claim 1, characterized in that The first-order mode of the conversion data is used as the on-site verification corrugation component of the rail to calculate the trough depth of the on-site verification corrugation component of the rail according to the following formula: Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; It represents the segment average wave depth of the trough depth of the field verified wave wear component of the rail; c1(k) is the first-order mode of the converted data.

8. A device for calculating the trough depth of rail corrugation, characterized in that: include: The axle box acceleration vibration signal processing module is used to perform a second frequency domain integration on the axle box acceleration vibration signal to obtain a wheel-rail displacement signal; the axle box acceleration vibration signal is obtained by the rail detection vehicle performing data acquisition on the target rail; the axle box acceleration vibration signal processing module is specifically used to: perform a first frequency domain integration on the axle box acceleration vibration signal to obtain an axle box velocity signal; perform a second frequency domain integration on the axle box velocity signal to obtain an axle box displacement signal; and use the axle box displacement signal as the wheel-rail displacement signal; The wheel-rail displacement signal decomposition module is used to decompose the wheel-rail displacement signal based on the ACMD signal decomposition algorithm to obtain the second-order mode of the wheel-rail displacement signal; the wheel-rail displacement signal decomposition module is specifically used to: decompose the wheel-rail displacement signal based on the ACMD signal decomposition algorithm to obtain all modes of the wheel-rail displacement signal; extract the second-order mode of the wheel-rail displacement signal from all modes of the wheel-rail displacement signal; A module for calculating the trough depth of the dynamic response corrugation component of the rail, used for taking the second-order mode of the wheel-rail displacement signal as the dynamic response corrugation component of the rail, and calculating the trough depth of the dynamic response corrugation component of the rail; The on-site verification data processing module is used to obtain on-site verification data of the rail; the on-site verification data of the rail includes short-wave irregularity data of the rail; the short-wave irregularity data of the rail is converted into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal; The on-site verification data signal decomposition module is used to perform signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain the first-order mode of the conversion data; the on-site verification data signal decomposition module is specifically used to: perform signal decomposition on the conversion data based on the ACMD signal decomposition algorithm to obtain all modes of the conversion data; extract the first-order mode of the conversion data from all modes of the conversion data; A module for calculating the trough depth of the on-site verification corrugation component of the rail, used for taking the first-order mode of the conversion data as the on-site verification corrugation component of the rail, and calculating the trough depth of the on-site verification corrugation component of the rail; The module for determining the target value of the trough depth is used to determine the target value of the trough depth of the rail corrugation according to the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail; the module for determining the target value of the trough depth of the rail corrugation is specifically used to: when the similarity between the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail is greater than a preset value, issue a notification message indicating that the inspection of the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail has passed; and take the average value of the trough depth of the dynamic response corrugation component of the rail and the trough depth of the on-site verification corrugation component of the rail as the target value of the trough depth of the rail corrugation.

9. The device according to claim 8, characterized in that Axle box acceleration vibration signal processing module, specifically used for: The axle box acceleration vibration signal is integrated in the second frequency domain according to the following formula to obtain the wheel-rail displacement signal: Among them, s(k) = ∫∫a(k)dk, s(k) represents the wheel-rail displacement signal; a(k) represents the axle box acceleration vibration signal, a(k) is a discrete time domain signal with a sampling frequency of Fs, and the integral frequency of a(k) is the full frequency domain of Fourier transform represents Fourier transform; represents the inverse transform of Fourier transform; ω is the circular frequency; j represents the imaginary unit; 1 / (jω) 2 Represents the integrating factor.

10. The device according to claim 8, characterized in that The wheel-rail displacement signal decomposition module is specifically used for: The wheel-rail displacement signal is decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the wheel-rail displacement signal: s(k)=s1(k)+s2(k)+γ s (k) Among them, s(k) represents the wheel-rail displacement signal; s1(k) is the first-order mode of the wheel-rail displacement signal, representing the trend term of the displacement; s2(k) is the second-order mode of the wheel-rail displacement signal, representing the main frequency component after filtering out the trend term; γ s (k) is the remaining modes of the wheel-rail displacement signal.

11. The device according to claim 8, characterized in that The module for calculating the trough depth of the dynamic response corrugation component of the rail is specifically used for: The second-order mode of the wheel-rail displacement signal is used as the dynamic response corrugation component of the rail to calculate the trough depth of the dynamic response corrugation component of the rail according to the following formula: Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; The segment average wave depth represents the trough depth of the corrugation component of the dynamic response of the rail; s2(k) is the second-order mode of the wheel-rail displacement signal.

12. The device according to claim 8, characterized in that Also includes: Bandpass filter processing module, used for: Performing bandpass filtering on the short-wave irregularity data of the rail to obtain low-frequency short-wave irregularity data within a preset wavelength range; On-site review data processing module, specifically used for: The low-frequency short-wave roughness data in a preset wavelength range is converted into conversion data consistent with the time sampling frequency of the axle box acceleration vibration signal.

13. The device according to claim 8, characterized in that On-site review data signal decomposition module, specifically used for: The conversion data is decomposed based on the ACMD signal decomposition algorithm according to the following formula to obtain all modes of the conversion data: c(k)=c1(k)+γ c (k) Where c(k) represents the converted data; c1(k) is the first-order mode of the converted data, representing the main frequency component of the signal; γ c (k) is the remaining modes of the transformed data, representing the secondary frequency components and interference components.

14. The device according to claim 8, characterized in that The module for calculating the trough depth of the corrugation component of the rail on-site verification is specifically used for: The first-order mode of the conversion data is used as the on-site verification corrugation component of the rail to calculate the trough depth of the on-site verification corrugation component of the rail according to the following formula: Where i represents the i-th sampling point, and N is the number of sampling points in the corresponding section of the rail; It represents the segment average wave depth of the trough depth of the field verified wave wear component of the rail; c1(k) is the first-order mode of the converted data.

15. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

17. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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