Track circuit signal anomaly detection method and device

Abstract

The invention discloses a track circuit signal anomaly detection method and device. The method comprises the following steps: periodically collecting original waveform array data of a track circuit signal; acquiring time domain index data and frequency domain index data corresponding to the acquisition time based on the original waveform array data of the track circuit signal acquired at each acquisition time; restoring the track circuit signal according to the time domain index data and the frequency domain index data corresponding to the plurality of acquisition moments; and determining whether abnormity exists or not according to the restored track circuit signal. According to the scheme, early warning can be carried out in the early stage of track circuit signal abnormity, troubleshooting and solving are carried out in the early stage, and therefore train operation safety and operation efficiency are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to, but are not limited to, the field of rail transit technology, and in particular, to a method and device for detecting abnormal track circuit signals. Background Art

[0002] The train operation control system, abbreviated as the train control system, is the key to ensuring the safe and efficient operation of trains. As one of its basic equipment, the track circuit system is responsible for detecting whether the track is broken or occupied, and transmitting coded sequence information, such as the idle state of the front section, to the train through the track circuit signal, so as to ensure the safe and stable operation of the train control system.

[0003] Currently, the main problem faced by the track circuit system is the abnormal signal transmission that may occur during the train operation. This situation will cause the ATP system (Automatic Train Protection) to misjudge it as a code dropout and trigger braking, thus affecting the operation efficiency and passenger experience. In addition, since these signal abnormalities are usually sporadic and change as the train moves, it is difficult for ground maintenance personnel to detect potential problems during routine inspections. Therefore, how to accurately diagnose and locate such signal abnormalities has become one of the current technical challenges. Summary of the Invention

[0004] The following is an overview of the subject matter described in detail in this article. This overview is not intended to limit the scope of protection of the claims.

[0005] The embodiments of the present application provide a method and device for detecting abnormal track circuit signals, which can accurately diagnose and locate abnormal signals in the track circuit signals.

[0006] An embodiment of the present application provides a method for detecting abnormal track circuit signals, including: periodically collecting the original waveform array data of the track circuit signal; respectively obtaining the time-domain index data and frequency-domain index data corresponding to the collection moment based on the original waveform array data of the track circuit signal collected at each collection moment; restoring the track circuit signal according to the time-domain index data and frequency-domain index data corresponding to multiple collection moments; and determining whether there is an abnormality according to the restored track circuit signal.

[0007] An embodiment of the present application further provides a device for detecting abnormal track circuit signals, including: a memory and a processor; the memory is used to store a program for detecting abnormal track circuit signals; the processor is used to read the program for detecting abnormal track circuit signals and execute the method for detecting abnormal track circuit signals according to any embodiment of the present application.

[0008] Compared with the related technologies, a method and a device for detecting abnormal track circuit signals provided by the embodiments of the present application obtain time-domain index data and frequency-domain index data based on the original waveform array data of the collected track circuit signals, and then restore the track circuit signals according to the time-domain index data and the frequency-domain index data. Then, the restored track circuit signals are analyzed to determine whether there is an abnormality, so that early warning can be carried out in the early stage of abnormal track circuit signals, and early investigation and solution can be carried out, thereby improving the train operation safety and operation efficiency. Through this solution, the problem that it is difficult to locate signal abnormalities during the train operation in the prior art is also indirectly solved.

[0009] Other features and advantages of the present application will be described in the subsequent specification, and, in part, will become obvious from the specification, or will be understood by implementing the present application. Other advantages of the present application can be realized and obtained through the solutions described in the specification and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The drawings are used to provide an understanding of the technical solutions of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solutions of the present application, and do not constitute a limitation to the technical solutions of the present application.

[0011] Figure 1 It is a brief flowchart of the method for detecting abnormal track circuit signals in the embodiments of the present application; Figure 2 It is a schematic diagram of the train track circuit signal receiving process in the related technology; Figure 3 It is a flowchart of the method for detecting abnormal track circuit signals in the embodiments of the present application; Figure 4a and Figure 4b It is a schematic diagram of the data relationship of the time-domain frequency data array in the embodiments of the present application; Figure 5a and Figure 5b It is a schematic diagram of the ground original waveform signal to the original waveform array information in the embodiments of the present application; Figure 5c It is a schematic diagram of the zero-crossing position in the original waveform array information in the embodiments of the present application; Figure 6 It is a schematic diagram of the device for detecting abnormal track circuit signals in the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] This application describes multiple embodiments, but the description is exemplary rather than restrictive, and it will be apparent to those of ordinary skill in the art that there can be more embodiments and implementation solutions within the scope encompassed by the embodiments described in this application. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically restricted, any feature or element of any embodiment can be used in combination with any other feature or element in any other embodiment, or can replace any other feature or element in any other embodiment.

[0013] This application includes and contemplates combinations with features and elements known to those of ordinary skill in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form unique inventive solutions. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented alone or in any suitable combination. Therefore, the embodiments are not subject to other limitations except those imposed by the appended claims and their equivalents. In addition, various modifications and changes can be made within the scope of the appended claims.

[0014] Furthermore, in describing representative embodiments, the specification may have presented the method and / or process as a particular sequence of steps. However, to the extent that the method or process does not depend on the particular sequence of steps described herein, the method or process should not be limited to the particular sequence of steps described. As will be understood by those of ordinary skill in the art, other sequences of steps are possible. Therefore, the particular sequence of steps set forth in the specification should not be construed as a limitation on the claims. In addition, the claims directed to the method and / or process should not be limited to performing their steps in the order written, and those skilled in the art can readily understand that these orders can vary and still remain within the spirit and scope of the embodiments of this application.

[0015] In current technology, the status analysis of ground track circuit equipment is usually carried out after the fact (after the fact, it means that someone will go to investigate after there is a problem with the train operation, such as after the train has a code loss and braking), and the detection means are limited (usually only static means can be used to detect the transmission of track circuit signals. Static means refer to "maintenance personnel use detection equipment to conduct relatively stable tests on the on-site track when there is no train running. Rather than testing the environment in which the train is running and the environmental conditions are constantly changing with the movement of the train"). However, the abnormalities in the track circuit signals received by the train are often instantaneous and dynamic. It is difficult to judge the real-time track circuit signal abnormalities based on existing technical means, and it is difficult to eliminate occasional hidden faults, resulting in similar faults occurring multiple times, affecting the train operation efficiency and increasing maintenance costs.

[0016] To this end, an embodiment of the present application provides a method for detecting abnormality of a track circuit signal, such as Figure 1 As shown, the following steps may be included: Step S110: periodically collecting original waveform array data of track circuit signals; Step S120: acquiring time domain index data and frequency domain index data corresponding to each acquisition moment based on the original waveform array data of the track circuit signal acquired at each acquisition moment; Step S130: restoring the track circuit signal according to the time domain index data and the frequency domain index data corresponding to the multiple acquisition moments; Step S140: Determine whether there is an abnormality based on the restored track circuit signal.

[0017] The track circuit signal anomaly detection method of this embodiment can obtain time domain index data and frequency domain index data based on the original waveform array data of the collected track circuit signal, and then restore the track circuit signal according to the time domain index data and the frequency domain index data, and then analyze and determine whether there is an abnormality based on the restored track circuit signal, so that early warning, early investigation and resolution of track circuit signal abnormality can be carried out, thereby improving the safety and efficiency of train operation. Through this solution, the problem of difficulty in locating signal abnormalities during train operation in the prior art is also solved in disguise.

[0018] In an exemplary embodiment, the time domain indicator data includes a low frequency deviation and a carrier frequency deviation; obtaining the time domain indicator data corresponding to the acquisition time includes: According to the original waveform array data and the signal sampling frequency at the acquisition moment, a time domain frequency data array is obtained; Acquire an actual low frequency value based on the time domain frequency data array, and acquire the low frequency deviation according to the actual low frequency value; Obtain the carrier frequency offset based on the time-domain frequency data array and the actual low-frequency frequency value.

[0019] Exemplarily, the time-domain frequency data array includes upper and lower sideband frequency values. For example, if the carrier frequency is 2000 Hz and the upper and lower sideband frequency offsets are 11 Hz, that is, the signal frequencies in the original signal are the lower sideband 1989 Hz and the upper sideband 2011 Hz. If the low frequency is 5 Hz, then in the 1-second original signal, 1989 Hz and 2011 Hz will switch 5 times (that is, the time for each sideband to appear is 0.1 second). Therefore, in the case of no interference, the "time-domain frequency array data" obtained is that 1989 Hz and 2011 Hz appear alternately, and the appearance time for each time is 0.1 second.

[0020] The abnormal detection method of the track circuit signal in this embodiment analyzes the time-domain data, analyzes the carrier frequency offset in the track circuit signal data based on the time-domain frequency data array of the signal, and discovers performance changes caused by equipment aging and the like in a timely manner by monitoring the carrier frequency offset, performs maintenance as early as possible, improves the equipment maintenance efficiency, and thus improves the train operation efficiency.

[0021] In an example of this embodiment, based on the original waveform array data and the signal sampling frequency at the acquisition moment, obtain the time-domain frequency data array, including: Perform DC removal processing on the original waveform array data to obtain DC-removed waveform array data; Calculate the zero-crossing information based on the DC-removed waveform array data, and obtain the sampling interval information between zero-crossings according to the zero-crossing information; Calculate the frequency value of the signal at each moment in the time period corresponding to the original waveform array data according to the sampling interval information and the signal sampling frequency, and generate the time-domain frequency data array according to the frequency value of the signal at each moment.

[0022] Exemplarily, the sampling interval information may include: the time interval between the first zero-crossing and the first sampling point in the current carrier frequency period, the time interval between the first sampling point and the last sampling point in the current carrier frequency period, and the time interval between the last sampling point and the second zero-crossing in the current carrier frequency period. For a clearer understanding of the implementation of this example, reference can be made to the relevant examples in the following text Figures 5a - 5c of this document.

[0023] In an example of this embodiment, based on the time-domain frequency data array, obtain the actual low-frequency frequency value, and obtain the low-frequency offset according to the actual low-frequency frequency value, including: Perform spectrum analysis on the time-domain frequency data array to obtain the low-frequency change frequency; The highest energy point frequency is obtained by the method of extreme value selection, and the highest energy point frequency is used as the actual low-frequency frequency value; The difference between the actual low-frequency frequency value and the preset standard low-frequency frequency value is used as the low-frequency frequency deviation.

[0024] In an example of this embodiment, based on the time-domain frequency data array and the actual low-frequency frequency value, obtaining the carrier frequency deviation includes: Determine the corresponding period length according to the actual low-frequency frequency value, select data points of an integer number of periods in the time-domain frequency data array for arithmetic averaging, and calculate the actual carrier frequency value; The deviation between the actual carrier frequency value and the preset carrier center value is used as the carrier frequency deviation.

[0025] Exemplarily, the preset carrier center value can be a standard carrier frequency value selected manually or set according to experience.

[0026] It should be noted that in this embodiment, selecting data points of an integer number of periods for arithmetic averaging can avoid the problem of "because the upper and lower side frequencies change with different low-frequency values, using a fixed number of frequency values to calculate the carrier frequency average will cause errors", improving the accuracy of the calculated actual carrier frequency value.

[0027] In the related art, in the normal maintenance of ground track circuit equipment, attention is often only paid to the signal acquisition data at the output position of the signal machine and the current information at the outlet of the code sender, and the performance changes brought about by equipment aging, resulting in poor monitoring of the low-frequency frequency and carrier frequency. The track circuit signal anomaly detection method of this embodiment analyzes the time-domain data, based on the time-domain frequency data array of the signal, analyzes the low-frequency frequency deviation and carrier frequency deviation in the track circuit signal data, and discovers performance changes caused by equipment aging and the like in time by monitoring the low-frequency frequency deviation and carrier frequency deviation, and performs maintenance as early as possible to improve the equipment maintenance efficiency, thereby improving the train operation efficiency.

[0028] In an exemplary embodiment, the frequency-domain index data includes signal-to-noise ratio and root mean square current; obtaining the frequency-domain index data corresponding to the acquisition moment includes: According to the original waveform array data and the signal sampling frequency, obtain the energy values of each frequency band; the energy of each frequency band includes the energy value of the valid signal and the energy value of the invalid signal; Calculate the signal-to-noise ratio according to the energy value of the valid signal and the energy value of the invalid signal.

[0029] Exemplarily, the method further includes performing targeted calculations for preset frequency band interference situations; for example, targeted calculations can be performed for interference in common specific frequency bands. Exemplarily, after performing targeted calculations for preset frequency band interference situations, it can further include analyzing according to the calculation results to determine whether there is an abnormality and the cause of the abnormality.

[0030] The abnormal detection method of the track circuit signal in this embodiment analyzes the frequency domain data, based on the frequency spectrum information of the signal, analyzes the energy distribution ratio of the effective signal and the invalid signal in the track circuit signal data, can determine whether there is clutter interference, and gives an early warning in time, enabling equipment maintenance personnel to promptly check the reasons and perform maintenance, reducing the occurrence of accidents, and improving the safety of train operation.

[0031] In an example of this embodiment, obtaining the frequency domain index data corresponding to the acquisition moment further includes: According to the energy value and the hardware characteristic parameters of the signal transmission link, calculate the effective current value of the track circuit signal, and the hardware characteristic parameters of the signal transmission link include the receiving coil height, impedance, and circuit amplification factor.

[0032] Among them, the effective current value of the track circuit signal refers to the effective current value of the rail return current of the track circuit.

[0033] The abnormal detection method of the track circuit signal in this example analyzes the frequency domain data, based on the effective signal energy value and the hardware characteristic parameters of the signal transmission link, converts the signal energy value into the effective current value of the rail return current of the track circuit, thereby determining whether the ground coding device is in a normal working state, and giving a reminder in time when there is an abnormality, so as to perform maintenance as early as possible, thereby improving the safety and operation efficiency of train operation.

[0034] In an exemplary embodiment, determining whether there is an abnormality according to the restored track circuit signal includes: Determine the values of the abnormal evaluation parameters corresponding to the multiple acquisition moments according to the restored track circuit signal, and the abnormal evaluation parameters are one or more signal parameters set in advance; Judge whether the values of the abnormal evaluation parameters meet the preset standards; and / or, judge whether the track circuit signal is continuously unstable. Continuously unstable means that the values of any one or more of the abnormal evaluation parameters corresponding to multiple consecutive acquisition moments do not meet the preset standards, and the duration of the first time period composed of these multiple consecutive acquisition moments exceeds the preset timeout duration corresponding to the abnormal evaluation parameter; According to the acquisition moments corresponding to the values of the abnormal evaluation parameters that do not meet the preset standards, determine the abnormal time point and position point of the track circuit; and / or, according to the first time period, determine the abnormal time period and position segment of the track circuit.

[0035] In an example of this embodiment, the abnormal evaluation parameters include the effective value of current, signal-to-noise ratio, carrier frequency offset, and low-frequency offset; determining whether the values of the abnormal evaluation parameters of the track circuit signal meet the preset standards includes: For each moment within the time period corresponding to the original waveform array data, perform one or more of the following operations: Determine whether the effective value of the current of the track circuit signal at this moment is lower than the preset minimum effective value of current; Determine whether the value of the signal-to-noise ratio of the track circuit signal at this moment is lower than the preset minimum signal-to-noise ratio value; Determine whether the absolute value of the carrier frequency offset of the track circuit signal at this moment is lower than the preset maximum carrier frequency offset value; Determine whether the absolute value of the low-frequency offset of the track circuit signal at this moment is lower than the preset maximum low-frequency offset value.

[0036] The method for detecting abnormal track circuit signals in this embodiment can analyze whether the track circuit signal is abnormal by analyzing abnormal evaluation parameters such as the effective value of current, signal-to-noise ratio, carrier frequency offset, and low-frequency offset, and then diagnose whether there is an abnormality in the track circuit. When an abnormality occurs, it can timely remind the staff to carry out maintenance and repair, eliminate occasional hidden equipment fault points, and reduce the maintenance cost; on the other hand, it also reduces the probability of substantial failures occurring during train operation, improves the operation safety and operation efficiency of the train, and enhances the passenger experience.

[0037] In an exemplary embodiment, the acquisition of the original waveform array data of the track circuit signal includes: Obtain the track circuit signal through an on-vehicle receiving coil, and after signal conditioning and analog-to-digital conversion, obtain the original waveform array data of the track circuit signal at a signal sampling frequency that is more than twice the highest frequency of the signal.

[0038] In summary, the method for detecting abnormal track circuit signals in this embodiment is based on the original waveform array data of the track circuit signal collected by the train, restores the track circuit signal (which can also be called the original track signal data) at the train operation moment through time-domain and frequency-domain indicators, and then can determine possible problems with the track circuit signal received during train operation based on the original track signal data for the reference of ground maintenance personnel, and timely check and maintain the ground track circuit equipment or on-vehicle equipment, thereby reducing the probability of failures, enhancing the passenger experience, and solving the problem in the prior art that it is difficult to locate the cause of signal abnormalities during train operation.

[0039] The following uses an embodiment to elaborate in detail on the method for detecting abnormal track circuit signals of the present application, which can be referred to Figure 2 and Figure 3 .

[0040] As Figure 2 shown Figure 2 in the figure, it is a schematic diagram of the train track circuit signal receiving process. The ground equipment continuously sends track circuit information through the rail. When the wheelset of the train presses on the track circuit section, the rail and the wheelset of the train form a current-conducting loop, and a track circuit signal (i.e., the Figure 2 original signal in the figure) is formed on the rail; the track circuit signal is an AC signal. According to the principle of electromagnetic induction, the train can obtain the induced voltage differential signal of this signal through the track circuit signal receiving coil installed in front of the wheelset; subsequently, the track circuit signal acquisition device installed after this signal can capture the original signal waveform array and store it in the storage medium; then, the analysis software can conduct in-depth analysis on the track circuit signal received by the train for this original signal waveform array.

[0041] As Figure 3 shown, the track circuit signal anomaly detection method may include the following steps: Step S310: Through the receiving coil installed on the train, after signal processing and the AD acquisition device, obtain the original waveform array data of the track circuit signal at a sampling rate exceeding 2 times the highest frequency of the signal, and store the obtained original waveform array data in the storage medium.

[0042] Among them, the receiving coil is located in the TCR antenna (Track Circuit Reader Antenna); the original waveform array data (which can also be called the track circuit signal waveform array) represents the sampling value sequence obtained by performing AD conversion on the induced voltage obtained by the track circuit signal receiving coil installed on the train at a set signal sampling frequency.

[0043] Exemplarily, the storage method includes but is not limited to: storing in a local storage medium (such as a CF card, hard disk, USB flash drive, etc.), storing at the server location.

[0044] Step S320: Based on the original waveform array data of the track circuit signal collected at each acquisition moment respectively, obtain the time-domain index data and frequency-domain index data corresponding to this acquisition moment. The time-domain index data includes low-frequency frequency deviation and carrier frequency deviation, and the frequency-domain index data includes signal-to-noise ratio and current effective value.

[0045] Exemplarily, the time-domain and frequency-domain analysis of the original waveform array data can be performed through online or offline data analysis software to obtain the time-domain index data and frequency-domain index data of the track circuit signal and restore the track circuit signal data.

[0046] Among them, exemplarily, the time-domain index data can be obtained through the following steps S3211 to S3213: Step S3211: Obtain a time-domain frequency data array according to the original waveform array data and the signal sampling frequency; wherein, the time-domain frequency data array represents a sequence set of the original signal carrier frequencies.

[0047] Exemplarily, since the track circuit signal is in the FSK modulation mode, this means that the ground signal uses a certain carrier frequency as the center frequency, obtains upper and lower side frequencies with a fixed frequency deviation, and the upper and lower side frequencies alternate at a specific low frequency. Taking the 1700-1 carrier frequency of the ZPW2000 system as an example, the center frequency is 1701.4 Hz, the frequency deviation is 11 Hz, so the upper side frequency is 1712.4 Hz, and the lower side frequency is 1690.4 Hz; in this example, theoretically, the time-domain frequency array should be an array composed of two side frequency values of 1712.4 and 1690.4, and the upper and lower side frequencies in the array change at a certain low frequency.

[0048] Step S3212: Obtain the actual low-frequency value based on the time-domain frequency data array, and obtain the low-frequency deviation according to the actual low-frequency value.

[0049] Exemplarily, the low-frequency deviation can be obtained in the following way: Obtain power spectrum information, frequency amplitude information, etc. using methods such as Paseval and Fourier Transform, and obtain the current low-frequency information by taking the highest value; calculate the difference between the calculated low-frequency information and the low-frequency value required by the standard to obtain the low-frequency deviation.

[0050] Exemplarily, this step S3212 may include: Analyze the time-domain frequency data array using the Discrete Fourier Transform method to obtain low-frequency distribution parameters and calculate the low-frequency deviation; wherein, the spectrum analysis of the time-domain frequency data array can obtain the change frequency of the low frequency, and the low-frequency information (i.e., the actual low-frequency value) of the track circuit signal in the data can be obtained by the method of extreme value selection, and compare the actual low-frequency value with the closest low frequency corresponding to the system in the specification requirements to obtain the low-frequency deviation. For example, there are 18 fixed low-frequency codes for track circuit signals in the specification. If the specification stipulates that the low frequency of the L3 code is 10.3 Hz, and the calculated low-frequency value is 10.35 Hz, then it means the low-frequency deviation is 0.05 Hz.

[0051] Step S3213: Obtain the carrier frequency deviation based on the time-domain frequency data array and the actual low-frequency value.

[0052] Exemplarily, the carrier frequency offset can be obtained in the following manner: according to the current low-frequency information, in accordance with the period corresponding to the low frequency, obtain different numbers of time-domain frequency data arrays for corresponding n periods, and calculate their mean value as the actual carrier frequency value; calculate the difference between the calculated actual carrier frequency value and the standard carrier frequency value (also known as the preset carrier center value) to obtain the carrier frequency offset. For example, take n numbers in the time-domain frequency array and calculate the average value f mean = (f1 + f2 + …… + f n ) / n, then the carrier frequency offset = (f mean - standard carrier frequency value). Among them, the period is stipulated in the specification. Only specific low-frequency periods of the track circuit signal are valid. The length of the period is calculated based on the low-frequency value and can refer to TB / T 3287.

[0053] Among them, exemplarily, the frequency-domain index data can be obtained through the following steps S3221 to step S3222: Step S3221: According to the original waveform array data and the signal sampling frequency, obtain the energy values of each frequency band; the energy of each frequency band includes the energy value of the valid signal and the energy value of the invalid signal; calculate the signal-to-noise ratio according to the energy value of the valid signal and the energy value of the invalid signal.

[0054] Exemplarily, step S3221 may include: the computing device uses online or offline software to perform frequency-domain analysis on the waveform array data using the Paseval method, obtain the energy distribution of the valid signal and the interference signal, and obtain the signal-to-noise ratio parameter. Among them, the computing device can be a host computer or software running on an embedded device; the software performs frequency spectrum operations on the original waveform array data of the track circuit signal to obtain the energy values of each frequency band; the software should combine the train operation situation or can be manually set according to the user to determine the frequency band range of the current valid signal to calculate the energy value of the valid signal and the energy value of the invalid signal, so as to calculate the signal-to-noise ratio.

[0055] Exemplarily, the valid signal and the invalid signal can be distinguished in the following manner: the valid frequency band has been clearly defined in the ground design specification. Among each frequency band, 500Hz, 600Hz, 700Hz, 800Hz, 900Hz, 1700Hz, 2000Hz, 2300Hz, 2600Hz can be valid signal frequency points, and other frequencies are always invalid signal frequency points.

[0056] Exemplarily, the signal-to-noise ratio can be calculated as follows: Find the frequency point with the highest energy among 500 Hz, 600 Hz, 700 Hz, 800 Hz, 900 Hz, 1700 Hz, 2000 Hz, 2300 Hz, and 2600 Hz as the effective signal. All frequencies other than the one with the highest energy are noise. Find the frequency point with the highest energy in the noise, and then divide them to obtain the signal-to-noise ratio.

[0057] It should be noted that for common interference frequency bands (such as power frequency and odd harmonic frequencies of power frequency), the relative energy value can be calculated separately to guide whether there is power frequency interference in traction return current, etc.

[0058] Step S3222: Calculate the effective current value of the track circuit signal according to the energy value and the hardware characteristic parameters of the signal transmission link. The hardware characteristic parameters of the signal transmission link include the height of the receiving coil, impedance, and circuit amplification factor.

[0059] Exemplarily, the energy value is in direct proportion to the square of the effective current value, and the coefficient is fixed. This coefficient is jointly determined by parameters such as the height of the receiving coil (type of receiving coil, height of the train-mounted antenna), impedance, and circuit amplification factor. In the case of the same vehicle type, the same antenna model, and fixed hardware, this proportional coefficient can be preset as a fixed value, which can be a preset value obtained through actual measurement. It should be noted that this proportional coefficient can also be manually adjusted according to changes in the receiving coil parameters, antenna installation errors, etc.

[0060] For this step S320, online or offline software can be used to perform time-domain and frequency-domain analysis on the waveform array data, restore information such as the effective current value, signal-to-noise ratio, carrier frequency offset, and low-frequency frequency offset of the track circuit signal at the operating moment, and then restore the track circuit signal data according to parameters such as the effective current in the rail and frequency offset.

[0061] Step S330: Restore the track circuit signal according to the time-domain index data and frequency-domain index data corresponding to multiple acquisition moments.

[0062] Step S340: Evaluate the ground track circuit condition according to the restored track circuit signal, and obtain the abnormal time point and position point of the track circuit condition.

[0063] Exemplarily, this step S340 can judge that the received track circuit signal is abnormal in the following ways: Judge that the effective current value of the track circuit signal at a certain moment is insufficient; Judge that the signal-to-noise ratio of the track circuit signal at a certain moment is too low; Judge that there is a frequency deviation in the carrier frequency of the track circuit signal at a certain moment; Judge that there is a frequency deviation in the low frequency of the track circuit signal at a certain moment; It is determined that the track circuit signal is continuously unstable during a certain period of time. Herein, "continuously unstable" means that one or more of the following conditions continuously occur: the effective value of the current is insufficient, the signal-to-noise ratio is too low, there is a frequency deviation in the carrier frequency, and there is a frequency deviation in the low frequency, and the duration reaches a preset duration threshold, and the preset duration threshold can be 1.5 s.

[0064] In this step S340, the moment when the track circuit signal is abnormal can be determined, and then, in combination with the operation data of the train, the position passed by the train at the abnormal moment can be determined. Exemplarily, the operation data of the train may include the departure and arrival times of the train, and the corresponding relationship between the time and the passed position during the operation process. For any moment, the passed position corresponding to the moment can be obtained through the corresponding relationship between the time and the passed position.

[0065] The method for detecting abnormal track circuit signals in this embodiment collects track circuit signals in real time through a receiving coil on the train, obtains an original waveform array data at a sampling rate exceeding twice the highest frequency of the signal, and stores these data in a storage medium; subsequently, online or offline data analysis software can be used to perform time-domain and frequency-domain analysis on the original waveform array data to obtain time-domain index data and frequency-domain index data of the track circuit signal, so as to realize the restoration of the track circuit signal; then, through comprehensive analysis of the restored data, the situation of the ground track circuit can be evaluated, and the time point and position point where the abnormality occurs can be determined. This solution can improve the recognition accuracy of the abnormal state of the track circuit signal, enhance the work efficiency of maintenance personnel, and further reduce the unplanned stop of the train caused by signal abnormalities, and improve the operation efficiency of the train and the riding experience of passengers.

[0066] It should be noted that the method for detecting abnormal track circuit signals in this embodiment is executed in real time by a specific computing device installed on the train, or data for a specific period can be obtained afterwards and executed by other computing devices.

[0067] In an exemplary embodiment, Figure 4a and Figure 4b is a schematic diagram of the data relationship of the time-domain frequency data array obtained by converting the original waveform data: As Figure 4a shown, waveform (a) represents the original information of the track circuit signal data, and the modulation method is FSK; the abscissa t in the figure represents time, and the ordinate u(t) represents the current value amplitude. f0 represents the carrier frequency center frequency, Δf represents the frequency deviation, so the lower sideband frequency is f0 - Δf, the upper sideband frequency is f0 + Δf, and the upper and lower sidebands change at the frequency of the modulated low frequency, and the period of the low frequency is Δt.

[0068] As Figure 4bAs shown, waveform (b) represents the theoretical value change waveform of the time-domain frequency data array; the abscissa t in the figure represents time, and the ordinate f(t) represents the frequency value. Theoretically, the time-domain frequency data array should be an array composed of the lower sideband frequency f0 - Δf and the upper sideband frequency f0 + Δf, and the changing frequency is the low-frequency period Δt.

[0069] In an exemplary embodiment, Figure 5a and Figure 5b are schematic diagrams of the ground original waveform signal to the original waveform array information, Figure 5c Schematic diagram of the zero-crossing position in the original waveform array information: Figure 5a The ordinate u(t) of represents the current value amplitude, and the abscissa t represents time. Figure 5b and Figure 5c The ordinate z(t) of also represents the current value amplitude, and the abscissa t represents time. Figure 5b 、 Figure 5c The ordinate z(t) of and Figure 5a The ordinate u(t) of are represented by different letters because u(t) is the representation of a continuous signal and z(t) is the representation of a discrete signal As Figure 5a shown, waveform (a) represents the original information of the amplified track circuit signal data, which should theoretically be a sine waveform changing at a certain frequency.

[0070] As Figure 5b shown, waveform ((b) represents the original waveform array information obtained after the data sampling process and the annotation of the zero-crossing position. Figure 5b In, the moment when the data waveform changes from positive to negative is taken as an example of the zero-crossing point. In actual operation, the moment when it changes from negative to positive can also be taken as the zero-crossing point. The sampling period is Δt. Since this calculation method has high requirements for the calculation of the zero-crossing position and the sampling sequence samples at regular time intervals, there is always a certain error. Therefore, a process of accurately positioning the sampling points is required to accurately calculate how many sampling periods Δt a carrier frequency period ΔT consists of.

[0071] As Figure 5c shown, waveform (c) represents the accurate calculation process of the zero-crossing position, which is the amplification of a certain zero-crossing waveform in waveform (b) of Figure 5b . Each carrier frequency period ΔT consists of three parts: the time interval between the first zero-crossing point in the current carrier frequency period and the first sampling point in the current carrier frequency period ( Figure 5c t2 in ), the time interval between the first sampling point in the current carrier frequency period and the last sampling point in the current carrier frequency period, and the time interval between the last sampling point in the current carrier frequency period and the second zero-crossing point in the current carrier frequency period ( Figure 5cin t1).

[0072] Exemplarily, perform a linear fit near the zero crossing. The calculation method of t1 is as follows: ; Exemplarily, perform a linear fit near the zero crossing. The calculation method of t2 is as follows: ; Wherein, t1 in the above formula represents the time interval between the last sampling point in the current carrier frequency period and the second zero crossing in the current carrier frequency period, t2 represents the time interval between the first zero crossing in the current carrier frequency period and the first sampling point in the current carrier frequency period, Δt represents the sampling period, u 1 represents the amplitude of the current value corresponding to the last sampling point in the current carrier frequency period, u 2 represents the amplitude of the current value corresponding to the first sampling point in the current carrier frequency period.

[0073] Exemplarily, the calculation method of the carrier frequency period ΔT is as follows: ; Wherein, t1 represents the time interval between the last sampling point in the current carrier frequency period and the second zero crossing in the current carrier frequency period, t2 represents the time interval between the first zero crossing in the current carrier frequency period and the first sampling point in the current carrier frequency period, Δt represents the sampling period, n represents the number of complete sampling periods included in the current carrier frequency period.

[0074] Exemplarily, the calculation method of the frequency value to be put into the time domain frequency data array (i.e., the frequency value of the signal at the current moment, where the current moment refers to taking the signal time window corresponding to the current carrier frequency period as the current moment) can be as follows: .

[0075] An embodiment of the present application also provides an abnormal detection device for track circuit signals, as Figure 6 shown, including: a memory and a processor; The memory is used to store a program for performing abnormal detection of track circuit signals; The processor is used to read the program for performing abnormal detection of track circuit signals and execute the abnormal detection method for track circuit signals as described in any embodiment of the present application.

[0076] An embodiment of the present application also provides a system applying the abnormal detection method for track circuit signals as described in any embodiment of the present application. The system includes: The on-vehicle track circuit signal acquisition system is used to obtain the original waveform array data of the guide through the receiving coil installed on the train, through signal processing and AD acquisition devices, at a sampling rate exceeding twice the highest signal frequency. The data analysis system is used to analyze the original waveform array data, obtain the time-domain index data and frequency-domain index data of the track circuit signal, restore the track circuit signal data, and evaluate the ground track circuit condition based on the data restoration result, to obtain the abnormal time points and position points of the track circuit condition.

[0077] In summary, an abnormal detection method, device and system for track circuit signals provided by this application obtain the original data of track circuit signals collected in real time through the track circuit signal receiving coil on the train, perform frequency-domain analysis on the original data to obtain the effective current information of the track circuit signal on the rail; at the same time, perform time-domain analysis on the original data to obtain the carrier frequency and low-frequency frequency deviation information of the track circuit signal; comprehensively analyze the effective current information of the rail, the carrier frequency of the track circuit signal and the low-frequency frequency deviation information, can obtain the real-time state of the track circuit signal, which helps to analyze the abnormal state of the track circuit, thereby improving the maintenance efficiency of ground track circuit equipment, eliminating occasional hidden equipment fault points, reducing the probability of encountering abnormal track circuit signals during the train operation while improving the work efficiency of maintenance personnel, and enhancing the train operation efficiency.

[0078] Those of ordinary skill in the art will understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations. In the hardware implementation, the division of the functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be executed by several physical components in cooperation. Some or all of the components can be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, a communication medium typically contains computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0079] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of this 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, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0080] Although the embodiments of this application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting this application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for detecting abnormal track circuit signals, characterized in that Including: Periodically collecting the original waveform array data of the track circuit signal; Based on the original waveform array data of the track circuit signal collected at each acquisition moment respectively, obtaining the time-domain index data and frequency-domain index data corresponding to this acquisition moment; Restoring the track circuit signal according to the time-domain index data and frequency-domain index data corresponding to multiple acquisition moments; Determining whether there is an abnormality according to the restored track circuit signal.

2. The abnormal detection method of track circuit signals according to claim 1, wherein The time-domain index data includes low-frequency frequency deviation and carrier frequency deviation; Obtaining the time-domain index data corresponding to this acquisition moment includes: Obtaining the time-domain frequency data array according to the original waveform array data at this acquisition moment and the signal sampling frequency; Obtaining the actual low-frequency frequency value based on the time-domain frequency data array, and obtaining the low-frequency frequency deviation according to the actual low-frequency frequency value; Obtaining the carrier frequency deviation based on the time-domain frequency data array and the actual low-frequency frequency value.

3. The track circuit signal anomaly detection method according to claim 2, characterized in that, Obtaining the time-domain frequency data array according to the original waveform array data at this acquisition moment and the signal sampling frequency includes: Performing DC removal processing on the original waveform array data to obtain DC-removed waveform array data; Calculating the zero-crossing information according to the DC-removed waveform array data, and obtaining the sampling interval information between zero-crossings according to the zero-crossing information; Calculating the frequency value of the signal at each moment within the time period corresponding to the original waveform array data according to the sampling interval information and the signal sampling frequency, and generating the time-domain frequency data array according to the frequency value of the signal at each moment.

4. The method for detecting abnormal track circuit signals according to claim 2 or 3, characterized in that Obtaining the actual low-frequency frequency value based on the time-domain frequency data array, and obtaining the low-frequency frequency deviation according to the actual low-frequency frequency value includes: Performing spectrum analysis on the time-domain frequency data array to obtain the low-frequency change frequency; Obtaining the highest energy point frequency by the method of extreme value selection, and taking the highest energy point frequency as the actual low-frequency frequency value; Taking the difference between the actual low-frequency frequency value and the preset standard low-frequency frequency value as the low-frequency frequency deviation.

5. The method for detecting abnormal track circuit signals according to claim 4, wherein Obtaining the carrier frequency deviation based on the time-domain frequency data array and the actual low-frequency frequency value includes: Determining the corresponding period length according to the actual low-frequency frequency value, selecting the data points of an integer number of periods in the time-domain frequency data array for arithmetic average, and calculating the actual carrier frequency value; Taking the deviation between the actual carrier frequency value and the preset carrier center value as the carrier frequency deviation.

6. The method for detecting abnormal track circuit signals according to claim 2, wherein The frequency-domain index data includes signal-to-noise ratio and effective current value; obtaining the frequency-domain index data corresponding to this acquisition moment includes: Obtaining the energy values of each frequency band according to the original waveform array data and the signal sampling frequency; the energy of each frequency band includes the energy value of the effective signal and the energy value of the invalid signal; Calculating the signal-to-noise ratio according to the energy value of the effective signal and the energy value of the invalid signal; Calculating the effective current value of the track circuit signal according to the energy value and the hardware characteristic parameters of the signal transmission link, and the hardware characteristic parameters of the signal transmission link include the receiving coil height, impedance, and circuit amplification factor.

7. The abnormal detection method for track circuit signals according to claim 6, wherein, Determining whether there is an abnormality according to the restored track circuit signal includes: Determine the values of the abnormal evaluation parameters corresponding to the multiple acquisition times according to the restored track circuit signals, where the abnormal evaluation parameters are one or more signal parameters preset in advance; Judge whether the values of the abnormal evaluation parameters meet the preset criteria; and / or, judge whether the track circuit signals are continuously unstable. Continuously unstable means that the values of any one or more of the abnormal evaluation parameters corresponding to multiple consecutive acquisition times do not meet the preset criteria, and the duration of the first time period composed of these multiple consecutive acquisition times exceeds the preset timeout duration corresponding to the abnormal evaluation parameter; Determine the abnormal time point and location point of the track circuit according to the acquisition times corresponding to the values of the abnormal evaluation parameters that do not meet the preset criteria; and / or, determine the abnormal time period and location section of the track circuit according to the first time period.

8. The track circuit signal abnormality detection method according to claim 7, characterized in that, The abnormal evaluation parameters include the effective value of current, signal-to-noise ratio, carrier frequency deviation, and low-frequency deviation; judging whether the values of the abnormal evaluation parameters of the track circuit signals meet the preset criteria includes: For each moment within the time period corresponding to the original waveform array data, perform one or more of the following operations: Judge whether the effective value of the current of the track circuit signal at this moment is lower than the preset minimum effective value of current; Judge whether the value of the signal-to-noise ratio of the track circuit signal at this moment is lower than the preset minimum signal-to-noise ratio value; Judge whether the absolute value of the carrier frequency deviation of the track circuit signal at this moment is lower than the preset maximum carrier frequency deviation value; Judge whether the absolute value of the low-frequency deviation of the track circuit signal at this moment is lower than the preset maximum low-frequency deviation value.

9. The track circuit signal abnormality detection method according to claim 1, wherein The acquisition of the original waveform array data of the track circuit signal includes: Obtain the track circuit signal through the on-vehicle receiving coil, and after signal conditioning and analog-to-digital conversion, obtain the original waveform array data of the track circuit signal at a signal sampling frequency exceeding twice the highest signal frequency.

10. An abnormal detection device for track circuit signals, comprising: A memory and a processor, characterized in that: The memory is used to store the program for abnormal detection of track circuit signals; The processor is used to read the program for abnormal detection of track circuit signals and execute the track circuit signal abnormal detection method according to any one of claims 1 to 9.

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