Method for detecting rail corrugation fault on line by adopting self-adaptive time sequence window

Abstract

The invention belongs to the technical field of rail traffic rail detection, and discloses a method for detecting a rail corrugation fault on line by adopting a self-adaptive time sequence window. According to the invention, a method for carrying out time sequence window analysis processing on vibration acceleration signals collected by N measuring point sensors at the same side of a train is introduced, so that missed judgment caused by value errors is reduced; a wavelength range band-pass filtering method is introduced, and misjudgment caused by non-rail corrugation frequency signal interference is reduced; a mode of carrying out weighted calculation on rail corrugation indexes of N measuring points on the same side of a train is introduced, so that the reliability of the rail corrugation evaluation indexes is improved, and misjudgment caused by abnormal state of individual wheels is effectively avoided; whether the maximum deviation of rail corrugation wavelength indexes of N measuring points on the same side of a train is smaller than a deviation coefficient is introduced as an alarm condition, and misjudgment caused by abnormities of a plurality of wheels is effectively avoided. According to the rail corrugation fault detection method, the monitoring result is accurate and stable, the requirement for system performance is low, and the requirement for a real-time online monitoring system of low-cost embedded equipment is met.

Description

Technical Field

[0001] The invention belongs to the technical field of rail transit track detection, and relates to a method for online detection of rail corrugation faults by using an adaptive timing window. Background Art

[0002] By the end of 2024, the national railway operating mileage will be 160,000 kilometers, and the high-speed railway operating mileage will reach 46,000 kilometers, ranking first in the world.

[0003] During train operation, there are many technical indicators related to economy, comfort and safety that need to be focused on, and rail corrugation is one of them. Rail corrugation refers to the wear phenomenon of the longitudinal regularity of the top surface of the rail. Rail corrugation will affect the service life of the rail, affect the vertical unevenness of the train, increase the vibration of the contact between the train wheels and the rails, generate noise pollution, affect the riding comfort, and the vibration will also affect the service life of the train and rail components. In severe cases, it will cause safety problems and lead to derailment.

[0004] At present, rail corrugation detection is mainly divided into three categories: manual detection, special detection vehicle detection and real-time online monitoring. Manual detection is suitable for lines with obvious corrugation or low detection accuracy requirements. The advantages are simple operation, low cost and no need for complex equipment; the disadvantages are low detection efficiency, reliance on the experience of inspectors, and it is difficult to detect tiny corrugations or corrugations hidden near the internal structure of the rail. Special detection vehicles detect rail corrugation characteristic parameters based on inertial reference method, axle box acceleration integration method, chord measurement method or machine vision method, etc. The detection efficiency is improved compared with manual detection, but special detection vehicles are required, and detection needs to be carried out online during the "window" period of maintenance, which limits the coverage and efficiency of detection. Real-time online monitoring generally refers to the use of vibration acceleration sensors installed on the axle boxes of operating vehicles for detection, and the rail corrugation evaluation indicators are obtained through the detection algorithm for real-time detection.

[0005] At present, the existing real-time online monitoring method (patent number 2022116867393) can cover the entire operating line of the train and has high detection efficiency. However, when the train speed is lower than 200Km / h, due to the influence of factors such as the time difference in collecting rail corrugation fault signals caused by the distribution spacing of sensors and the average effect of the vibration signal in the non-rail corrugation period on the fault signal within the 1s signal period, the existing rail corrugation evaluation index calculation method has a high probability of missing reports, so the detection accuracy is worse than that of manual and special inspection vehicles. Summary of the invention

[0006] The present invention provides a specific solution to this difficult problem. The present invention adopts a method of performing time series window analysis and processing on the vibration acceleration signals collected by multiple measuring point sensors on the same side of the train, a wavelength range bandpass filtering method and a weighted calculation method, which can not only avoid missed judgments caused by value errors, but also avoid misjudgments caused by interference from non-rail corrugation frequency signals and wheel abnormalities.

[0007] The technical solution of the present invention:

[0008] A method for online detection of rail corrugation faults using an adaptive timing window is as follows:

[0009] Get the real-time speed information of the train;

[0010] Arrange measuring points on at least two wheels on the same side of the train to obtain vertical vibration acceleration signals of each measuring point;

[0011] Band-pass filtering is performed on the vertical vibration acceleration signal according to the wavelength range of the steel corrugation;

[0012] According to the vibration acceleration signal after bandpass filtering, the reference measuring point signal is enveloped and the envelope curve is drawn;

[0013] According to the obtained envelope curve, extract the time point of the corrugation signal in the envelope curve;

[0014] Calculate the delay parameters according to the positional relationship, spacing and vehicle speed of each measuring point and the reference measuring point;

[0015] According to the obtained corrugation signal time point and delay parameters, the vibration acceleration signal time period of the corresponding measuring point is intercepted and frequency domain transformation is performed at the same time;

[0016] According to the frequency domain data obtained by frequency domain transformation, the maximum amplitude and corresponding frequency in the frequency domain data are firstly extracted, and the rail corrugation amplitude index and rail corrugation wavelength index are calculated;

[0017] According to the rail corrugation amplitude index of the measuring point on the same side of the train, the rail corrugation evaluation index and the rail corrugation wavelength evaluation index are calculated and output;

[0018] When the train speed is greater than the preset value, the rail corrugation evaluation index is compared with the alarm threshold, and the rail corrugation wavelengths of the measuring points on the same side of the train are compared. When the alarm conditions are met, the alarm status is output.

[0019] A method for online detection of rail corrugation faults, the specific steps are as follows:

[0020] Step 1: Get the real-time speed TSpd of the train;

[0021] Step 2: Obtain vertical vibration acceleration signals of N wheels on the same side of the train;

[0022] Step 3: According to the wavelength range (L low ,L High ), calculate the cutoff frequency f of the bandpass filter x =TSpd*1000 / 3.6 / L High , filter upper cutoff frequency f s =TSpd*1000 / 3.6 / L low ;

[0023] Step 4: performing band-pass filtering on the vertical vibration acceleration signal obtained in step 2 according to the frequency range of the band-pass filtering obtained in step 3 to obtain a filtered vibration acceleration signal;

[0024] Step 5: According to the vibration acceleration signal obtained in step 4, select any measuring point as a reference measuring point, perform envelope calculation, and draw an envelope curve;

[0025] Step 6: Extract the corrugation signal time point T in the envelope curve according to the envelope curve Q and T Z ;

[0026] Step 7: According to the position relationship between each measuring point and the reference measuring point, the spacing L j and vehicle speed TSpd, calculate the delay parameter T d =L j *3.6 / TSpd;

[0027] Step 8: According to T Q , T Z and T d ; Intercept the vibration acceleration signal of each measuring point in the corresponding period, and perform FFTW frequency domain transformation at the same time;

[0028] Step 9: According to the frequency domain data obtained by the FFTW frequency domain transformation in step 8, first extract the maximum amplitude A and the corresponding frequency f in the frequency domain data, and calculate the rail corrugation amplitude index AdB=20log(A) and the rail corrugation wavelength index Ln=TSpd*1000 / (3.6*f);

[0029] Step 10: Sort the rail corrugation amplitude index AdB of the N measuring points on the same side of the train from large to small, in order of AdB1, AdB2, AdB3, AdB4, ..., AdB N Weighted calculation, calculate and output rail corrugation evaluation index GdB = a1*AdB1+a2*AdB2+a3*AdB3+a4*AdB4+……+a N *AdB N ;

[0030] Step 11: Average the rail corrugation wavelength index Ln of N measuring points on the same side of the train, calculate and output the rail corrugation wavelength evaluation index

[0031] Step 12: When the train speed is greater than the preset value, the rail corrugation evaluation index GdB is compared with the alarm threshold, and the rail corrugation wavelength Ln of N measuring points on the same side of the train is compared to determine whether the alarm condition is met and whether to alarm;

[0032] Step 13: Output the alarm status ALTtr and set the alarm status to 0.

[0033] As a preferred method, in step 3, in order to avoid interference from non-rail corrugation frequency signals, the wavelength range L low =30mm, L High =300mm.

[0034] As a preferred method, in step 5, the reference measuring point selects the first measuring point in the direction of vehicle travel.

[0035] As a better way, in step 6, according to the obtained envelope curve, the whole wave peak point in the envelope curve is extracted, and the time points T1 and T2 corresponding to the first and last peak points greater than the threshold a are determined as the corrugation signal extraction time point T Q and T Z ; Further, the preferred threshold a=1.5*the average value of all peak values ​​within the signal duration.

[0036] As a preferred method, in step 9, the method for extracting the maximum amplitude A and the corresponding frequency f in the frequency domain data is: using a least squares fitting algorithm to extract the maximum amplitude A and the corresponding frequency f in the frequency domain data.

[0037] As a preferred method, in step 10, due to the difference in wheel states, the wheel-rail excitation force is also different. In order to avoid misjudgment caused by abnormal state of individual wheels, the present invention introduces a method of weighted calculation of rail corrugation indexes at N measuring points on the same side of the train to improve the reliability of rail corrugation evaluation indexes; the number of measuring points N ranges from 2 to 16, preferably N = 4; weighting coefficients a1, a2, a3, a4 ..., a N The value range is 0.01-0.99, and a1+a2+a3+a4+……+a N =1.

[0038] As a preferred method, in step 12, the method for determining whether to alarm is: when the vehicle speed is greater than the preset value, the rail corrugation evaluation index GdB is compared with the alarm threshold. When GdB < 1-level alarm threshold, the operation is normal, and the state value ALTst = 0; when the 1-level alarm threshold ≤ GdB < 2-level alarm threshold, the state value ALTst = 1; when the M-1-level alarm threshold ≤ GdB < M-level alarm threshold, the state value ALTst = M-1; when GdB ≥ M-level alarm threshold, the state value ALTst = M; when the alarm is continuously for n seconds and the maximum deviation of the Ln value of N measuring points ≤ the deviation coefficient, the alarm state ALTtr = ALTst, and an alarm prompt is issued; otherwise, the alarm state ALTtr = 0, and no alarm prompt is issued; when the vehicle speed is less than the preset value, the judgment is terminated. If only the rail corrugation evaluation index is used for judgment, when multiple wheels are abnormal, a large number of false alarms will be caused. However, when multiple wheels are abnormal, the possibility of presenting a rail corrugation wavelength at the same time is extremely small. Therefore, the present invention introduces whether the rail corrugation wavelength indexes of N measuring points on the same side of the train are consistent as an alarm condition, that is, when the rail corrugation evaluation index exceeds the alarm threshold for n seconds continuously, and the maximum deviation of the rail corrugation wavelength indexes of the N measuring points on the same side of the train is ≤ the deviation coefficient, an alarm prompt is issued; further, the alarm level M has a value range of 1-10; preferably, the alarm level M=3, ALTst=1 is pre-judgment, ALTst=2 is early warning, and ALTst=3 is alarm; further, the value range of n is 1-10 seconds; further, the value range of the deviation coefficient is 0-20 mm.

[0039] Beneficial effects of the present invention: The rail corrugation fault detection method of the present invention introduces a method of performing time series window analysis and processing on the vibration acceleration signals collected by sensors at N measuring points on the same side of the train, thereby reducing missed judgments caused by errors in value selection; introduces a wavelength range bandpass filtering method, thereby reducing misjudgments caused by interference from non-rail corrugation frequency signals; introduces a method of weighted calculation of rail corrugation indicators at N measuring points on the same side of the train, thereby improving the reliability of rail corrugation evaluation indicators, thereby effectively avoiding misjudgments caused by abnormal conditions of individual wheels; introduces whether the maximum deviation of the rail corrugation wavelength indicators at N measuring points on the same side of the train is less than the deviation coefficient as an alarm condition, thereby effectively avoiding misjudgments caused by abnormalities in multiple wheels. The monitoring results of the rail corrugation fault detection method of the present invention are accurate and stable, with low requirements on system performance, meeting the requirements of a real-time online monitoring system for low-cost embedded devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the hardware structure of a system for implementing the method of the present invention.

[0041] Figure 2 It is a flow chart of the monitoring method of the present invention.

[0042] Figure 3These are the original time domain waveforms of measuring points 1#-4#, where (a) is the original time domain diagram of 1 car and 1 position, (b) is the original time domain diagram of 1 car and 2 positions, (c) is the original time domain diagram of 2 cars and 1 position, and (d) is the original time domain diagram of 2 cars and 3 positions.

[0043] Figure 4 These are the time domain waveforms of the 1#-4# measuring points after filtering, where (a) is the time domain diagram of 1 car and 1 position filtering, (b) is the time domain diagram of 1 car and 2 positions filtering, (c) is the time domain diagram of 2 cars and 1 position filtering, and (d) is the time domain diagram of 2 cars and 3 positions filtering.

[0044] Figure 5 This is the time domain envelope curve of measuring point 1#.

[0045] Figure 6 This is the time window diagram of the corrugation signal extracted from the 1# measuring point.

[0046] Figure 7 It is the time window diagram of the corrugation signal of the original method 1#-4# measuring points, among which (a) is the time domain diagram of 1 car 1 position filtering, (b) is the time domain diagram of 1 car 2 positions filtering, (c) is the time domain diagram of 2 cars 1 position filtering, and (d) is the time domain diagram of 2 cars 3 positions filtering.

[0047] Figure 8 It is the time window diagram of the corrugation signal of the 1#-4# measuring points of this method, among which (a) is the time domain diagram of the 1#-1# filtering of the 1# vehicle, (b) is the time domain diagram of the 1#-2# filtering of the 1# vehicle, (c) is the time domain diagram of the 1#-1# filtering of the 2# vehicles, and (d) is the time domain diagram of the 3# filtering of the 2# vehicles.

[0048] Fig. 9 It is the frequency domain waveform diagram of the vibration signal of the 1#-4# measuring points of the original method, among which (a) is the filtered spectrum diagram of 1 car and 1 position, (b) is the filtered spectrum diagram of 1 car and 2 positions, (c) is the filtered spectrum diagram of 2 cars and 1 position, and (d) is the filtered spectrum diagram of 2 cars and 3 positions.

[0049] Fig.10 It is the frequency domain waveform diagram of the vibration signal of the 1#-4# measuring points of this method, among which (a) is the filtered spectrum diagram of 1 car and 1 position, (b) is the filtered spectrum diagram of 1 car and 2 positions, (c) is the filtered spectrum diagram of 2 cars and 1 position, and (d) is the filtered spectrum diagram of 2 cars and 3 positions.

[0050] Fig.11 It is the trend chart of rail corrugation evaluation indicators using the original method.

[0051] Fig.12 This is the trend chart of rail corrugation evaluation indicators of this method. DETAILED DESCRIPTION

[0052] The specific implementation of the present invention is described in detail below in combination with the technical scheme and the accompanying drawings.

[0053] Example 1

[0054] like Figure 1 As shown in the schematic diagram of the system hardware structure, the vibration sensor is arranged above the train axle box bearing, and each of the eight wheels of each carriage is arranged with a vibration acceleration sensor. The data acquisition module collects the wheel vertical vibration acceleration signal obtained by the sensor and sends it to the diagnosis and analysis algorithm processing module; the communication module obtains the real-time speed of the train sent by the on-board central control unit through Ethernet and sends it to the diagnosis and analysis algorithm processing module for calculating the rail corrugation wavelength, filtering parameters, etc.; the rail corrugation evaluation index, rail corrugation wavelength evaluation index and alarm information calculated by the diagnosis and analysis algorithm processing module are sent from the communication module to the on-board central control unit in real time through Ethernet. This method is implemented in the diagnosis and analysis algorithm processing module.

[0055] like Figure 2 The monitoring method flow chart shows that the specific steps are as follows:

[0056] Step 1: Get the real-time speed information TSpd of the train;

[0057] Step 2: Obtain the collected vertical vibration acceleration signal of the train wheel;

[0058] Step 3: According to the wavelength range L low and L High , calculate the cutoff frequency f of the bandpass filter x =TSpd*1000 / 3.6 / L High , filter upper cutoff frequency f s =TSpd*1000 / 3.6 / L low ;

[0059] Step 4: Bandpass filter the vibration acceleration signal. The filter selects the 6th-order Butterworth filter. The filter transfer function is as follows:

[0060]

[0061] The wavelength range bandpass filtering method is introduced to effectively reduce the misjudgment caused by the interference of non-rail corrugation frequency signals.

[0062] Step 5: For the vibration acceleration signal of the first measuring point, use Hilbert transform to generate the signal envelope curve. The calculation formula is:

[0063]

[0064] Among them, x(t) is the original signal function, y(t) is the Hilbert transform of the original signal function

[0065] Step 6: According to the obtained upper envelope curve, extract the peak point of the whole wave in the envelope curve, determine the time points T1 and T2 corresponding to the first and last peak points greater than the threshold a, and use them as the extraction time point T of the corrugation signal. Q and T Z ;

[0066] Step 7: According to the distance L between each measuring point and the first measuring point j and vehicle speed TSpd, calculate the delay parameter T d =L j *3.6 / TSpd;

[0067] Step 8: According to T Q , T Z and T d ; Intercept the corresponding T of each measuring point Q +T d To T Z +T d The vibration acceleration signal of the time period is transformed into the frequency domain by FFTW at the same time. The calculation formula is as follows:

[0068]

[0069] According to the properties of the correlation function and the use of recursive divide and conquer, all coefficients, that is, the frequency domain amplitudes, can be quickly calculated.

[0070] A method of performing time series window analysis and processing on the vibration acceleration signals collected by sensors at multiple measuring points on the same side of the train is introduced, which can effectively reduce missed judgments caused by value errors.

[0071] Step 9: extract the maximum amplitude A and the corresponding frequency f in the frequency domain data, the extraction algorithm is the least square fitting algorithm, and then calculate the rail corrugation amplitude index AdB=20log(A) and the rail corrugation wavelength index Ln=TSpd*1000 / (3.6*f);

[0072] Step 10: Sort the rail corrugation index AdB of the four measuring points on the same side of the train from large to small, and perform weighted calculation to calculate and output the rail corrugation evaluation index GdB = a1*AdB1+a2*AdB2+a3*AdB3+a4

[0073] *AdB4; the weighted coefficients a1, a2, a3, and a4 range from 0.01 to 0.99, and a1+a2+a3+a4=1, preferably a1=0.15, a2=0.35, a3=0.35, and a4=0.15. The method of weighted calculation of the rail corrugation index at the four measuring points on the same side of the train is introduced, which can effectively reduce the influence of wheel state differences on the calculation of rail corrugation index and improve the reliability of rail corrugation evaluation index.

[0074] Step 11: Average the rail corrugation wavelength index Ln of the four measuring points on the same side of the train, calculate and output the rail corrugation wavelength evaluation index

[0075] Step 12: When the vehicle speed TSpd≥10km / h, compare the rail corrugation evaluation index GdB with the alarm threshold. When GdB<10(dB), the operation is normal, and the state value ALTst=0; when 10(dB)≤GdB<18(dB) for n consecutive seconds, and the maximum deviation of the Ln value of the four measuring points is ≤deviation coefficient, the state value ALTst=1, and the alarm state ALTtr=1; when 18(dB)≤GdB<23(dB) for n consecutive seconds, and the maximum deviation of the Ln value of the four measuring points is ≤deviation coefficient, the state value ALTst=2, and the alarm state ALTtr=2; when GdB≥23(dB) for n consecutive seconds, and the maximum deviation of the Ln value of the four measuring points is ≤deviation coefficient, the state value ALTst=3, the alarm state ALTtr=3, and an alarm prompt is given; otherwise, the alarm state ALTtr=0, and no alarm prompt is given; when the vehicle speed is <10km / h, the judgment ends. The consistency of the rail wave index at the four measuring points on the same side of the train is introduced as an alarm condition, that is, when the rail wave evaluation index exceeds the alarm threshold for n consecutive seconds, and the maximum deviation of the rail wave index at the four measuring points on the same side of the train is ≤ the deviation coefficient, an alarm prompt is issued, avoiding false alarms caused by abnormalities in 3 to 4 wheels. Preferably, when the rail wave evaluation index exceeds the alarm threshold for n = 1 second continuously, and the maximum deviation of the Ln value of the four measuring points is ≤ the deviation coefficient of 5 mm, an alarm prompt is issued;

[0076] Step 13: Output the alarm status ALTtr and set the alarm status to 0.

[0077] Example 2

[0078] The method of the present invention is applied to a domestic intelligent high-speed railway dynamic safety monitoring system to perform rail corrugation fault diagnosis, as follows:

[0079] Step 1: Get the real-time speed information of the train TSpd = 160.41Km / h;

[0080] Step 2: Obtain the collected vertical vibration acceleration signal of the train wheel;

[0081] Step 3: According to the wavelength range L low and L High , calculate the cutoff frequency f of the bandpass filter x =160.41*1000 / 3.6 / 300=148.53Hz, filter upper cutoff frequency f s =160.41*1000 / 3.6 / 30=1485.3Hz

[0082] Step 4: Figure 3 to Figure 4 , perform band-pass filtering on the vibration acceleration signal;

[0083] Step 5: Figure 5 , perform envelope calculation on the vibration acceleration signal of the first measuring point to generate an envelope curve;

[0084] Step 6: Figure 6 According to the obtained upper envelope curve, the whole wave peak point in the envelope curve is extracted, the threshold a=1.5*the average value of the peak value of the envelope curve is calculated, and the time points T1=0.511s and T2=1.145s corresponding to the first and last peak points greater than the threshold a are determined as the corrugation signal extraction time point T Q and T Z ;

[0085] Step 7: According to the distance L between each measuring point and the first measuring point j and vehicle speed TSpd, calculate the delay parameter T d1 =L j / TSpd=23*3.6 / 160.41=0.516s、T d2 =L j / TSpd=46*3.6 / 160.41=1.032s、T d3 =L j / TSpd = 69 * 3.6 / 160.41 = 1.549s,

[0086] Step 8: Figure 8 , according to T Q , T Z and T d ; Intercept the corresponding T of each measuring point Q +T d To T Z +T d The vibration acceleration signal of the time period. Figure 7 and Fig. 9 When the timing window is not intercepted, due to the time difference between different measuring points entering the fault track and the influence of the normal track vibration signal, the fault frequency amplitude in the frequency domain transformation cannot correctly reflect the actual condition of the track, that is, due to the value error, it is easy to miss the rail corrugation fault. Fig.10 , perform FFTW frequency domain transformation on the intercepted vibration signal, the fault frequency amplitude can better reflect the real condition of the fault track, and the calculation result is more accurate and reliable;

[0087] Step 9: extract the maximum amplitude A and the corresponding frequency f in the frequency domain data, and then calculate the rail corrugation amplitude index AdB=20log(A) and the rail corrugation wavelength index Ln=TSpd*1000 / (3.6*f);

[0088] 1# measurement point AdB=20log(8.78762g)=18.877dB

[0089] 1# measuring point Ln=TSpd*1000 / (3.6*f)=160.41*1000 / (3.6*529.264)=84.19mm 2# measuring point AdB=20log(8.20622g)=18.283dB

[0090] 2# measuring point Ln=TSpd*1000 / (3.6*f)=160.41*1000 / (3.6*527.689)=84.44mm 3# measuring point AdB=20log(10.4554g)=20.387dB

[0091] 3# measuring point Ln=TSpd*1000 / (3.6*f)=160.41*1000 / (3.6*527.689)=84.44mm 4# measuring point AdB=20log(9.56975g)=19.617dB

[0092] 4# measuring point Ln = TSpd*1000 / (3.6*f) = 160.41*1000 / (3.6*527.689) = 84.44 mm

[0093] Step 10: Fig.12 , sort the rail corrugation index GndB of the four measuring points on the same side of the train from large to small, perform weighted calculation, and calculate and output the rail corrugation evaluation index.

[0094] GdB=a1*AdB1+a2*AdB2+a3*AdB3+a4*AdB4=0.15*20.387+0.35*19.617+0.35*18.8

[0095] 77+0.15*18.283=19.27dB; Fig.11 The calculation result of rail corrugation evaluation index for the same data using the original algorithm is 4.46dB, and the frequency deviation is 78.994Hz (that is, the wavelength deviation reaches 11mm), which misses the rail corrugation fault. The calculation result of this method is more accurate and reliable.

[0096] Step 11: Average the rail corrugation wavelength index Ln of the four measuring points on the same side of the train, calculate and output the rail corrugation wavelength evaluation index

[0097] Step 12: When the vehicle speed TSpd160.41km / h≥10km / h, compare the rail corrugation evaluation index GdB with the alarm threshold. Since 18(dB)≤GdB=19.27dB<23(dB) for 1 second continuously, the state value ALTst=2, and the maximum deviation of the Ln values ​​of the four measuring points (84.44mm-84.19mm=0.25mm)≤5mm, the alarm state ALTtr=ALTst=2;

[0098] Step 10: Output alarm status ALTtr=2, that is, rail corrugation prediction alarm.

[0099] The intelligent high-speed rail dynamic safety monitoring system has been running for 9 months using this algorithm, and has prompted alarms at 12 locations 482 times. After manual measurement of the rails at the alarm locations, it is found that there are indeed rail corrugation defects that are the same as the monitoring results. Compared with the original algorithm, 6 locations have been detected, which improves the fault detection rate and has an accuracy rate of 100%. The monitoring results of the method of the present invention are accurate, and the monitoring method has high monitoring stability.

Claims

1. A method for online detection of rail corrugation faults using an adaptive timing window, characterized in that: Here are the steps: Get the real-time speed information of the train; Arrange measuring points on at least two wheels on the same side of the train to obtain vertical vibration acceleration signals of each measuring point; Band-pass filtering is performed on the vertical vibration acceleration signal according to the wavelength range of the steel corrugation; According to the vibration acceleration signal after bandpass filtering, the reference measuring point signal is enveloped and the envelope curve is drawn; According to the obtained envelope curve, extract the time point of the corrugation signal in the envelope curve; Calculate the delay parameters according to the positional relationship, spacing and vehicle speed of each measuring point and the reference measuring point; According to the obtained corrugation signal time point and delay parameters, the vibration acceleration signal time period of the corresponding measuring point is intercepted and frequency domain transformation is performed at the same time; According to the frequency domain data obtained by frequency domain transformation, the maximum amplitude and corresponding frequency in the frequency domain data are firstly extracted, and the rail corrugation amplitude index and rail corrugation wavelength index are calculated; According to the rail corrugation amplitude index of the measuring point on the same side of the train, the rail corrugation evaluation index and the rail corrugation wavelength evaluation index are calculated and output; When the train speed is greater than the preset value, the rail corrugation evaluation index is compared with the alarm threshold, and the rail corrugation wavelengths of the measuring points on the same side of the train are compared. When the alarm conditions are met, the alarm status is output.

2. A method for online detection of rail corrugation faults, characterized in that: The specific steps are as follows: Step 1: Get the real-time speed TSpd of the train; Step 2: Obtain vertical vibration acceleration signals of N wheels on the same side of the train; Step 3: According to the wavelength range (L low ,L High ), calculate the cutoff frequency f of the bandpass filter x =TSpd*1000 / 3.6 / L High , filter upper cutoff frequency f s =TSpd*1000 / 3.6 / L low ; Step 4: performing band-pass filtering on the vertical vibration acceleration signal obtained in step 2 according to the frequency range of the band-pass filtering obtained in step 3 to obtain a filtered vibration acceleration signal; Step 5: According to the vibration acceleration signal obtained in step 4, select any measuring point as a reference measuring point, perform envelope calculation, and draw an envelope curve; Step 6: Extract the corrugation signal time point T in the envelope curve according to the envelope curve Q and T Z ; Step 7: According to the position relationship between each measuring point and the reference measuring point, the spacing L j and vehicle speed TSpd, calculate the delay parameter T d =L j *3.6 / TSpd; Step 8: According to T Q , T Z and T d ; Intercept the vibration acceleration signal of each measuring point in the corresponding period, and perform FFTW frequency domain transformation at the same time; Step 9: According to the frequency domain data obtained by the FFTW frequency domain transformation in step 8, first extract the maximum amplitude A and the corresponding frequency f in the frequency domain data, and calculate the rail corrugation amplitude index AdB=20log(A) and the rail corrugation wavelength index Ln=TSpd*1000 / (3.6*f); Step 10: Sort the rail corrugation amplitude index AdB of the N measuring points on the same side of the train from large to small, in order of AdB1, AdB2, AdB3, AdB4, ..., AdB N Weighted calculation, calculate and output rail corrugation evaluation index GdB = a1*AdB1+a2*AdB2+a3*AdB3+a4*AdB4+……+a N *AdB N ; Step 11: Average the rail corrugation wavelength index Ln of N measuring points on the same side of the train, calculate and output the rail corrugation wavelength evaluation index Step 12: When the train speed is greater than the preset value, the rail corrugation evaluation index GdB is compared with the alarm threshold, and the rail corrugation wavelength Ln of N measuring points on the same side of the train is compared to determine whether the alarm condition is met and whether to alarm; Step 13: Output the alarm status ALTtr and set the alarm status to 0.

3. The method according to claim 2, characterized in that In step 3, the wavelength range L low =30mm, L High =300mm.

4. The method according to claim 2, characterized in that: In step 5, the reference measuring point selects the first measuring point in the direction of vehicle travel.

5. The method according to claim 2, characterized in that: In step 6, according to the obtained envelope curve, the whole wave peak point in the envelope curve is extracted, and the time points T1 and T2 corresponding to the first and last peak points greater than the threshold a are determined as the corrugation signal extraction time point T Q and T Z ; Threshold a = 1.5*average value of all peak values ​​within the signal duration.

6. The method according to claim 2, characterized in that In step 9, the maximum amplitude A and the corresponding frequency f in the frequency domain data are extracted by using a least squares fitting algorithm.

7. The method according to claim 2, characterized in that In step 10, the number of measuring points N ranges from 2 to 16; the weighting coefficients a1, a2, a3, a4, ..., a N The value range is 0.01-0.99, and a1+a2+a3+a4+……+a N =1.

8. The method according to claim 2, characterized in that: In step 12, the method for determining whether to alarm is as follows: when the vehicle speed is greater than a preset value, the rail corrugation evaluation index GdB is compared with the alarm threshold; when GdB < level 1 alarm threshold, the operation is normal, and the state value ALTst = 0; when level 1 alarm threshold ≤ GdB < level 2 alarm threshold, the state value ALTst = 1; when level M-1 alarm threshold ≤ GdB < level M alarm threshold, the state value ALTst = M-1; when GdB ≥ level M alarm threshold, the state value ALTst = M; When the alarm is sounded continuously for n seconds and the maximum deviation of the Ln values ​​of N measuring points is ≤ the deviation coefficient, the alarm state ALTtr=ALTst and an alarm prompt is given; otherwise, the alarm state ALTtr=0 and no alarm prompt is given; when the vehicle speed is less than the preset value, the judgment ends.

9. The method according to claim 2, characterized in that: In step 12, whether the rail corrugation wavelength index of N measuring points on the same side of the train is consistent is introduced as an alarm condition, that is, when the rail corrugation evaluation index exceeds the alarm threshold for n seconds continuously and the maximum deviation of the rail corrugation wavelength index of N measuring points on the same side of the train is ≤ the deviation coefficient, an alarm prompt is issued; the alarm level M takes a value range of 1-10.

10. The method according to claim 9, characterized in that The alarm level M=3, ALTst=1 is prediction, ALTst=2 is warning, ALTst=3 is alarm; the value range of n is 1-10 seconds; the value range of the deviation coefficient is 0-20 mm.

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