A method and system for speed measurement of maglev trains based on sleeper detection

Abstract

This invention discloses a method and system for measuring the speed of a maglev train based on sleeper detection. The method includes: arranging six sensors at certain intervals under the maglev train body; during normal operation, sampling the time difference of the rising edges of the six sensor signals and averaging them, calculating the actual train speed based on the principle that speed equals distance divided by time; calculating four sets of speed values, grouping three adjacent sensors together; identifying faults based on different sensor fault conditions when sensors malfunction or occasionally lose pulse signals, and calculating reliable speed values; and identifying sensor faults based on the collected sensor pulse signals and sending an alarm signal. This system is used to implement the above method. This invention has the advantages of simple principle, convenient installation, wide applicability, and high testing accuracy.

Description

Technical Field

[0001] This invention mainly relates to the field of maglev rail transit technology, specifically a method and system for measuring the speed of maglev trains based on sleeper detection. Background Technology

[0002] Since maglev trains are wheelless and do not contact the track during operation, their speed measurement and positioning differ from that of traditional wheel-rail railways. Generally speaking, there are three main methods for achieving speed measurement and positioning of maglev trains: (1) microwave positioning speed measurement; (2) proximity sensor positioning speed measurement (sleeper detection speed measurement); and (3) cross-induction loop positioning speed measurement.

[0003] The first method, such as radar speed measurement and GPS speed measurement, is subject to multipath propagation interference during microwave propagation. It is also greatly affected by severe weather conditions, so it is not very adaptable to complex terrain. Moreover, its equipment is complex and costly.

[0004] The second method involves installing multiple metal proximity sensors on the train. When each sensor detects a steel sleeper, the operating speed is calculated using the time difference between the signals collected from two sensors. This method is simple in structure, easy to maintain, and low in cost. It has already been applied on railway lines in my country, but it has some problems. For example, the low reliability of the proximity sensors over long-term operation can lead to large errors in the speed signal acquisition, or even prevent the speed measurement system from functioning, seriously affecting train operation safety. Its accuracy is also affected by differences in track spacing, and it has large errors at curves.

[0005] The third method is to lay cross loops on the track and install onboard induction coils on the trains. This method requires permission to lay loops and ensures that there is always an excitation signal. If a signal fails in a certain section, the operation of the entire line will be affected. Summary of the Invention

[0006] The technical problem to be solved by this invention is: in view of the technical problems existing in the prior art, this invention provides a magnetic levitation train speed measurement method and system based on sleeper detection that is simple in principle, easy to install, widely applicable, and has high testing accuracy.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0008] A method for speed measurement of maglev trains based on sleeper detection, comprising:

[0009] Six sensors are arranged at certain intervals under the maglev train body;

[0010] During normal operation, the average of the time difference between the rising edges of the six sensor signals is calculated, and the actual running speed of the train is calculated based on the principle that speed equals distance divided by time.

[0011] Calculate four sets of velocity values, grouping each group into three adjacent sensors;

[0012] When the sensor malfunctions or occasionally loses pulse signals, the fault is identified based on the different fault conditions of the sensor, and a reliable speed value is calculated.

[0013] Based on the collected sensor pulse signals, sensor faults are identified, and alarm signals are sent.

[0014] As a further improvement to the method of the present invention: During normal operation, the speed measurement system samples six sensor signals, namely S1, S2, S3, S4, S5, and S6. The average of the rising time differences of the six sensor signals is calculated. Based on the principle that speed equals distance divided by time, the process includes:

[0015] Step S100: Selection of sampling time base and bit width;

[0016] Step S200: Speed ​​calculation; calculate the time difference between the rising edges of two adjacent pulses; the formulas for speed and frequency calculation are:

[0017] f = v * k / 0.864 = v * 11.574

[0018] v = S / T, where T is the time between the rising edges of two adjacent pulses and S is the distance between the two adjacent pulses.

[0019] As a further improvement to the method of the present invention, it also includes a speed measurement optimization process, which includes: under normal operating conditions, with the direction already determined, taking the positive direction of vehicle operation, taking S1, S2, and S3 as one group, taking S2, S3, and S4 as the second group, taking S3, S4, and S5 as the third group, and taking S4, S5, and S6 as the fourth group; collecting the rising edge time t1 of S1 and S2 of the first group and outputting speed 1; collecting the rising edge time t2 of S2 and S3 of the second group and outputting speed 2; collecting the rising edge time t3 of S3 and S4 of the second group and outputting speed 3; collecting the rising edge time t4 of S4 and S5 of the second group and outputting speed 4; ORing the four groups of speed outputs CS1, CS2, CS3, and CS4 to form a composite CS, and outputting the speed each time CS falls.

[0020] As a further improvement to the method of the present invention, it also includes a speed measurement optimization process, which includes: when the sensor occasionally malfunctions, S3 is used to monitor whether S2 has lost pulses. If there are lost pulses, when S3 rises, t1 is still at a high level. At this time, t1 is set to a low level, and the time of the first group is measured as S1-S3, and the distance traveled is calculated. The measured time t1 is divided by 2 to obtain the speed output of the first group. Since S2 loses pulses, S2-S3 of the second group fails, and the second group has no speed output at this time, and CS2 is not generated. The third group can output the speed of S3-S4 normally.

[0021] As a further improvement to the method of the present invention, it also includes a speed measurement optimization process, which includes: when a sensor fails, S3 is used to monitor whether S2 has lost pulses. If there are lost pulses, when S3 rises, t1 is still at a high level. At this time, t1 is set to a low level, and the time of the first group is measured as S1-S3, the running distance value. The measured time t1 is divided by 2 as the speed output of the first group. Since S2 loses pulses, S2-S3 of the second group fails, and the second group has no speed output at this time, and CS2 is not generated. The third group can output the speed of S3-S4 normally.

[0022] When any one of S3, S4, S5, or S6 fails, and there is a lost pulse state, the speed output is calculated as follows: V1, V2, V3, and V4 are speed values ​​processed in a FIFO manner at the rising edge of the synthesized CS. Each time the speed is updated, the last updated value among V1, V2, V3, and V4 is replaced with the currently updated value. The maximum and minimum values ​​among V1, V2, V3, and V4 are averaged, and the outlier value in the state of lost pulses when any one of S3, S4, S5, or S6 fails is discarded.

[0023] As a further improvement to the method of the present invention, it also includes a speed measurement optimization process, which includes: when multiple sensors fail, when any two sensors fail, the direction and speed magnitude can be normally determined; when three sensors fail, the direction cannot be determined, but the speed magnitude can be determined, and in this case, the speed is set to a speed failure state and the speed is not output; in other such cases, the direction and speed magnitude can be determined; when four sensors fail, as long as two adjacent sensors are normal, the direction and speed magnitude can be determined, but if they are not adjacent, the direction and speed magnitude cannot be determined.

[0024] As a further improvement to the method of the present invention, it also includes a speed measurement optimization process, which includes: speed calculation; generating a high level V between two rising edges of two adjacent signals, counting the high level to obtain a count value n; generating a high level with a ds delay of 16us at the falling edge of V; generating a high level with an as of 8us 8us 8us after the falling edge of V; generating a high level with a bs of 16us 16us 16us after the falling edge of V; generating a high level with a cs of 8us 24us after the falling edge of V; wherein the rising edge of ds is used to update the value of the speed counting register of the adjacent signal group, ORing the four groups of as to synthesize a new AS, and at the rising edge of AS, according to the four groups of d When s is high, the speed counter register with ds high is assigned to the total speed register; the four bs are ORed to form a new BS, and on the rising edge of BS, the four speed channel registers are updated, replacing the last updated value with the latest value; on the falling edge of BS, the speed values ​​of the four speed channels are compared, the maximum and minimum values ​​are removed, and the average amplitude of the two middle values ​​is assigned to the speed output register; finally, the four CS are ORed to form a new CS, and on the rising edge of CS, it is determined whether the speed output register is greater than the set threshold. If it is greater, the speed output register is used as the speed output; if it is less than or equal to, the speed of the group with bs high is used as the speed output based on the high level of bs.

[0025] As a further improvement to the method of the present invention, it also includes a speed measurement optimization process, which includes: speed sensor fault judgment; taking the rising edge of the pulses of the six axes respectively to form a CS, ORing the CS of the six axes, accumulating CS to 31, and at the same time calculating the pulse count of each axis during this period, with a maximum of 7. When CS reaches 31, it is determined that the pulse count of each axis is less than 1, and a fault is judged; when CS reaches 32, the pulse count of each axis is cleared.

[0026] As a further improvement to the method of the present invention, it also includes a self-test process. The self-test process involves sending a standard pulse signal from the system to the proximity sensor. The sensor receives the pulse signal and returns a corresponding pulse signal to the speed measurement system. The speed measurement system checks whether the sensor is faulty by retesting the pulse signal. At the same time, the distance between two adjacent sensors is calculated and corrected by using the time and speed of the standard pulse, so as to solve the problem of speed measurement accuracy caused by the error in the installation spacing between each adjacent sensor.

[0027] The present invention further provides a speed measurement system for maglev trains based on sleeper detection, comprising:

[0028] Six sensors are arranged at certain intervals under the maglev train body;

[0029] The calculation unit is used to sample the time difference of the rising edges of six sensor signals during normal operation and calculate their average. Based on the principle that speed equals distance divided by time, it calculates the actual running speed of the train. It calculates four sets of speed values, with three adjacent sensors as a group.

[0030] The identification unit is used to identify faults based on different fault conditions of the sensor when the sensor fails or when there is occasional loss of pulse signals, and to calculate a reliable speed value; and to identify sensor faults based on the collected sensor pulse signals and send alarm signals.

[0031] Compared with the prior art, the advantages of the present invention are as follows:

[0032] 1. The present invention provides a method and system for measuring the speed of maglev trains based on sleeper detection. This method and system are simple in principle, easy to install, widely applicable, and highly accurate. The invention has a function to diagnose speed sensor malfunctions, capable of identifying up to five sensors in a faulty state. It also features communication capabilities, enabling the onboard information processing device to acquire status signals for diagnostic functions and to transmit wireless information between the vehicle and the ground. This allows for timely notification of the location of faulty sensors and prompts for replacement, thus improving system reliability.

[0033] 2. The magnetic levitation train speed measurement method and system based on sleeper detection of the present invention can simultaneously acquire signals from 6 sensors, calculate 4 sets of speed values ​​by grouping 3 adjacent sensors, and cross-reference them, greatly improving the accuracy of speed calculation. The present invention can also calculate the magnetic levitation speed even when sensor signals are lost or up to 4 sensors malfunction, greatly improving the reliability of magnetic levitation speed measurement.

[0034] 3. The maglev train speed measurement method and system based on sleeper detection of this invention can simultaneously acquire signals from six sensors. Compared to conventional methods using two to four sensors, the number of speed pulse signals increases by more than 50% at the same sampling frequency, improving speed calculation and accelerating speed value updates. Therefore, speed accuracy is also improved, especially when the spacing between the sleepers under the maglev train varies significantly and at curves. Although this increases the computational complexity, the mutual reference between the six sensors further enhances overall reliability and maintainability.

[0035] 4. The magnetic levitation train speed measurement method and system based on sleeper detection of the present invention has a self-testing function. The system sends a standard pulse signal to the proximity sensor. The sensor receives the pulse signal and returns the corresponding pulse signal to the speed measurement system. The speed measurement system checks whether the sensor is faulty by retesting the pulse signal. At the same time, it calculates the distance between two adjacent sensors by using the time and speed of the standard pulse and makes corrections, thus solving the problem of speed measurement accuracy caused by the error in the installation spacing between each adjacent sensor. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the topological structure of the system of the present invention.

[0037] Figure 2 This is a velocity pulse diagram in a specific application example of the present invention.

[0038] Figure 3 This is a schematic diagram of the normal state of the present invention in a specific application example.

[0039] Figure 4 This is a schematic diagram illustrating the loss of pulses in a specific application example of the present invention.

[0040] Figure 5 This is a schematic diagram of a speed sensor malfunction in a specific application example of the present invention.

[0041] Figure 6 This is a schematic diagram illustrating the failure of two speed sensors in a specific application example of the present invention.

[0042] Figure 7 This is a schematic diagram illustrating a specific application example of the present invention where three sensors malfunction and cannot determine direction.

[0043] Figure 8 This is a schematic diagram illustrating a specific application example of the present invention where four sensors malfunction and cannot determine direction and magnitude.

[0044] Figure 9 This is a schematic diagram illustrating the invention in a specific application example where four sensors malfunction but the direction and magnitude can still be determined.

[0045] Figure 10 This is a schematic diagram of time counting processing in a specific application example of the present invention. Detailed Implementation

[0046] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] In the description of this application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0048] like Figure 1 As shown, the speed measurement method for maglev trains based on sleeper detection of the present invention includes:

[0049] Six sensors are arranged at specified intervals under the maglev train body;

[0050] During normal operation, the average of the time difference between the rising edges of the six sensor signals (S1, S2, S3, S4, S5, S6) is calculated, and the actual running speed of the train is determined based on the principle that speed equals distance divided by time.

[0051] Calculate four sets of velocity values, grouping each group into three adjacent sensors;

[0052] In the event of sensor failure or occasional pulse signal loss, the fault is identified based on different sensor failure conditions, and a reliable speed value is calculated, such as... Figures 4-8 As shown, through the above steps of the present invention, the speed value can still be calculated even if up to four sensors fail.

[0053] Based on the collected sensor pulse signals, sensor faults are identified, and alarm signals are sent.

[0054] In specific application examples, when deploying six sensors, depending on actual needs, a spacing of 0.3 meters can be chosen as an example. The sleeper spacing is generally between 0.8 meters and 1.2 meters, but can also exceed this range. Figure 2 As shown.

[0055] In specific application examples, when calculating multiple sets of velocity values, such as Figure 3 As shown, a cross-referencing method is used, and the number of update speed samples and calculations can be increased according to actual needs to improve its real-time accuracy. Speed ​​calculation and updating are as follows: Figure 10 As shown.

[0056] In specific application examples, the alarm signal can be a level signal or it can be implemented through other communication interfaces and communication protocols; the present invention can identify up to five sensor faults.

[0057] In a specific application example, the present invention further includes a self-testing function. A standard pulse signal is sent from the system to the proximity sensor. The sensor receives the pulse signal and returns a corresponding pulse signal to the speed measurement system. The speed measurement system checks whether the sensor is faulty by retrieving the pulse signal. At the same time, the distance between two adjacent sensors is calculated and corrected by using the time and speed of the standard pulse. This can solve the problem of speed measurement accuracy caused by the error in the installation spacing between adjacent sensors.

[0058] In a preferred embodiment, during normal operation, the speed measurement system samples the time difference between the rising edges of six sensor signals (S1, S2, S3, S4, S5, S6) and averages them. Based on the principle that speed equals distance divided by time, the specific process may include:

[0059] Step S100: Selection of sampling time base and bit width;

[0060] The timing base for counting the rising edges of two adjacent pulses must be neither too large, as this would reduce speed accuracy, nor too small, as this would increase FPGA resources. Therefore, the chosen timing base must satisfy both speed accuracy and reduced FPGA resource overhead.

[0061] As a preferred embodiment, a 50µs time base and a 16-bit bit width are selected in this example. Since the maximum value of 16 bits is 65535 and the minimum value is 1, the maximum calculation duration for two adjacent pulses using a 50µs time base is 65535 * 50µs = 3.28s, and the minimum duration is 50µs. Therefore, the minimum accuracy of the speed is 0.3 / 3.28 = 0.32 km / h, and the maximum speed can reach 2000 km / h. Furthermore, from another perspective, estimating the accuracy error when using a 50µs time base to achieve a speed of 120 km / h: v = 120 km / h = 33.33 m / s, yielding T = 9 ms. Therefore, the time error for speed acquisition is T0. 1 =9±0.05ms, v=0.3 / T 1 =33.3±0.1m / s=120±0.36km / h, that is, the accuracy at a speed of 120km / h is 0.36km / h.

[0062] Step S200: Speed ​​calculation; calculate the time difference between the rising edges of two adjacent pulses; the formulas for speed and frequency calculation are:

[0063] f = v * k / 0.864 = v * 11.574 (where k = 10)

[0064] Where v = S / T (where T is the time between the rising edges of two adjacent pulses and S is the distance between two adjacent pulses of 0.3M), and the time base of T is 50us, which is equivalent to T = n * 50us (n is the number of counts), so v = 0.3 / (n * 50us).

[0065] Furthermore, the present invention also includes a speed measurement optimization process to improve the reliability of speed measurement calculations. The process includes the following steps under different operating conditions:

[0066] (a) Under normal operating conditions:

[0067] Under normal circumstances, with the direction already determined, let's take the positive direction of vehicle movement as an example. For example... Figure 3Take S1, S2, and S3 as one group; S2, S3, and S4 as the second group; S3, S4, and S5 as the third group; and S4, S5, and S6 as the fourth group. Collect the rising edge time t1 of S1 and S2 in the first group and output speed 1. Collect the rising edge time t2 of S2 and S3 in the second group and output speed 2. Collect the rising edge time t3 of S3 and S4 in the second group and output speed 3. Collect the rising edge time t4 of S4 and S5 in the second group and output speed 4. OR the four speed outputs CS1, CS2, CS3, and CS4 to form a composite CS. Output the speed at each falling edge of CS.

[0068] (b) Occasionally, the sensor malfunctions:

[0069] Based on the actual pulse measurements, at higher speeds, the sensor occasionally loses pulses, such as... Figure 4 Use S3 to monitor if S2 has a missing pulse. If a missing pulse is detected, t1 will still be high when S3 rises. At this point, set t1 low. The measured time for the first group is S1-S3, and the distance traveled is 0.6m. Therefore, the measured time t1 needs to be divided by 2 to obtain the speed output for the first group. Because S2 has a missing pulse, the second group's S2-S3 is invalid, and the second group has no speed output and does not generate CS2. The third group can output the speed S3-S4 normally.

[0070] (c) A sensor malfunction:

[0071] Use S3 to monitor whether S2 has a missing pulse. If a missing pulse occurs, t1 will still be high when S3 rises. At this time, set t1 low. The measured time for the first group is S1-S3, and the running distance is 0.6m. Therefore, the measured time t1 needs to be divided by 2 to obtain the speed output for the first group. Because S2 has a missing pulse, the second group's S2-S3 is invalid, and the second group has no speed output and does not generate CS2. The third group can output the speed S3-S4 normally. Similarly, suppose one of the sensors fails, such as... Figure 5 The handling would be similar.

[0072] Regarding the situation where one of S3, S4, S5, or S6 malfunctions and there is a lost pulse, the speed output calculation method adopted after the speed exceeds 5 km / h is as follows: V1, V2, V3, and V4 are the speed values ​​processed in FIFO mode at the rising edge of the synthesized CS. Each time the speed is updated, the last updated value in V1, V2, V3, and V4 is replaced with the currently updated value. The maximum and minimum values ​​in V1, V2, V3, and V4 are averaged. In this way, the abnormal value in the state of lost pulse when one of S3, S4, S5, or S6 malfunctions is discarded.

[0073] (d) Multiple sensor failures:

[0074] Clearly, even if any two sensors malfunction, the system can still correctly determine the direction and speed. For example... Figure 6 .

[0075] When all three sensors fail, extreme cases such as Figure 7 If the direction cannot be determined, but the speed can be determined, a speed fault state will be set in this case, and the speed will not be output; otherwise, both the direction and the speed can be determined.

[0076] When all four sensors fail, such as Figure 9 If two adjacent sensors are functioning correctly, the system can determine direction and speed magnitude. However, if they are not adjacent, such as... Figure 8 The direction and magnitude of the speed cannot be determined.

[0077] (e) Velocity calculation;

[0078] Taking S1-S2 as an example, such as Figure 10 A high level V is generated between the two rising edges of S1 and S2. The count value n is obtained by counting the high level, which is the n in the above formula. At the falling edge of V, a high level with a delay of 16us (ds) is generated; 8us after the falling edge of V, a high level with a delay of 8us (as) is generated; 16us after the falling edge of V, a high level with a delay of 16us (bs) is generated; 24us after the falling edge of V, a high level with a delay of 8us (cs) is generated.

[0079] The rising edge of DS is used to update the values ​​of the speed counter registers in groups S1-S2. The four groups of AS are ORed to form a new AS. When AS rises, the speed counter register with high DS is assigned to the total speed register based on the high level of the four groups of DS. The four groups of BS are ORed to form a new BS. When BS rises, the four speed channel registers are updated, and the latest value replaces the last updated value. When BS falls, the speed values ​​of the four speed channels are compared, the maximum and minimum values ​​are removed, and the average value of the two middle values ​​is assigned to the speed output register. Finally, the four groups of CS are ORed to form a new CS. When CS rises, it is determined whether the speed output register is greater than 5km / h. If it is greater, the speed output register is used as the speed output. If it is less than or equal to 5km / h, the speed of the group with high BS is used as the speed output based on the high level of BS.

[0080] (f) Speed ​​sensor fault diagnosis;

[0081] Take the rising edge of the pulses for axes 1, 2, 3, 4, 5, and 6 respectively to generate a clock signal (CS). OR the CS values ​​of the six axes together, accumulating CS values ​​to 31. During this period, calculate the pulse count for each axis, with a maximum of 7. When CS reaches 31, determine if the pulse count for each axis is less than 1, and then identify a fault. When CS reaches 32, clear the pulse count for each axis.

[0082] After determining that the sensor is faulty, it communicates with the host system and issues an alarm.

[0083] In a specific application example, the self-testing process of this invention includes:

[0084] When the speed measurement system is in the self-test position, it outputs a pulse signal to 6 proximity sensors, with a maximum speed not exceeding 120 km / h.

[0085] The pulse output period T = 1 / f = 1 / (v*k / 0.864) = 0.086 / v; v can be set according to the actual situation, and generally the larger the better.

[0086] The pulse outputs of each proximity sensor are delayed by 1 / 4 of the pulse output period.

[0087] After receiving the self-test pulse signal, the proximity sensor outputs the received pulse signal and sends it back to the speed measurement system hardware port.

[0088] See Figure 1 The present invention further provides a speed measurement system for maglev trains based on sleeper detection, comprising:

[0089] Six sensors are arranged at certain intervals under the maglev train body;

[0090] The calculation unit is used to sample the time difference of the rising edges of six sensor signals during normal operation and calculate their average. Based on the principle that speed equals distance divided by time, it calculates the actual running speed of the train. It calculates four sets of speed values, with three adjacent sensors as a group.

[0091] The identification unit is used to identify faults based on different fault conditions of the sensor when the sensor fails or when there is occasional loss of pulse signals, and to calculate a reliable speed value; and to identify sensor faults based on the collected sensor pulse signals and send alarm signals.

[0092] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for speed measurement of maglev trains based on sleeper detection, characterized in that, include: Six sensors are arranged at certain intervals under the maglev train body; During normal operation, the average of the time difference between the rising edges of the six sensor signals is calculated, and the actual running speed of the train is calculated based on the principle that speed equals distance divided by time. Calculate four sets of velocity values, grouping each group into three adjacent sensors; When the sensor malfunctions or occasionally loses pulse signals, the fault is identified based on the different fault conditions of the sensor, and a reliable speed value is calculated. Based on the collected sensor pulse signals, sensor faults are identified and alarm signals are sent. During normal operation, the speed measurement system samples signals from six sensors: S1, S2, S3, S4, S5, and S6. The average of the rising time differences of these six signals is calculated. Based on the principle that speed equals distance divided by time, the process includes: Step S100: Selection of sampling time base and bit width; Step S200: Speed ​​calculation; calculate the time difference between the rising edges of two adjacent pulses; the formulas for speed and frequency calculation are: ； It also includes a self-test process, in which a standard pulse signal is sent from the system to the proximity sensor. The sensor receives the pulse signal and returns a corresponding pulse signal to the speed measurement system. The speed measurement system checks whether the sensor is faulty by retesting the pulse signal. At the same time, the distance between two adjacent sensors is calculated and corrected by using the time and speed of the standard pulse, in order to solve the problem of speed measurement accuracy caused by the error in the installation spacing between each adjacent sensor.

2. The method for measuring the speed of a maglev train based on sleeper detection according to claim 1, characterized in that, It also includes a speed measurement optimization process, which includes: under normal operating conditions, with the direction already determined, taking the positive direction of vehicle operation, taking S1, S2, and S3 as one group, taking S2, S3, and S4 as the second group, taking S3, S4, and S5 as the third group, and taking S4, S5, and S6 as the fourth group; collecting the rising edge time t1 of S1 and S2 in the first group and outputting speed 1; collecting the rising edge time t2 of S2 and S3 in the second group and outputting speed 2; collecting the rising edge time t3 of S3 and S4 in the second group and outputting speed 3; collecting the rising edge time t4 of S4 and S5 in the second group and outputting speed 4; ORing the four speed outputs CS1, CS2, CS3, and CS4 to form a composite CS, and outputting the speed at each falling edge of CS.

3. The method for measuring the speed of a maglev train based on sleeper detection according to claim 1, characterized in that, It also includes a speed measurement optimization process, which includes: when the sensor occasionally malfunctions, S3 is used to monitor whether S2 has lost pulses. If there are lost pulses, when S3 rises, t1 is still at a high level. At this time, t1 is set to a low level, and the time of the first group is measured as S1-S3, and the distance traveled is calculated. The measured time t1 is divided by 2 to obtain the speed output of the first group. Since S2 loses pulses, S2-S3 of the second group fails, and the second group has no speed output at this time, nor does it generate CS2. The third group can output the speed of S3-S4 normally.

4. The method for measuring the speed of a maglev train based on sleeper detection according to claim 1, characterized in that, The process also includes a speed measurement optimization procedure, which includes: when a sensor fails, S3 is used to monitor whether S2 has lost pulses. If there are lost pulses, when S3 rises, t1 is still at a high level. At this time, t1 is set to a low level, and the time of the first group is measured as S1-S3, the running distance value. The measured time t1 is divided by 2 to obtain the speed output of the first group. Since S2 loses pulses, S2-S3 of the second group fails, and the second group has no speed output at this time, nor does it generate CS2. The third group can output the speed of S3-S4 normally. When one of S3, S4, S5, or S6 is faulty, and there is a lost pulse state, the speed output calculation method is as follows: V1, V2, V3, and V4 are the speed values ​​processed in FIFO mode at the rising edge of synthesized CS. Each time the speed is updated, the last updated value in V1, V2, V3, and V4 is replaced with the currently updated value; the maximum and minimum values ​​in V1, V2, V3, and V4 are averaged, and the abnormal value in the state of lost pulse when one of S3, S4, S5, or S6 is faulty is discarded.

5. The method for measuring the speed of a maglev train based on sleeper detection according to claim 1, characterized in that, It also includes a speed measurement optimization process, which includes: when multiple sensors fail, when any two sensors fail, the direction and speed magnitude can be determined normally; when three sensors fail, the direction cannot be determined, but the speed magnitude can be determined, and in this case, the speed is set to a speed fault state and the speed is not output; in other cases like this, the direction and speed magnitude can be determined; when four sensors fail, as long as two adjacent sensors are normal, the direction and speed magnitude can be determined, but if they are not adjacent, the direction and speed magnitude cannot be determined.

6. The method for measuring the speed of a maglev train based on sleeper detection according to claim 1, characterized in that, The system also includes a speed measurement optimization process, which includes: speed calculation; generating a high level V between the rising edges of two adjacent signals, counting the high level to obtain a count value n; generating a high level with a ds delay of 16us at the falling edge of V; generating a high level as of 8us 8us after the falling edge of V; generating a high level with a bs delay of 16us 16us 16us after the falling edge of V; generating a high level with a cs delay of 8us 24us after the falling edge of V; wherein the rising edge of ds is used to update the value of the speed count register of the adjacent signal group, ORing the four groups of as to synthesize a new as, and at the rising edge of as, based on the high level states of the four groups of ds. The process involves: assigning the speed count register where DS is high to the total speed register; ORing the four speed count registers (BS) to create a new speed count register (BS); updating the four speed channel registers at the rising edge of BS, replacing the last updated value with the latest value; comparing the speed values ​​of the four speed channels at the falling edge of BS, removing the maximum and minimum values, and assigning the average of the two middle values ​​to the speed output register; finally, ORing the four speed count registers (CS) to create a new speed output register (CS); and checking if the speed output register is greater than a set threshold at the rising edge of CS. If it is, the speed output register is used as the speed output; if it is less than or equal to the threshold, the speed count register where BS is high is used as the speed output.

7. The method for measuring the speed of a maglev train based on sleeper detection according to claim 1, characterized in that, It also includes a speed measurement optimization process, which includes: speed sensor fault judgment; taking the rising edge of the pulses of the six axes respectively to form a CS, ORing the CS of the six axes, accumulating CS to 31, and at the same time calculating the pulse count of each axis during this period, with a maximum of 7. When CS reaches 31, it is determined that the pulse count of each axis is less than 1, and a fault is judged; when CS reaches 32, the pulse count of each axis is cleared.

8. A system for measuring the speed of a maglev train based on sleeper detection according to any one of claims 1 to 7, characterized in that, include: Six sensors are arranged at certain intervals under the maglev train body; The calculation unit is used to sample the time difference of the rising edges of six sensor signals during normal operation and calculate their average. Based on the principle that speed equals distance divided by time, it calculates the actual running speed of the train. It calculates four sets of speed values, with three adjacent sensors as a group. The identification unit is used to identify faults based on different sensor fault conditions when the sensor fails or when there is occasional loss of pulse signals, and to calculate a reliable speed value. Based on the collected sensor pulse signals, the system identifies sensor faults and sends alarm signals.

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