A rail online detection method and system

Abstract

The present invention relates to an online rail detection method and system, the method comprising: collecting original signals and filtering them; performing Fourier transform on the filtered signals to obtain a first modulus; generating a sinusoidal reference signal according to the frequency corresponding to the maximum value of the spectrum energy after the Fourier transform, and performing Fourier transform on the sinusoidal reference signal to obtain a second modulus; obtaining a correlation coefficient based on the first modulus and the second modulus; and detecting the health status of the rails based on the correlation coefficient. The online rail detection method of the present invention can monitor the damage of rails to different degrees, such as rail head fracture, rail waist fracture, intact rails, and complete rail fractures in real time, so as to report the damage degree of the rails before the rails are completely broken, thereby improving driving safety.

Description

Technical Field

[0001] The present invention belongs to the technical field of railway track status detection, and in particular relates to a rail online detection method and system. Background Art

[0002] The health of rails is directly related to the running safety of trains. The rails in the turnout area are easily broken due to repeated movement to provide steering for trains, which seriously threatens the running safety of trains and the safety of people's lives and property. At present, the detection of rails in the turnout area is mainly carried out manually by ultrasonic flaw detectors or hand-pushed rail flaw detection vehicles at the skylight points of railway operation. This method requires a large amount of human resources, is inefficient, requires the occupation of train running lines, and cannot be detected during train operation. With the popularization of high-speed trains and the increase in line occupancy, the impact, extrusion force and frequency of trains on rails are increasing, resulting in a decrease in the life of rails and an increasing probability of rail breakage accidents, posing a serious threat to the running safety of trains. In order to change the direction of the train, the rails in the turnout area need to be moved repeatedly, which is very likely to break. Therefore, it is necessary to study a real-time online monitoring technology for the health status of rails in the turnout area.

[0003] At present, rail health status monitoring is mainly divided into online monitoring and offline detection. Online monitoring mainly relies on track circuits, which can monitor the complete breakage of rails. However, in the turnout area, since the slide bed forms an electrical connection between the turnout point rail and the base rail, when the rail breaks, the electrical signal can still pass through the slide bed to the track circuit receiving end, making it impossible to monitor the breakage of the rail. Offline detection is mainly carried out through large rail flaw detection vehicles and small flaw detectors. This method can only be carried out at the skylight points where the train is stopped, which requires line resources and cannot monitor in real time whether the rail is broken. In addition, this method is inefficient and requires a lot of human resources.

[0004] At present, some online monitoring systems for the health status of rails in the switch area mainly rely on the amplitude of the signal at the receiving end to make judgments. A major disadvantage of this method is that the amplitude of the signal at the receiving end fluctuates widely, sometimes equivalent to the amplitude when the rail breaks, and it is impossible to effectively monitor the status of the rail. This problem is mainly due to the fact that the transducer installed on the rail is greatly affected by temperature. When the temperature changes, the density of the rail changes, resulting in a mismatch in the acoustic impedance between the transducer and the rail; in addition, the coupling state between the transducer and the rail also changes greatly with the temperature, which ultimately causes the energy of the acoustic signal coupled to the rail to fluctuate and the frequency to shift.

[0005] Therefore, there is an urgent need to provide an online rail detection method and system that can solve the problems of frequency offset and large energy fluctuation of acoustic signals transmitted on the rails when the temperature changes, and can realize all-weather real-time online monitoring of the health status of the switch area rails without interfering with the existing track safety environment. Summary of the invention

[0006] In view of the above problems, the present invention provides a rail online detection method, the method comprising:

[0007] Collect the original signal and filter it;

[0008] Performing Fourier transform on the filtered signal to obtain a first modulus value;

[0009] Generate a sinusoidal reference signal according to the frequency corresponding to the maximum value of the spectrum energy after Fourier transformation, and perform Fourier transformation on the sinusoidal reference signal to obtain a second modulus value;

[0010] Calculate a correlation coefficient based on the first modulus value and the second modulus value;

[0011] The health status of the rail is detected based on the correlation coefficient.

[0012] Further, when the correlation coefficient is not greater than a first threshold value, it is determined that the rail is completely broken; or,

[0013] When the correlation coefficient is greater than the first threshold value and not greater than the second threshold value, it is determined that the rail is broken to the rail waist; or,

[0014] When the correlation coefficient is greater than the second threshold value and not greater than the third threshold value, it is determined that the rail is broken to the rail head; or,

[0015] When the correlation coefficient is greater than the third threshold value and not greater than the fourth threshold value, it is determined that the rail is intact.

[0016] Furthermore, the specific calculation method of performing Fourier transform on the filtered signal to obtain the first modulus value is:

[0017] For the filtered signal x1_ filtered (n) Perform Fourier transform to obtain X1(k);

[0018]

[0019] Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value;

[0020] Calculate the first modulus value X after Fourier transform of the filtered signal 1_abs (k):

[0021]

[0022] Where a1(k) is the real part of X1(k), and b1(k) is the imaginary part of X1(k).

[0023] Furthermore, the specific calculation method of the second modulus value is:

[0024] Performing Fourier transform on the filtered signal;

[0025] Calculate the frequency f corresponding to the maximum value of the spectrum energy of the filtered signal after Fourier transformation;

[0026] A sinusoidal reference signal x2(n) is generated according to the frequency f, and the sinusoidal reference signal is subjected to Fourier transformation to obtain X2(k):

[0027]

[0028] Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value;

[0029] Calculate the second modulus value X after Fourier transformation 2_abs (k):

[0030]

[0031] Where a2(k) is the real part of X2(k) and b2(k) is the imaginary part of X2(k).

[0032] Furthermore, the specific calculation method for obtaining the correlation coefficient based on the first modulus value and the second modulus value is:

[0033]

[0034] Among them, ρ(X 1_abs (k),X 2_abs (k)) represents the first modulus value X 1_abs (k) and the second modulus value X 2_abs (k), N is the length of the module value, μ1 and μ2 are the first module value X 1_abs (k) and the second modulus value X 2_abs The mean of (k), X 1_abs (k) is the first modulus value of the kth data, X 2_abs (k) is the second modulus value of the kth data.

[0035] The present invention also provides a rail online detection system, the system comprising:

[0036] The system includes a sensor, a filter, and a receiver;

[0037] The sensor is used to collect original signals;

[0038] The filter is used to filter the original signal;

[0039] The receiver is used to perform Fourier transform on the filtered signal to obtain a first modulus value;

[0040] The receiver is used to generate a sinusoidal reference signal according to the frequency corresponding to the maximum value of the spectrum energy after Fourier transformation, and perform Fourier transformation on the sinusoidal reference signal to obtain a second modulus value;

[0041] The receiver is used to obtain a correlation coefficient based on the first modulus value and the second modulus value;

[0042] The receiver is used to detect the health status of the rail based on the correlation coefficient.

[0043] Further, the receiver is used to determine that the rail is completely broken when the correlation coefficient is not greater than a first threshold; or,

[0044] When the correlation coefficient is greater than the first threshold value and not greater than the second threshold value, it is determined that the rail is broken to the rail waist; or,

[0045] When the correlation coefficient is greater than the second threshold value and not greater than the third threshold value, it is determined that the rail is broken to the rail head; or,

[0046] When the correlation coefficient is greater than the third threshold value and not greater than the fourth threshold value, it is determined that the rail is intact.

[0047] Furthermore, the receiver is used to filter the signal x of length N. 1_filtered (n) Perform N-point Fourier transform to obtain X1(k);

[0048]

[0049] Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value;

[0050] Calculate the first modulus value X after Fourier transformation 1_abs (k):

[0051]

[0052] Where a1(k) is the real part of X1(k), and b1(k) is the imaginary part of X1(k).

[0053] Further,

[0054] The receiver is used to calculate the second modulus value, and the specific calculation method is:

[0055] Performing Fourier transform on the filtered signal;

[0056] Calculate the frequency f corresponding to the maximum value of the spectrum energy after Fourier transformation;

[0057] A sinusoidal reference signal x2(n) with a length of N points is generated according to the frequency f, and an N-point Fourier transform is performed on the sinusoidal reference signal to obtain X2(k):

[0058]

[0059] Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value;

[0060] Calculate the second modulus value X after Fourier transformation 2_abs (k):

[0061]

[0062] Where a2(k) is the real part of X2(k) and b2(k) is the imaginary part of X2(k).

[0063] Further, the receiver is used to obtain a correlation coefficient based on the first modulus value and the second modulus value, and the specific calculation includes:

[0064]

[0065] Among them, ρ(X 1_abs (k),X 2_abs (k)) represents the first modulus value X 1_abs (k) and the second modulus value X 2_abs (k), N is the length of the module value, μ1 and μ2 are the first module value X 1_abs (k) and the second modulus value X 2_abs The mean of (k), X 1_abs (k) is the first modulus value of the kth data, X 2_abs (k) is the second modulus value of the kth data.

[0066] The present invention has the following beneficial effects:

[0067] (1) When a rail breaks in the switch area, an accurate and timely alarm can be sounded, which facilitates the rapid investigation and replacement of the broken rails, improves the real-time and accuracy of track inspection, and reduces labor costs;

[0068] (2) It can monitor the damage of rails of different degrees (rail head break, rail waist break, rail intact, rail completely broken) in real time, so as to report the damage degree of rails before they are completely broken, thus improving driving safety;

[0069] (3) Solved the problem of frequency shift and large energy fluctuation of acoustic signals transmitted on the rails when the temperature changes;

[0070] (4) Without interfering with the existing track safety environment, it is possible to achieve all-weather real-time online monitoring of the health status of the switch area rails.

[0071] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] 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 description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0073] Figure 1 A schematic structural diagram of a rail online detection system according to an embodiment of the present invention is shown;

[0074] Figure 2 A flow chart of a rail online detection method according to an embodiment of the present invention is shown;

[0075] Figure 3 A schematic diagram of an original acoustic signal for online detection of rails according to an embodiment of the present invention is shown;

[0076] Figure 4 shows an amplitude-frequency characteristic curve of a high-pass filter according to an embodiment of the present invention;

[0077] Figure 5 A schematic diagram of an acoustic signal after being filtered by a high-pass filter according to an embodiment of the present invention is shown;

[0078] Figure 6 The spectrum diagram after Fourier transformation of rail online detection according to an embodiment of the present invention is shown;

[0079] Figure 7 A correlation coefficient curve diagram of four different damage degrees of the rail according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] The present invention provides a method and system for online detection of rails. The method and system algorithm calculates the frequency corresponding to the maximum value of the received signal spectrum and generates a sinusoidal reference signal of the frequency value, and calculates the correlation coefficient between the original signal spectrum and the sinusoidal reference signal spectrum to monitor the health status of the rails. The embodiment of the present invention takes the health status detection of the rails in the turnout area as an example for illustrative description, but is not limited to the health status detection of the rails in the turnout area. The health status detection of the rails in any section can be applied to the present invention.

[0082] In the detection of the health status of the rails in the switch area, many devices are included, such as transmitters, transducers, sensors, filters, receivers, data transmission modules, power supply modules and display terminals, etc. In order to realize the detection of the health status of the rails in the switch area, there is an interactive relationship between different devices.

[0083] The health status detection of the turnout rail in the embodiment of the present invention is exemplified by several common devices. According to the connection relationship between the related devices for the health status detection of the turnout rail, the interface connection relationship between the various devices is as follows: Figure 1 As shown, Figure 1 The schematic diagram of the structure of the rail online detection system according to the embodiment of the present invention is shown. Figure 1 It can be seen that the transmitter and transducer located in the outdoor trackside cabinet are interconnected, the transducer and the sensor are interconnected, and the sensor and the receiver are interconnected. The electrical signal is sent out by the transmitter and converted into an acoustic signal by the transducer, and the acoustic signal is transmitted to the receiver through the sensor. The acoustic signal is converted into a peak factor in the receiver, and the receiver and the data transmission module are interconnected. The receiver transmits the peak factor value to the data transmission module, and the data transmission module transmits the received peak factor value to the display terminal located outdoors. The power supply module is connected to the receiver, the transmitter and the data transmission module, and is used to power the receiver, the transmitter and the data transmission module. It should be noted that the embodiments of the present invention are only illustrative of the above-mentioned device as an example, but are not limited to the above-mentioned device.

[0084] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0085] For example, the rail online detection method provided by the present invention is as follows: Figure 2As shown, Figure 2 A flow chart of a rail online detection method according to an embodiment of the present invention is shown, and the method comprises:

[0086] Collect the original signal and filter it;

[0087] The original signal is generated by the transmitter sending out an electrical signal with a frequency of 10kHz. The original signal is converted into an acoustic signal by the transducer installed on the rail waist at the root end of the rail in the switch area and coupled to the rail. The acoustic signal of the rail waist at the tip of the switch area rail is collected by the sensor, which is installed on the rail waist at the tip of the switch area rail. In the sampling theorem, the sampling rate must be more than twice the highest frequency. In theory, the higher the sampling rate, the better. When it is too high, the hardware cost of the equipment is high. Therefore, the system sampling frequency is set to 100kHz, and the signal length is N = 4096 points. The original acoustic signal x1(n) is obtained, where n = 0, 1, ..., N-1, such as Figure 3 As shown, Figure 3 A schematic diagram of the original acoustic signal of rail online detection is shown, where the horizontal axis represents time and the vertical axis represents amplitude.

[0088] A high-pass filter is used to filter the collected rail tip and waist sound signal of the switch area. The high-pass filter can be a Chebyshev high-pass filter, such as Figure 4 As shown, Figure 4 The figure shows an amplitude-frequency characteristic curve of a high-pass filter according to an embodiment of the present invention, where the horizontal axis represents frequency and the vertical axis represents amplitude.

[0089] In order to filter out low-frequency noise and interference caused by passing vehicles, the passband frequency of the filter is set to 8kHz-100kHz. Figure 5 As shown, this is a schematic diagram of the sound signal after filtering by a high-pass filter, where the horizontal axis represents time and the vertical axis represents amplitude.

[0090] The specific calculation method for obtaining the first modulus value by Fourier transforming the filtered signal is:

[0091] For the filtered signal x 1_filtered (n) Perform N-point Fourier transform to obtain X1(k);

[0092]

[0093] Wherein, N=4096, k=0,1,…,N-1; n=0,1,…,N-1;

[0094] Calculate the first modulus value X after Fourier transformation 1_abs (k):

[0095]

[0096] Where a1(k) is the real part of X1(k), and b1(k) is the imaginary part of X1(k).

[0097] The specific calculation method of the second modulus value is:

[0098] Performing Fourier transform on the filtered signal;

[0099] Calculate the frequency f corresponding to the maximum value of the spectrum energy after Fourier transform, such as Figure 6 As shown, Figure 6 The spectrum diagram after Fourier transformation of rail online detection according to an embodiment of the present invention is shown, where the horizontal axis represents frequency and the vertical axis represents amplitude;

[0100] Generate a sinusoidal reference signal x2(n) according to the frequency f, and perform N-point Fourier transform on the sinusoidal reference signal to obtain X2(k):

[0101]

[0102] Wherein, N=4096, k=0,1,…,N-1; n=0,1,…,N-1;

[0103] Calculate the second modulus value X after Fourier transformation 2_abs (k):

[0104]

[0105] Where a2(k) is the real part of X2(k) and b2(k) is the imaginary part of X2(k).

[0106] According to the first modulus value X 1_abs (k), the second modulus value X 2_abs (k) The specific calculation method for the correlation coefficient is:

[0107]

[0108] Among them, ρ(X 1_abs (k),X 2_abs (k)) represents the first modulus value X 1_abs (k) and the second modulus value X 2_abs (k), N is the length of the module value, μ1 and μ2 are the first module value X 1_abs (k) and the second modulus value X 2_abs The mean of (k), X 1_abs (k) is the first modulus value of the kth data, X 2_abs (k) is the second modulus value of the kth data.

[0109] Judge the rail health status based on the correlation coefficient;

[0110] When the correlation coefficient is not greater than the first threshold, it is judged that the rail is completely broken; or, when the correlation coefficient is greater than the first threshold but not greater than the second threshold, it is judged that the rail is broken to the rail waist; or, when the correlation coefficient is greater than the second threshold but not greater than the third threshold, it is judged that the rail is broken to the rail head; or, when the correlation coefficient is greater than the third threshold but not greater than the fourth threshold, it is judged that the rail is intact.

[0111] The present invention collects multiple test data under four different degrees of rail damage, including four states: the rail is intact, the rail is broken to the rail head, the rail is broken to the rail waist, and the rail is completely broken. According to the algorithm steps of the present invention, the correlation coefficient value of the collected acoustic signal is calculated. The results are as follows: Figure 7 As shown, Figure 7 The graph shows the correlation coefficients under four different degrees of damage to the rails, with the horizontal axis being the number of samples and the vertical axis being the correlation coefficient. When the rail is intact, its correlation coefficient value fluctuates around 0.7; when the rail breaks to the rail head, its correlation coefficient value fluctuates around 0.5; when the rail breaks to the rail waist, its correlation coefficient value fluctuates around 0.25; when the rail is completely broken, most of its correlation coefficient values ​​are less than 0.22. It can be seen that the deeper the damage to the rail, the smaller its correlation coefficient value. Therefore, the correlation coefficient value can be used to describe the degree of damage to the rail. In addition, according to the experimental results, the embodiment of the present invention sets the first threshold value to 0.22, the second threshold value to 0.4, the third threshold value to 0.6, and the fourth threshold value to 1. The specific judgment is as follows:

[0112] When the correlation coefficient is greater than 0 and less than or equal to 0.22, it is judged that the rail is completely broken; or,

[0113] When the correlation coefficient is greater than 0.22 and less than or equal to 0.4, it is judged that the rail is broken to the rail waist; or,

[0114] When the correlation coefficient is greater than 0.4 and less than or equal to 0.6, it is judged that the rail is broken to the rail head; or,

[0115] When the correlation coefficient is greater than 0.6 and less than or equal to 1, the rail is judged to be intact.

[0116] Further,

[0117] The present invention also provides a rail online detection system, such as Figure 7 As shown, a schematic diagram of the structure of the rail online detection system is shown, and the system includes:

[0118] Sensor, filter (not shown in the figure, the filter is in the receiver) and receiver;

[0119] The sensor is used to collect the original signal;

[0120] The filter is used to filter the original signal;

[0121] The receiver is used to perform Fourier transform on the filtered signal to obtain a first modulus value;

[0122] The receiver is used to generate a sinusoidal reference signal according to the frequency corresponding to the maximum value of the spectrum energy after Fourier transformation, and perform Fourier transformation on the sinusoidal reference signal to obtain a second modulus value;

[0123] The receiver is used to obtain a correlation coefficient based on the first modulus value and the second modulus value;

[0124] The receiver is used to judge the health status of the rail based on the correlation coefficient.

[0125] Specifically, the receiver is used to judge that the rail is completely broken when the correlation coefficient is not greater than a first threshold value; or, when the correlation coefficient is greater than the first threshold value but not greater than the second threshold value, to judge that the rail is broken to the rail waist; or, when the correlation coefficient is greater than the second threshold value but not greater than the third threshold value, to judge that the rail is broken to the rail head; or, when the correlation coefficient is greater than the third threshold value but not greater than the fourth threshold value, to judge that the rail is intact.

[0126] The receiver is used to filter the length N signal x 1_filtered (n) Perform N-point Fourier transform to obtain X1(k):

[0127]

[0128] Wherein, N=4096, k=0,1,…,N-1; n=0,1,…,N-1;

[0129] Calculate the first modulus value X after Fourier transformation 1_abs (k):

[0130]

[0131] Where a1(k) is the real part of X1(k), and b1(k) is the imaginary part of X1(k).

[0132] The receiver is used to calculate the second modulus value. The specific calculation method is:

[0133] Performing Fourier transform on the filtered signal;

[0134] Calculate the frequency f corresponding to the maximum value of the spectrum energy after Fourier transformation;

[0135] Generate a sinusoidal reference signal x2(n) according to the frequency f, and perform N-point Fourier transform on the sinusoidal reference signal to obtain X2(k):

[0136]

[0137] Wherein, N=4096, k=0,1,…,N-1; n=0,1,…,N-1;

[0138] Calculate the second modulus value X after Fourier transformation 2_abs (k):

[0139]

[0140] Where a2(k) is the real part of X2(k) and b2(k) is the imaginary part of X2(k).

[0141] The receiver is used to obtain the correlation coefficient based on the first modulus value and the second modulus value. The specific calculation method is:

[0142]

[0143] Among them, ρ(X 1_abs (k),X 2_abs (k)) represents the first modulus value X 1_abs (k) and the second modulus value X 2_abs (k), N is the length of the module value, μ1 and μ2 are the first module value X 1_abs (k) and the second modulus value X 2_abs The mean of (k), X 1_abs (k) is the first modulus value of the kth data, X 2_abs (k) is the second modulus value of the kth data.

[0144] The system also includes: a transmitter, a transducer, a data transmission module, a display terminal and a power supply module. The original signal is generated by an electrical signal sent by the transmitter;

[0145] The transducer is used to convert the original signal (electrical signal) sent by the transmitter into an acoustic signal and couple it to the rail in the switch area;

[0146] Data transmission module: used to transmit the correlation coefficient calculated in the receiver to the display terminal;

[0147] Display terminal: displays the correlation coefficient data in the data transmission module, and then judges the health status of the rail according to the correlation coefficient;

[0148] Power supply module: used to supply power to the receiver, transmitter, transducer, filter, sensor, data transmission module and display terminal in the system.

[0149] That is, the transmitter is used to send out the original electrical signal, and convert the original electrical signal into an acoustic signal through the transducer and couple it to the turnout rail. After the acoustic signal is transmitted in the rail, it is received by the sensor installed at the tip of the turnout rail, and then high-pass filtered by the Chebyshev filter. In the receiver, the filtered signal is Fourier transformed and the first modulus value after Fourier transformation is calculated. A single-frequency reference signal is generated according to the frequency corresponding to the maximum value of the spectrum energy. The reference signal is Fourier transformed to obtain the second modulus value of the reference signal. The correlation coefficient is calculated based on the first modulus value and the second modulus value, and the health status of the rail is judged according to the correlation coefficient.

[0150] The specific working principle of the rail online detection method and system of the present invention is as follows:

[0151] Due to changes in external environmental factors such as temperature, the rail density, Young's modulus, elastic modulus and other factors will be affected, thereby affecting the acoustic impedance of the transducer and rail coupling surface and the propagation performance of sound waves in the rail, which ultimately causes the acoustic signal energy coupled to the rail to fluctuate and the frequency to shift. The spectrum-correlated switch area rail health status monitoring method based on frequency tracking proposed in this patent can effectively solve the above problems. This algorithm calculates the frequency corresponding to the maximum value of the received signal spectrum and generates a sinusoidal reference signal of the frequency value, and monitors the health status of the rail by calculating the correlation coefficient of the original signal spectrum and the sinusoidal reference signal spectrum. When cracks occur in the rail, the sound wave will be dispersed after passing through the crack, resulting in more components of the sound wave energy at other frequencies. At this time, when the correlation coefficient is calculated with the spectrum of the single-frequency sinusoidal reference signal, the value of the correlation coefficient will decrease. Through a large number of experiments, it is found that the larger the crack in the rail, the more severe the dispersion and the lower the correlation coefficient.

[0152] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A rail online detection method, characterized in that: The method comprises: Collecting and filtering the original signal, wherein the original signal is generated by an electrical signal sent by a transmitter, the original signal is converted into an acoustic signal by a transducer and coupled to the rail, and the acoustic signal of the rail tip and the waist of the turnout area rail is collected by a sensor; Performing Fourier transform on the filtered signal to obtain a first modulus value; The specific calculation method of performing Fourier transform on the filtered signal to obtain the first modulus value is: For the filtered signal x 1_filtered (n) Perform Fourier transform to obtain X1(k); Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value; Calculate the first modulus value X of the filtered signal after Fourier transformation 1_abs (k): Where a1(k) is the real part of X1(k), and b1(k) is the imaginary part of X1(k); Generate a sinusoidal reference signal according to the frequency corresponding to the maximum value of the spectrum energy after Fourier transformation, and perform Fourier transformation on the sinusoidal reference signal to obtain a second modulus value; The specific calculation method of the second modulus value is: Performing Fourier transform on the filtered signal; Calculate the frequency f corresponding to the maximum value of the spectrum energy of the filtered signal after Fourier transformation; A sinusoidal reference signal x2(n) is generated according to the frequency f, and the sinusoidal reference signal is subjected to Fourier transformation to obtain X2(k): Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value; Calculate the second modulus value X after Fourier transformation 2_abs (k): Where a2(k) is the real part of X2(k), and b2(k) is the imaginary part of X2(k); Calculate a correlation coefficient based on the first modulus value and the second modulus value; The specific calculation method for obtaining the correlation coefficient based on the first modulus value and the second modulus value is: Among them, ρ(X 1_abs (k),X 2_abs (k)) represents the first modulus value X 1_abs (k) and the second modulus value X 2_abs (k), N is the length of the module value, μ1 and μ2 are the first module value X 1_abs (k) and the second modulus value X 2_abs The mean of (k), X 1_abs (k) is the first modulus value of the kth data, X 2_abs (k) is the second modulus value of the kth data; The health status of the rail is detected based on the correlation coefficient.

2. The rail online detection method according to claim 1, characterized in that: When the correlation coefficient is not greater than the first threshold, it is determined that the rail is completely broken; or, When the correlation coefficient is greater than the first threshold value and not greater than the second threshold value, it is determined that the rail is broken to the rail waist; or, When the correlation coefficient is greater than the second threshold value and not greater than the third threshold value, it is determined that the rail is broken to the rail head; or, When the correlation coefficient is greater than the third threshold value and not greater than the fourth threshold value, it is determined that the rail is intact.

3. A rail online detection system, characterized in that: The system comprises: The system includes a sensor, a filter, and a receiver; The sensor is used to collect the original signal, wherein the original signal is generated by the electrical signal sent by the transmitter, the original signal is converted into an acoustic signal by the transducer and coupled to the rail, and the acoustic signal of the rail tip and the waist of the turnout area rail is collected by the sensor; The filter is used to filter the original signal; The receiver is used to perform Fourier transform on the filtered signal to obtain a first modulus value; The receiver is used to filter the signal x of length N 1_filtered (n) Perform N-point Fourier transform to obtain X1(k); Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value; Calculate the first modulus value X after Fourier transformation 1_abs (k): Where a1(k) is the real part of X1(k), and b1(k) is the imaginary part of X1(k); The receiver is used to generate a sinusoidal reference signal according to the frequency corresponding to the maximum value of the spectrum energy of the filtered signal after Fourier transformation, and perform Fourier transformation on the sinusoidal reference signal to obtain a second modulus value; The receiver is used to calculate the second modulus value, and the specific calculation includes: Performing Fourier transform on the filtered signal; Calculate the frequency f corresponding to the maximum value of the spectrum energy after Fourier transformation; A sinusoidal reference signal x2(n) with a length of N points is generated according to the frequency f, and an N-point Fourier transform is performed on the sinusoidal reference signal to obtain X2(k): Wherein, k=0,1,…,N-1; n=0,1,…,N-1, N is a predetermined value; Calculate the second modulus value X after Fourier transformation 2_abs (k): Where a2(k) is the real part of X2(k), and b2(k) is the imaginary part of X2(k); The receiver is used to obtain a correlation coefficient based on the first modulus value and the second modulus value; The receiver is used to calculate a correlation coefficient based on the first modulus value and the second modulus value, and the specific calculation includes: Among them, ρ(X 1_abs (k),X 2_abs (k)) represents the first modulus value X 1_abs (k) and the second modulus value X 2_abs (k), N is the length of the module value, μ1 and μ2 are the first module value X 1_abs (k) and the second modulus value X 2_abs The mean of (k), X 1_abs (k) is the first modulus value of the kth data, X 2_abs (k) is the second modulus value of the kth data; The receiver is used to detect the health status of the rail based on the correlation coefficient.

4. The rail online detection system according to claim 3, characterized in that: The receiver is used to judge that the rail is completely broken when the correlation coefficient is not greater than a first threshold; or, When the correlation coefficient is greater than the first threshold value and not greater than the second threshold value, it is determined that the rail is broken to the rail waist; or, When the correlation coefficient is greater than the second threshold value and not greater than the third threshold value, it is determined that the rail is broken to the rail head; or, When the correlation coefficient is greater than the third threshold value and not greater than the fourth threshold value, it is determined that the rail is intact.

Images