Vehicle-mounted network safety communication method for railway vehicle

Abstract

The invention discloses a railway vehicle on-board network safety communication method, and relates to the technical field of on-board network safety, and the method comprises the steps: carrying out the abnormality evaluation analysis of signals circulating between sensors in a railway vehicle, and recognizing whether the signals transmitted by the next group have related abnormalities or not based on the signal features of the previous group, thereby achieving the safety of the on-board network. If only a single group of abnormal signals exist in the period, frequency adjustment is directly carried out to ensure that the corresponding sensor end can work normally, and if multiple groups of abnormal signals exist, frequency band analysis is carried out to identify whether the plurality of abnormal signals are subjected to same-frequency interference or external network intrusion; in the aspect of identification of network security communication, the method is wider in range and better in effect, the corresponding sensor ends are synchronously and timely corrected, and normal signal transmission of the sensors in the railway vehicle body can be effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle-mounted network security, and in particular to a vehicle-mounted network security communication method for a rail vehicle. Background Art

[0002] The rail vehicle on-board network refers to the network system installed on the rail vehicle to realize data communication and control between various devices inside the vehicle.

[0003] With the continuous development of rail vehicle technology, rail vehicle on-board networks play a vital role in ensuring the safe and efficient operation of trains; however, in practical applications, rail vehicle on-board networks face many challenges.

[0004] On the one hand, there are many sensors inside rail vehicles, and the signals flowing between sensors are complex and diverse. Due to the influence of various factors, the signals may be abnormal during the transmission process, such as interference, failure, etc. Traditional signal monitoring methods can only alarm when the signal is obviously abnormal, and cannot deal with potential interference, which may cause abnormal operation of the sensor and affect the normal operation of the rail vehicle.

[0005] On the other hand, in terms of network security, rail vehicle onboard networks also face risks such as external network intrusion and co-frequency interference. If these risks are not identified in a timely manner and corresponding measures are not taken, protocol problems may occur, which in turn may cause the simultaneous appearance of multiple sets of abnormal signals, seriously threatening the network security communications of rail vehicles. In addition, when network security problems arise, how to quickly and accurately find the problem points so that external personnel can take timely response measures is also an urgent problem to be solved in the current rail vehicle onboard networks. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method for secure on-board network communication of a rail vehicle.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A rail vehicle onboard network security communication method, comprising the following steps:

[0008] Step 1: calibrate the sensors with signal flow in the rail vehicle as an interactive sensor set, perform correlation analysis on the signal waveforms flowing in the interactive sensor set, and lock the evaluation criteria for the next set of signal waveforms based on the signal waveform data. The specific sub-steps are:

[0009] S11, determine the signal waveform of the interactive sensor set that has completed the interaction closest to the current moment, determine the wave speed of this signal waveform, and calibrate it as V k , where k represents a set of different interacting sensors;

[0010] S12, re-determine the wavelength of the signal waveform: lock multiple peak points of the signal waveform, and determine the horizontal and vertical distances between adjacent peak points, average the determined horizontal and vertical distances to determine the wavelength, and mark the determined wavelength as B k , using F k =V k ÷B k Determine its standard frequency F k , F k The value range of ±Y1 is used as the evaluation standard for the next signal waveform of this interactive sensor set, where Y1 is the preset value;

[0011] Step 2: Perform standard verification on the signals transmitted between the interactive sensor set. Based on the determined evaluation criteria, identify whether the currently transmitted signal is abnormal. If there is an abnormality, perform relevant calibration on the abnormal signal. If there is no abnormality, determine the standard frequency of the signal and lock the evaluation criteria, and perform abnormal judgment on the next group of signals. The specific sub-steps are:

[0012] S21, using the same method as steps S11-S12, determine the standard frequency of the signal transmitted this time, and mark it as PL, compare PL with the evaluation standard: PL∈evaluation standard, it means that the signal transmitted between the interactive sensor set this time is normal, and determine the evaluation standard of the next group of signals based on the signal waveform of this signal;

[0013] If PL If the evaluation standard is not met, the signal will be marked as an abnormal signal;

[0014] Step 3: Based on the determined abnormal signal, a group of association cycles is locked, and the signals transmitted between different sets of interactive sensors in this association cycle are subjected to standard verification to identify whether there are multiple groups of abnormal signals in this association cycle, and different processing measures are performed based on different identification results. The specific method is as follows:

[0015] Based on the moment of determining the abnormal signal, a group of association periods T is determined in the future, where T is a preset value, and the signals transmitted by different sets of interactive sensors within the association period T are subjected to standard verification. For the same set of interactive sensors, the same method is used to preferentially determine the evaluation criteria based on the signals transmitted by the upper group, and then confirm whether the signals transmitted by the lower group are abnormal signals. If there are abnormal signals, the determined abnormal signals are calibrated as secondary abnormal signals, and step P311 is executed. If there are no abnormal signals, no calibration is performed, and step S311 is executed;

[0016] Step S311 includes:

[0017] Based on the interactive sensor set associated with the abnormal signal, the sender of the abnormal signal is identified from the interactive sensor set, the signal generation frequency of the sender is adjusted, and the signal is sent in real time, and it is identified whether the frequency generated by the next group of signals sent is within the evaluation standard determined by the previous group of signals. If it is, the adjustment is stopped and the signal generation frequency after the adjustment is executed to send the signal; if it is not, the adjustment is continued until the signal sent is within the evaluation standard;

[0018] Step P311 includes:

[0019] The determined abnormal signal and the determined secondary abnormal signal are marked as the signal to be checked, the interactive sensor set associated with the signal to be checked is determined, the signal transmitted by the corresponding interactive sensor set before the signal to be checked is used as the standard signal, and the signal waveform of the signal to be checked is compared with the signal waveform of the corresponding standard signal: the initial endpoints of the two sets of waveforms are aligned, and after the alignment is completed, two points in the two waveforms belonging to the same vertical direction are determined, and the vertical distance L between the two points is determined. i , where i represents two different points, when L i > Y2, where Y2 is the preset value, the point on the signal waveform corresponding to the signal to be checked is marked as an abnormal point. i When ≤Y2, no calibration is performed, and based on the determined abnormal points, the waveform segment between adjacent abnormal points is calibrated as an abnormal band;

[0020] Confirm the characteristic value of the abnormal band inside the signal waveform of different signals to be checked: place the abnormal band in a set of two-dimensional coordinate systems, make the initial point of the abnormal band coincide with the origin of the two-dimensional coordinate system, and sequentially construct vertical lines with the endpoints of the abnormal band between the horizontal coordinate axes of the two-dimensional coordinate system. Based on the constructed vertical lines, identify the area parameters of the abnormal band located above and below the horizontal coordinate axis, calibrate the area parameter of the upper area as M1, and calibrate the area parameter of the lower area as M2, and use Tm=M1-M2 to determine the characteristic value of the abnormal band corresponding to the signal to be checked;

[0021] The plurality of groups of characteristic values ​​associated with the plurality of groups of signals to be checked confirmed this time are subjected to variance processing to determine the variance parameter Fc, and the determined variance parameter Fc is checked with the preset value Y3. When Fc≤Y3, the frequency of the interactive sensor set associated with each signal to be checked is adjusted in the same manner as in step S311, and the frequency adjustment is stopped when the standard is met;

[0022] When Fc>Y3, step 4 is executed to perform network analysis to assess whether there is a network security problem that causes related faults in signal transmission between sensors;

[0023] Step 4: Based on the interval period of the abnormal signal, lock a group of interaction time periods, identify the interaction logs associated with this interaction time period from the master control terminal, and determine the interaction type of the interaction data from the interaction logs. Based on the historical completion data of the corresponding interaction type, determine the abnormal type and display it. The specific sub-steps are:

[0024] S41, based on the abnormal signal determined in step 2, identify the set of interactive sensors associated with the abnormal signal and determine the sender, lock the time interval for the sender to send such abnormal signal, and based on the determined time of the abnormal signal and the determined time interval, trace the time period from the determined time forward, determine the interactive time period through the endpoint time of the traceability, the specific duration of the traceability is consistent with the time interval, and confirm the interactive log generated in the interactive time period;

[0025] S42, identifying the interaction type existing in the interaction log, and identifying the flow data generated per unit time of this interaction type from the historical completion data, determining the flow standard interval Bq belonging to this interaction type based on the minimum and maximum values ​​of the flow data, and identifying the flow data Lq generated per unit time of this interaction type from the interaction log, where q represents different interaction types:

[0026] If Lq∈Bq, no processing is performed;

[0027] If Lq Bq,marks this type of interaction as an abnormal type and displays it directly in the display terminal.

[0028] The present invention provides a method for secure communication of a rail vehicle onboard network. Compared with the prior art, it has the following beneficial effects:

[0029] The present invention performs abnormal assessment and analysis on the signals circulating between the internal sensors of the rail vehicle, identifies whether the signals transmitted by the next group have related abnormalities based on the signal characteristics of the previous group, and performs period confirmation. When there is only a single group of abnormal signals in the period, the frequency adjustment is directly performed to ensure that the corresponding sensor end can work normally. If there are multiple groups of abnormal signals, frequency band analysis is performed to identify whether the several abnormal signals are all subject to co-frequency interference or external network invasion, resulting in related problems in the protocol, thereby causing the simultaneous appearance of multiple groups of abnormal signals. The identification of network security communication is more extensive and has better effects. The corresponding sensor end is corrected synchronously and timely, which can effectively ensure the normal signal transmission of the sensor in the rail vehicle body, achieve better network security communication effect, and effectively ensure the communication of the vehicle network itself.

[0030] Secondly, in response to relevant situations where network security issues exist, the interaction period is locked based on the determined time of the corresponding abnormal signal, and the interaction log is determined. The corresponding abnormal type in the interaction log is identified from the historical completion data and displayed in a timely manner. This can quickly and effectively identify network security communication problems, quickly discover network anomalies and find problem points, making it convenient for external personnel to take timely response measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the process of the present invention;

[0032] Figure 2 It is a schematic diagram of processing abnormal bands of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0034] See also Figure 1 When rail vehicles are communicating with each other, corresponding sensors will transmit signals. The signals transmitted between the relevant sensors have corresponding signal characteristics, and the signals have corresponding waveforms and relevant characteristic data. Therefore, based on the specific characteristic data, it can be evaluated whether the signals have relevant abnormalities. Based on the specific evaluation results and abnormal conditions, it is determined whether the abnormal conditions are caused by electromagnetic interference or network security problems, so as to perform relevant signal display and processing. In order to display the detailed evaluation and processing process, the present application provides a rail vehicle on-board network security communication method, which specifically includes the following steps:

[0035] Step 1: calibrate the sensors with signal flow in the rail vehicle as an interactive sensor set (the interactive sensor set is a general term for two intercommunication sensors), perform correlation analysis on the signal waveforms circulated in the interactive sensor set, and lock the evaluation criteria of the next set of signal waveforms based on the signal waveform data (the evaluation criteria of this set of signal waveforms are based on the signal characteristics generated by the previous set of signal waveforms during transmission, and the signal characteristics are the relevant frequencies determined by the corresponding wavelengths and wave speeds. In the absence of any interference, the frequencies of the signals interacted by the two sensors should be consistent and will not change, because the transmission protocol determined between the two is also in a determined state). The specific sub-steps of locking the evaluation criteria of the next set of signal waveforms are:

[0036] S11, determine the signal waveform of the interactive sensor set that has completed the interaction closest to the current moment (that is, the signal waveform of the last group that completed the interaction), determine the wave speed of this signal waveform, and calibrate it as V k , where k represents a set of different interactive sensors. Specifically, the corresponding speed data can be determined after the signal waveform completes the relevant transmission;

[0037] S12, re-determine the wavelength of the signal waveform: lock multiple peak points of the signal waveform, and determine the horizontal and vertical distances between adjacent peak points, average the determined horizontal and vertical distances to determine the wavelength, and mark the determined wavelength as B k , using F k =V k ÷B k Determine its standard frequency F k , F k The value range of ±Y1 is used as the evaluation standard for the next signal waveform of this interactive sensor set, where Y1 is a preset value. Its specific value is determined by the operator based on experience, and is generally 0.3-0.5;

[0038] The frequency of the signal waveform is determined by the wave velocity and the corresponding wavelength of the corresponding signal waveform. Since the signals transmitted between the same type of interactive sensors are basically the same, the generated signal frequencies are also basically the same. Therefore, the previous signal data can be directly used as the relevant standard for the waveform transmitted between the next set of such sensors.

[0039] Step 2: Perform standard verification on the signals transmitted between the interactive sensor set. Based on the determined evaluation criteria, identify whether the currently transmitted signal is abnormal. If there is an abnormality, perform relevant calibration on the abnormal signal. If there is no abnormality, determine the standard frequency of the signal and lock the evaluation criteria, and perform abnormal judgment on the next group of signals. The specific sub-steps of evaluating whether there is an abnormality are as follows:

[0040] S21, using the same method as steps S11-S12, determine the standard frequency of the signal transmitted this time, and mark it as PL (the signal transmitted this time is the next group of signals corresponding to the signal in step 1), compare PL with the evaluation standard: PL∈evaluation standard, it means that the signal transmitted between the interactive sensor set this time is normal, and determine the evaluation standard of the next group of signals based on the signal waveform of this signal;

[0041] If PL If the evaluation standard is not met, the signal will be marked as an abnormal signal;

[0042] Step 3: Based on the determined abnormal signal, a group of association cycles is locked, and the signals transmitted between different sets of interactive sensors in the association cycle are subjected to standard verification to identify whether there are multiple groups of abnormal signals in the association cycle, and different processing measures are performed based on different identification results. The specific sub-steps of identification are:

[0043] S31. Based on the moment of determination of the abnormal signal, a group of associated periods T is determined in the future, wherein T is a preset value, and its specific value is determined by the operator based on experience. The signals transmitted by different sets of interactive sensors within the associated period T are subjected to standard verification. For the same set of interactive sensors, the same method is used to preferentially determine its evaluation standard based on the signal transmitted by the upper group, and then confirm whether the signal transmitted by the lower group is an abnormal signal. If an abnormal signal exists, the determined abnormal signal is calibrated as a secondary abnormal signal, and step P311 is executed (the secondary abnormal signal is not the abnormal signal determined by steps one to two). If no abnormal signal exists, it means that only the determined abnormal signal exists, and no abnormal signal is determined within its associated period, so no calibration is performed, and step S311 is executed (step P311 and step S311 are in parallel relationship, and there are only two situations, either there is only one group of abnormal signals, or there are multiple groups of abnormal signals, so it is a parallel relationship);

[0044] S311. Based on the interactive sensor set associated with the abnormal signal, identify the sender of the abnormal signal from the interactive sensor set, adjust the signal generation frequency of the sender, and send the signal in real time, identify whether the frequency generated by the next group of signals sent is within the evaluation criteria determined by the previous group of signals, if so, stop adjusting and execute the adjusted signal generation frequency to send the signal, if not, continue adjusting until the sent signal is within (this is also an anti-interference process, when there is only one group of abnormal signals, it means that the signal is subject to co-frequency interference during transmission, then In order to avoid such interference, the frequency of occurrence of such signals can be directly adjusted so that the frequency of occurrence of such signals is staggered with the interference frequency, which can ensure that the signal will not be affected by relevant interference. The evaluation method is also based on the signals generated by the previous group to determine the specific standards of the next group of signals, so as to determine whether the evaluation meets the standards. When the previous group of signals A is abnormal and the next group of signals B is normal, the evaluation still does not meet the standards. Then the next group of signals B at this moment is used as the evaluation standard for the next group of signals C. If the evaluation meets the standards, the relevant adjustment process of the corresponding signal frequency can be completed, thereby executing the optimal signal frequency);

[0045] P311. Mark the determined abnormal signal and the determined secondary abnormal signal (there may be one group or multiple groups of secondary abnormal signals) as signals to be checked, determine the interactive sensor set associated with the signal to be checked, use the signal transmitted by the corresponding interactive sensor set before the signal to be checked as the standard signal (that is, the signal transmitted by the previous group of the signal to be checked, which is the standard signal), and compare the signal waveform of the signal to be checked with the signal waveform of the corresponding standard signal: align the initial endpoints of the two groups of waveforms, and after the alignment is completed, determine the two points in the two waveforms that belong to the same vertical direction, and determine the vertical distance L between the two points. i , where i represents two different points, when L i > Y2, where Y2 is a preset value, and its specific value is determined by the operator based on experience. The point on the signal waveform corresponding to the signal to be checked is marked as an abnormal point. i When ≤Y2, no calibration is performed, and based on the determined abnormal points, the waveform segment between adjacent abnormal points is calibrated as an abnormal band;

[0046] Confirm the characteristic value of the abnormal band within the signal waveform of different signals to be verified: Combined with Figure 2 , place the abnormal band in a set of two-dimensional coordinate systems, make the initial point of the abnormal band coincide with the origin of the two-dimensional coordinate system, and sequentially construct vertical lines with the endpoints of the abnormal band between the horizontal coordinate axes of the two-dimensional coordinate system, based on the constructed vertical lines (there may also be only one set of vertical lines), identify the area parameters of the abnormal band located above and below the horizontal coordinate axis (based on the constructed vertical lines, the relevant area contained between the vertical lines and the abnormal band can be locked), calibrate the area parameter of the upper area as M1, calibrate the area parameter of the lower area as M2, and use Tm=M1-M2 to determine the characteristic value of the abnormal band corresponding to the signal to be checked;

[0047] The several groups of characteristic values ​​associated with the several groups of signals to be checked confirmed this time are processed with variance (because the variance processing method is relatively common in the prior art, it will not be described in detail here. Generally, the discreteness between the several groups of data can be evaluated according to the confirmed variance. When the difference between the data is large, the variance generated will also be large), and the variance parameter Fc is determined. The determined variance parameter Fc is checked with the preset value Y3. When Fc≤Y3, it means that the numerical difference between the several characteristic values ​​is small and relatively clustered, which means that their characteristics are relatively close. Therefore, the generation of multiple abnormal signals is basically caused by external electromagnetic interference. The frequency of each interactive sensor set associated with the signal to be checked is adjusted in the same way as in step S311, and it stops when it meets the standard. There is also the following: when the specific duration of the frequency adjustment of the corresponding interactive sensor set exceeds 6h, it still cannot meet the standard, then an error signal will be directly generated for display for external operators to view, which means that the sensors associated with such interactive sensor set may have related faults, and human intervention is required to solve such fault problems;

[0048] When Fc>Y3, it means that the numerical differences between several eigenvalues ​​are large, and the characteristics between several eigenvalues ​​are far apart, which means that such abnormal signals are not caused by external electromagnetic interference. Therefore, step 4 is executed to perform network analysis to assess whether there are network security issues that cause related faults in signal transmission between sensors.

[0049] Step 4: Based on the interval period of the abnormal signal, a group of interaction time periods are locked, and the interaction logs associated with the interaction time periods are identified from the master control terminal, and the interaction type of the interaction data is determined from the interaction logs. Based on the historical completion data of the corresponding interaction type, the abnormal type is determined and displayed, wherein the specific sub-steps for determination are:

[0050] S41. Based on the abnormal signal determined in step 2, identify the interactive sensor set associated with the abnormal signal and determine the sender, lock the time interval for the sender to send such abnormal signal (such time interval can be directly obtained from the transmission protocol of the corresponding sensor set, belongs to the existing relevant data, and can be directly extracted), based on the determined time of the abnormal signal and the determined time interval, trace the time period from the determined time forward, determine the interactive time period through the endpoint time of the traceability, the specific duration of the traceability is consistent with the time interval, and confirm the interactive log generated in the interactive time period;

[0051] S42, identifying the interaction type existing in the interaction log, and identifying the flow data generated per unit time of this interaction type from the historical completion data, determining the flow standard interval Bq belonging to this interaction type based on the minimum and maximum values ​​of the flow data, and identifying the flow data Lq generated per unit time of this interaction type from the interaction log, where q represents different interaction types:

[0052] If Lq∈Bq, no processing is performed;

[0053] If Lq Bq, marks this type of interaction as an abnormal type and displays it directly on the display terminal for external relevant personnel to view. Based on the determined abnormal type, the external relevant personnel delete the relevant data packets, and simultaneously record the IP address associated with this abnormal type and blacklist it, so as to provide associated protection for network security.

[0054] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0055] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A rail vehicle onboard network security communication method, characterized in that: The following steps are involved: Step 1: calibrate the sensors with signal circulation in the rail vehicle as an interactive sensor set, perform correlation analysis on the signal waveforms circulating in the interactive sensor set, and lock the evaluation criteria of the next set of signal waveforms based on the signal waveform data; Step 2: Perform standard verification on the signals transmitted between the interactive sensor set, and identify whether the currently transmitted signal is abnormal based on the determined evaluation standard. If there is an abnormality, perform relevant calibration on the abnormal signal. If there is no abnormality, determine the standard frequency of the signal and lock the evaluation standard, and perform abnormal judgment on the next group of signals; Step 3: Based on the determined abnormal signal, a group of association cycles is locked, and the signals transmitted between different sets of interactive sensors in the association cycle are subjected to standard verification to identify whether there are multiple groups of abnormal signals in the association cycle, and different processing measures are executed based on different identification results; Step 4: Based on the interval period of the abnormal signal, lock a group of interaction time periods, identify the interaction logs associated with this interaction time period from the master control terminal, and determine the interaction type of the interaction data from the interaction logs. Based on the historical completion data of the corresponding interaction type, determine the abnormal type and display it.

2. A rail vehicle onboard network security communication method according to claim 1, characterized in that: In step 1, the specific sub-steps of locking the evaluation criteria of the next set of signal waveforms are: S11, determine the signal waveform of the interactive sensor set that has completed the interaction closest to the current moment, determine the wave speed of this signal waveform, and calibrate it as V k , where k represents a set of different interacting sensors; S12, re-determine the wavelength of the signal waveform: lock multiple peak points of the signal waveform, and determine the horizontal and vertical distances between adjacent peak points, average the determined horizontal and vertical distances to determine the wavelength, and mark the determined wavelength as B k , using F k =V k ÷B k Determine its standard frequency F k , F k The value range of ±Y1 is used as the evaluation standard for the next signal waveform of this interactive sensor set, where Y1 is a preset value.

3. A rail vehicle onboard network security communication method according to claim 2, characterized in that: In step 2, the specific sub-steps of identifying whether the currently transmitted signal is abnormal are: S21, using the same method as steps S11-S12, determine the standard frequency of the signal transmitted this time, and mark it as PL, compare PL with the evaluation standard: PL∈evaluation standard, it means that the signal transmitted between the interactive sensor set this time is normal, and determine the evaluation standard of the next group of signals based on the signal waveform of this signal; like If the evaluation standard is not met, the signal will be marked as an abnormal signal.

4. A rail vehicle onboard network security communication method according to claim 1, characterized in that: In step 3, the specific method of identifying whether there are multiple groups of abnormal signals in the current correlation period is: Based on the moment of determining the abnormal signal, a group of associated periods T is determined in the future, where T is a preset value. The signals transmitted by different sets of interactive sensors within the associated period T are subjected to standard verification. For the same interactive sensor set, the same method is used to preferentially determine its evaluation criteria based on the signal transmitted by the upper group, and then confirm whether the signal transmitted by the lower group is an abnormal signal. If an abnormal signal exists, the determined abnormal signal is calibrated as a secondary abnormal signal, and step P311 is executed. If no abnormal signal exists, no calibration is performed, and step S311 is executed.

5. A rail vehicle onboard network security communication method according to claim 4, characterized in that: The step S311 includes: Based on the interactive sensor set associated with this abnormal signal, the sender of this abnormal signal is identified from the interactive sensor set, the signal generation frequency of the sender is adjusted, and the signal is sent in real time, and it is identified whether the frequency generated by the next group of signals sent is within the evaluation criteria determined by the previous group of signals. If it is, the adjustment is stopped and the signal is sent with the adjusted signal generation frequency. If it is not, the adjustment is continued until the signal sent is within.

6. A rail vehicle onboard network security communication method according to claim 4, characterized in that: The step P311 comprises: The determined abnormal signal and the determined secondary abnormal signal are marked as the signal to be checked, the interactive sensor set associated with the signal to be checked is determined, the signal transmitted by the corresponding interactive sensor set before the signal to be checked is used as the standard signal, and the signal waveform of the signal to be checked is compared with the signal waveform of the corresponding standard signal: the initial endpoints of the two sets of waveforms are aligned, and after the alignment is completed, two points in the two waveforms belonging to the same vertical direction are determined, and the vertical distance L between the two points is determined. i , where i represents two different points, when L i > Y2, where Y2 is the preset value, the point on the signal waveform corresponding to the signal to be checked is marked as an abnormal point. i When ≤Y2, no calibration is performed, and based on the determined abnormal points, the waveform segment between adjacent abnormal points is calibrated as an abnormal band; Confirm the characteristic value of the abnormal band inside the signal waveform of different signals to be checked: place the abnormal band in a set of two-dimensional coordinate systems, make the initial point of the abnormal band coincide with the origin of the two-dimensional coordinate system, and sequentially construct vertical lines with the endpoints of the abnormal band between the horizontal coordinate axes of the two-dimensional coordinate system. Based on the constructed vertical lines, identify the area parameters of the abnormal band located above and below the horizontal coordinate axis, calibrate the area parameter of the upper area as M1, and calibrate the area parameter of the lower area as M2, and use Tm=M1-M2 to determine the characteristic value of the abnormal band corresponding to the signal to be checked; The plurality of groups of characteristic values ​​associated with the plurality of groups of signals to be checked confirmed this time are subjected to variance processing to determine the variance parameter Fc, and the determined variance parameter Fc is checked with the preset value Y3. When Fc≤Y3, the frequency of the interactive sensor set associated with each signal to be checked is adjusted in the same manner as in step S311, and the frequency adjustment is stopped when the standard is met; When Fc>Y3, step 4 is executed to perform network analysis to assess whether there is a network security problem that causes related faults in signal transmission between sensors.

7. A rail vehicle onboard network security communication method according to claim 1, characterized in that: In step 4, the specific sub-steps for determining the abnormality type are: S41, based on the abnormal signal determined in step 2, identify the set of interactive sensors associated with the abnormal signal and determine the sender, lock the time interval for the sender to send such abnormal signal, and based on the determined time of the abnormal signal and the determined time interval, trace the time period from the determined time forward, determine the interactive time period through the endpoint time of the traceability, the specific duration of the traceability is consistent with the time interval, and confirm the interactive log generated in the interactive time period; S42, identifying the interaction type existing in the interaction log, and identifying the flow data generated per unit time of this interaction type from the historical completion data, determining the flow standard interval Bq belonging to this interaction type based on the minimum and maximum values ​​of the flow data, and identifying the flow data Lq generated per unit time of this interaction type from the interaction log, where q represents different interaction types: If Lq∈Bq, no processing is performed; like This type of interaction is marked as an abnormal type and displayed directly in the display terminal.

Images