Retarder working condition detection method and device and storage medium

Abstract

The invention discloses a retarder working condition detection method and device and a storage medium, and relates to the technical field of retarder measurement, and the method comprises the steps: carrying out the statistics of pulse signals generated by the state change of a Hall switch, and obtaining the pulse number corresponding to the pulse signals; according to a stroke calculation rule, the pulse number is substituted for segmentation operation, and a stroke difference value corresponding to the piston is obtained; substituting the time interval of the periodic change of the pulse signal and the preset distance between the adjacent hubs of the train compartment into a speed formula, and calculating to obtain the passing speed of the train; and comparing the travel difference value, the duration from pulse signal triggering to stopping and the train passing speed according to a preset fault judgment rule, and judging the fault type corresponding to the retarder. The problem that the detection effect of the retarder is not good is solved, and the durability, the fault detection rate and the diagnosis precision of working condition detection of the retarder are improved.

Description

Technical Field

[0001] This application relates to the field of deceleration top measurement technology, and in particular to a method, device and storage medium for detecting the working condition of a deceleration top. Background Technology

[0002] In railway transportation yards, speed reduction jacks are key equipment for controlling train speed and ensuring operational safety. Currently, speed reduction jack inspection still relies on manual checks. Workers manually verify the integrity of the mechanical structure and the effectiveness of the function of the speed reduction jack. This method is not only inefficient but also prone to omissions due to human error, resulting in poor inspection results.

[0003] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of this application is to provide a method, device and storage medium for detecting the working condition of deceleration tops, in order to solve the technical problem of poor detection effect of deceleration tops.

[0005] To achieve the above objectives, this application proposes a detection device for a deceleration top, the device comprising: A magnetic encoder wheel has multiple magnets spaced apart around its circumference. The edge of the magnetic encoder wheel contacts a deceleration top piston, so that the movement of the deceleration top piston can drive the magnetic encoder wheel to rotate. A Hall switch is deployed on the plane of the magnetic encoder wheel, such that when the magnetic encoder wheel rotates and drives the magnet to pass the Hall switch, the state of the Hall switch is changed. A signal acquisition unit, connected to the Hall switch, is used to acquire the state of the Hall switch and send it to the data processing unit.

[0006] To achieve the above objectives, this application proposes a method for detecting the working condition of a deceleration top, the method comprising: The number of pulses corresponding to the pulse signals generated by the changes in the state of the Hall switch is obtained by counting the pulse signals. The stroke difference corresponding to the piston is obtained by substituting the pulse number into the stroke calculation rules and performing segmented calculations. The train speed is calculated by substituting the time interval of the periodic change of the pulse signal and the preset distance between adjacent wheel hubs of the train car into the speed formula. By comparing the travel difference, the duration from pulse signal triggering to stop, and the train's passing speed with preset fault judgment rules, the fault type corresponding to the deceleration top is determined.

[0007] In one embodiment, the Hall switch detects the alternating changes in magnetic poles generated when the piston drives the magnetic encoder wheel to rotate, and generates a magnetic pole change signal. The Hall switch switches its state according to the magnetic pole change signal, generating the pulse signal; The number of pulses corresponding to the periodically changing pulse signal is obtained by statistically analyzing the pulse signal.

[0008] In one embodiment, based on the periodic change of the pulse signal, the number of pulses corresponding to the downward rotation direction of the piston and the number of pulses corresponding to the upward rotation direction of the piston are distinguished to obtain the number of pulses corresponding to the downward and upward rotation directions of the piston. Based on the number of pulses in the corresponding rotational directions of the piston's downward and upward movements, calculate the difference between the two types of pulse counts and output the pulse count difference. Based on the aforementioned travel calculation rules, the pulse quantity difference is calculated proportionally to generate the travel difference.

[0009] In one embodiment, the trigger signal generated when the train car wheel hub passes over the deceleration top is detected, the trigger signals corresponding to two consecutive wheel hubs are distinguished, and the trigger signals of the two consecutive wheel hubs are output; Based on the trigger signals of two consecutive wheel hubs, the time point when each trigger signal is generated is recorded to determine the trigger time point corresponding to the two consecutive wheel hubs; Based on the trigger time points corresponding to two consecutive wheel hubs, the difference between the subsequent trigger time point and the previous trigger time point is calculated to obtain the time interval between two consecutive wheel hubs of the train car passing over the deceleration top.

[0010] In one embodiment, the original speed value is obtained by dividing the preset distance by the time interval based on the time interval and the preset distance between adjacent wheel hubs of the train car; Invalid original velocity values ​​caused by the time interval being zero or negative are removed, and original velocity values ​​that conform to physical meaning are retained to determine the valid original velocity values; Based on a preset speed unit standard, the unit of the effective original speed value is converted to determine the train's passing speed.

[0011] In one embodiment, the set of parameters to be diagnosed is determined by integrating the stroke difference, the duration of the piston's up-and-down movement during the deceleration cycle, and the train's passing speed. Based on the set of parameters to be diagnosed, the system matches and compares them with the preset fault judgment rules in the database to determine the target rule entries that the parameter set conforms to. Based on the target rule entries, the corresponding fault type of the deceleration top is identified.

[0012] In one embodiment, the target rule entry is parsed to extract the fault judgment conditions contained in the target rule entry; Based on the fault judgment conditions, the set of parameters to be diagnosed is compared with the fault judgment conditions one by one to determine the comparison result between the set of parameters to be diagnosed and the fault judgment conditions. Based on the comparison results, determine whether the parameter to be diagnosed fully meets all the fault judgment conditions of the target rule entry, and output the judgment result; If the determination result is a complete match, then according to the preset correspondence between rule entries and fault types, the corresponding fault type is selected from the target rule entries, and the preliminary matched fault type is output. The validity of the initially matched fault type is verified to confirm the consistency between the initially matched fault type and the actual working condition characteristics of the deceleration top, and the fault type corresponding to the deceleration top is output.

[0013] In addition, to achieve the above objectives, this application also proposes a deceleration top detection device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the deceleration top working condition detection method described above.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the deceleration top condition detection method described above.

[0015] This application provides a method for detecting the working condition of a deceleration top, including detecting the alternating changes in magnetic poles caused by the piston driving a magnetic encoder wheel to rotate along the corresponding rotation direction within a deceleration cycle, generating a pulse signal corresponding to the rotation direction and counting the number of pulses, and then calculating the stroke difference of the piston's vertical movement within a deceleration cycle according to the stroke calculation rules based on the number of pulses corresponding to different rotation directions within a deceleration cycle. Simultaneously, the train passing speed is calculated according to the speed formula based on the time interval recorded when two consecutive wheel hubs of the train car pass over the deceleration top in sequence and the preset distance between adjacent wheel hubs of the train car. Finally, based on the stroke difference, the duration of the piston's vertical movement within the deceleration cycle, and the train passing speed, the fault type corresponding to the deceleration top is identified according to the preset fault judgment rules. This application overcomes the technical problems of traditional deceleration top detection, such as easy wear of contact sensors, inaccurate fault diagnosis due to the ability to detect only a single parameter, and lack of vehicle speed feedback function. It realizes quantitative detection of the piston's bidirectional movement synchronously through non-contact magnetic encoding, fault diagnosis through multi-parameter fusion, and real-time vehicle speed monitoring.

[0016] In summary, this application overcomes the technical problem of poor detection effect of deceleration tops by using bidirectional magnetic coding for deceleration top fault detection, combined with multi-parameter fusion analysis and non-contact detection method, improves the durability, fault detection rate and diagnostic accuracy of deceleration top working condition detection, and expands the vehicle speed monitoring function, providing more comprehensive and reliable technical support for deceleration top operation and maintenance. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the hardware structure of this application; Figure 2 This is a flowchart illustrating the second embodiment of the deceleration top working condition detection method of this application; Figure 3 This is a schematic diagram of the hardware operating environment of this application; Figure 4 This is a schematic diagram of the diagnostic process for this application; Figure 5 This is a flowchart illustrating the eighth embodiment of the deceleration top working condition detection method of this application; Figure 6 This is a schematic diagram of the system architecture of this application; Figure 7 This is a schematic diagram of the detection device for the deceleration top in this application.

[0020] Label: Explanation of icon numbers: 1. Piston; 2. Magnetic encoder wheel; 3. Hall switch; 4. Signal acquisition unit.

[0021] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] In related technologies, the inspection of deceleration jacks still relies on manual inspection. Workers verify the integrity of the mechanical structure and the effectiveness of the function of the deceleration jacks by manual operation. This method is not only inefficient, but also prone to omissions due to human factors, resulting in poor inspection results for deceleration jacks.

[0024] This application provides a solution: First, the pulse signals generated by the changes in the state of the Hall switch are statistically analyzed to obtain the number of pulses corresponding to the pulse signals. Then, the number of pulses is substituted into the stroke calculation rules to perform segmented calculations to obtain the stroke difference value corresponding to the piston. Next, the time interval of the periodic changes of the pulse signals and the preset distance between the adjacent wheel hubs of the train car are substituted into the speed formula to calculate the train passing speed. Finally, the stroke difference value, the duration from the triggering to the stopping of the pulse signal, and the train passing speed are compared by a preset fault judgment rule to determine the fault type corresponding to the deceleration top.

[0025] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0026] This application provides a detection device for a deceleration top, referring to... Figure 1 , Figure 1 This is a schematic diagram of the hardware structure of this application.

[0027] like Figure 1As shown, the deceleration top magnetic signal detection device includes: a piston 1, a magnetic encoder wheel 2, a Hall switch 3, and a signal acquisition unit 4. The Hall switch 3 is positioned circumferentially outside the magnetic encoder wheel 2, within the effective area where the magnetic field changes generated by the alternating circumferential magnetic poles of the magnetic encoder wheel 2 during rotation can be sensed by the Hall switch 3. The Hall switch 3 senses the alternating changes in the magnetic poles of the magnetic encoder wheel 2 during rotation and outputs a corresponding electrical signal. Optionally, the Hall switch 3 can be a high-sensitivity magnetic field sensing element, and can adjust the level of the output electrical signal according to the proximity and distance of different magnetic poles of the magnetic encoder wheel 2. The magnetic encoder wheel 2 has multiple magnets embedded at circumferential intervals and contacts the edge of the piston 1. The piston 1 is connected to the deceleration top; the up-and-down movement of the deceleration top drives the piston 1 to move up and down accordingly, thereby driving the magnetic encoder wheel 2 to rotate. The acquisition unit 4 is connected to the Hall switch 3 and is used to acquire the electrical signal output by the Hall switch 3. When the deceleration top drives the piston 1 to move, which in turn drives the magnetic encoder wheel 2 to rotate, the magnet generates an electrical signal through the Hall switch 3 along with the wheel. The signal acquisition unit 4 captures the electrical signal and transmits it to the subsequent data processing unit through the communication interface.

[0028] Because the alternating changes in magnetic poles cause the electrical signal output by Hall switch 3 to change periodically, the periodicity of the electrical signal reflects the rotational state of the magnetic encoder wheel 2. Therefore, the subsequent data processing unit can analyze parameters such as pulse frequency and switching pattern of the electrical signal collected by signal acquisition unit 4 to determine the rotation of magnetic encoder wheel 2, thereby reflecting the motion state of piston 1 and deceleration top. Furthermore, the subsequent data processing unit can also determine the current detection progress based on the detection process of deceleration top and control the corresponding components in the deceleration top magnetic signal detection device to perform corresponding actions.

[0029] Furthermore, as shown in the figure, the magnetic encoder wheel 2 also includes a wheel body and multiple N-pole and S-pole magnets alternately arranged circumferentially on the wheel body. The magnetic encoder wheel 2 rotates through contact with the piston 1, as the deceleration head drives the piston 1 to move up and down. With the continuous movement of the piston 1, the magnetic encoder wheel 2 continues to rotate, causing the Hall switch 3 to continuously sense the alternating changes in the magnetic poles. When the magnetic encoder wheel 2 rotates, the Hall switch 3 senses the N-pole or S-pole and outputs different electrical signals. These electrical signals are directly acquired by the signal acquisition unit 4 or acquired and pre-processed to more accurately present the characteristics of the electrical signals, facilitating subsequent data processing.

[0030] Those skilled in the art will understand that the structure of the deceleration top magnetic signal detection device shown in the figure does not constitute a limitation on the device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0031] It should be noted that the executing entity in this embodiment can be a deceleration top magnetic signal detection device, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or detection device capable of performing the above functions. This embodiment does not specifically limit it in this regard. The following uses a deceleration top magnetic signal detection device as an example to describe this embodiment and the following examples.

[0032] Based on this, embodiments of this application provide a method for detecting deceleration top conditions, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the deceleration top working condition detection method of this application.

[0033] In this embodiment, the deceleration top working condition detection method includes steps S10~S40: Step S10: Count the pulse signals generated by the change in the state of the Hall switch to obtain the number of pulses corresponding to the pulse signals.

[0034] In this embodiment, the Hall switch state change refers to the switching between two operating states: a high-level output during conduction and a low-level output during cutoff, caused by the magnetic encoder wheel driving the magnet to pass through. The pulse signal refers to the alternating high and low level signal generated when the Hall switch state changes. The pulse count refers to the specific number of pulse signals generated by the Hall switch.

[0035] As an optional implementation, the system receives the state change signal generated by the Hall switch as the magnet passes by due to the rotation of the magnetic encoder wheel. When the Hall switch is detected to switch from off to on, a count is triggered and recorded as a pulse signal. When it switches from on to off, another count is triggered and recorded as a pulse signal. The system continuously monitors the state changes, accumulating a pulse for each switch. Simultaneously, the rotation phase of the magnetic encoder wheel is correlated to ensure that each state change corresponds to a valid pass of the magnet, eliminating invalid switches caused by brief signal fluctuations. The final count is the total number of pulses corresponding to the pulse signal within that time period. This method is suitable for scenarios with high real-time counting requirements, providing rapid feedback on the rotation of the magnetic encoder wheel and offering immediate data support for subsequent real-time calculation of the piston stroke.

[0036] As an alternative implementation, the state change signal output by the Hall switch is first buffered for a preset duration. During the buffering period, the time point and direction of the state transition are recorded synchronously, ending at the point of conduction and then from conduction to cutoff. After the buffering ends, the recorded transition information is filtered, excluding continuous transitions with intervals less than a preset threshold, which are identified as false signals caused by electromagnetic interference, and retaining valid transitions with intervals conforming to the rotation cycle of the magnetic encoder wheel. The number of valid transitions is then counted, with each valid transition corresponding to one pulse signal. Finally, the number of valid transitions is summed to obtain the pulse count corresponding to each pulse signal. This method is suitable for scenarios requiring high counting accuracy and susceptible to electromagnetic interference, ensuring the accuracy of the pulse count and providing reliable data for subsequent accurate calculation of travel differences and fault type determination, reducing the risk of misjudgment due to data errors.

[0037] Step S20: Substitute the pulse number into the stroke calculation rules to perform segmented calculations and obtain the stroke difference value corresponding to the piston.

[0038] In this embodiment, the stroke calculation rule refers to a pre-set rule that associates the number of pulses with the actual stroke of the piston, and then calculates the stroke difference based on the difference in the number of pulses. The stroke difference refers to the difference between the actual upward stroke and the actual downward stroke of the piston within one deceleration cycle.

[0039] As an optional implementation, the pulse signal output from the Hall switch is received, and the initial state and the signal after the first state switch are recorded. Then, the signal after the second state switch is monitored. Based on the polarity arrangement of the circumferential magnets of the magnetic encoder wheel, the pulse count is divided into upward pulse count and downward pulse count. Then, the preset calculation formula in the stroke calculation rule is called to calculate the upward and downward pulse counts respectively, obtaining the piston's upward and downward stroke values. Finally, the calculation is completed according to the fixed logic of subtracting the upward stroke value from the downward stroke value in the stroke calculation rule, obtaining the corresponding stroke difference value for the piston. The correspondence between the data during the decomposition and calculation process is recorded for subsequent verification. This method is suitable for scenarios where the transmission ratio between the magnetic encoder wheel and the piston is stable and can quickly output the stroke difference value.

[0040] As an alternative implementation, the method first receives a statistically calculated number of pulses and divides these pulses into multiple continuous intervals according to the stroke calculation rules. The division is based on the spacing distribution of the circumferential magnets on the magnetic encoder wheel. Then, the calculation formula corresponding to each interval is called to calculate the pulse count for each interval, obtaining the piston stroke value for the corresponding stage. Next, the stroke values ​​for all stages are summed to obtain the total piston stroke. Simultaneously, the sum of the strokes for the upward and downward stages is extracted. Finally, the sum of the strokes for the downward stage is subtracted from the sum of the strokes for the upward stage to obtain the stroke difference for the piston. This method adapts to fluctuations in the transmission ratio between the magnetic encoder wheel and the piston, significantly improving the accuracy of the stroke difference calculation.

[0041] Step S30: Substitute the time interval of the periodic change of the pulse signal and the preset distance between adjacent wheel hubs of the train carriage into the speed formula to calculate the train passing speed.

[0042] In this embodiment, two consecutive wheel hubs of the train car refer to two adjacent wheel components arranged sequentially along the direction of travel on the bottom of the train car, used to support the car and contact the track. The time interval refers to the difference in duration between the moment the first wheel hub begins to press against the deceleration cap and the moment the second wheel hub begins to press against the deceleration cap. The preset distance refers to a fixed distance predetermined in advance between the central axes of two adjacent wheel hubs on the bottom of the train car. The speed formula is a calculation logic that converts distance and time interval into speed using the ratio of distance to time. The train passing speed refers to the instantaneous speed of the train when it passes the location of the deceleration cap during its travel.

[0043] As an optional implementation, the method acquires the contact start time of each of two consecutive wheel hubs as they pass over the deceleration platform. The contact start time of the subsequent wheel hub is subtracted from that of the preceding wheel hub to obtain the time interval between the two wheel hubs passing over the deceleration platform. Then, a pre-stored preset distance between adjacent wheel hubs in the train car is used, and the calculation is performed according to the preset distance divided by the time interval to obtain a preliminary speed result. This preliminary result is then validated to determine if it falls within the reasonable range for conventional train operating speeds. If the preliminary result is within the reasonable range, it is determined as the final train passing speed. If the preliminary result exceeds the reasonable range, the calculation result is marked as abnormal, and the contact start times of the two wheel hubs are acquired again, repeating the above calculation process. This method only requires acquiring one set of contact times for two consecutive wheel hubs, eliminating the need to process multiple sets of data, and can quickly output the train passing speed, meeting the requirements for real-time detection.

[0044] As an alternative implementation, the starting times of the contact points of three or more sets of adjacent wheel hubs of train cars successively passing over the deceleration platform are continuously collected. For each set of time data, the corresponding time interval is calculated. After obtaining multiple time interval data, the differences between the time interval data are compared, and abnormal interval values ​​that deviate significantly from the majority of time interval data are eliminated. Then, the average duration of the remaining valid time interval values ​​is calculated. Subsequently, a pre-stored preset distance between adjacent wheel hubs of train cars is called, and the initial speed is calculated according to the ratio of the preset distance to the average duration. Then, each valid time interval value is substituted into the calculation logic to obtain a single speed value. The deviation of all single speed values ​​from the initial speed is compared. If all deviations are within the allowable range, the initial speed is determined as the train passing speed. If there are deviations exceeding the allowable range, multiple sets of contact point starting times are collected again, and the entire process is repeated. This method, through multiple sets of data collection, outlier elimination, and average value calculation, significantly reduces the impact of single data anomalies on the results.

[0045] Step S40: By comparing the travel difference, the duration from pulse signal triggering to stop, and the train passing speed with the preset fault judgment rules, the fault type corresponding to the deceleration top is determined.

[0046] In this embodiment, the duration from pulse signal triggering to stopping refers to the total time from the piston starting its upward movement to completing its downward movement and ending a full reciprocating motion. The preset fault judgment rule refers to a pre-set judgment logic that associates the stroke difference, piston movement duration, train speed, and deceleration top fault type. The fault type refers to the possible fault categories that may occur at the deceleration top, such as piston jamming, insufficient air pressure, or insufficient buffering performance.

[0047] As an optional implementation, the stroke difference, the duration of the piston's up-and-down movement during the deceleration cycle, and the train's passing speed are integrated to form a complete set of parameters to be judged. A preset fault judgment rule library is then invoked, where each fault type corresponds to a specific set of parameter range thresholds. The parameters to be judged are compared sequentially with the corresponding thresholds for each fault type, in the order of stroke difference, piston movement duration, and train passing speed. If all three sets of parameter thresholds for a certain fault type completely cover the parameters to be judged, then the fault type is directly determined to be the fault type corresponding to the deceleration peak. If the thresholds for all fault types cannot completely cover the parameters to be judged, it is marked as an unmatched fault type, and the current parameter set is retained for subsequent rule optimization. This method has a direct judgment process, requires no complex scoring and weight calculations, and can quickly output the fault type.

[0048] As an alternative implementation, weights are assigned to the stroke difference, the duration of the piston's up-and-down movement during the deceleration cycle, and the train's passing speed. Each set of parameters is then compared to a preset standard parameter range, and a score is given based on the degree of deviation from the standard range; the smaller the deviation, the higher the score. The scores of the three parameters are weighted and summed to obtain a comprehensive score. Subsequently, the correspondence between the comprehensive score and fault type in the preset fault judgment rules is invoked to determine the score interval to which the comprehensive score belongs, and then the corresponding fault type is matched. Finally, the matching result is verified a second time by comparing the current parameter set with the typical parameter characteristics of the matched fault type. If the characteristics match, the result is confirmed; otherwise, the weights are readjusted and the scoring and matching process is repeated. The weights are preset based on the degree of influence of each parameter on fault judgment. This method, through weight setting and comprehensive scoring, can take into account the influence of each parameter on fault judgment and has high tolerance for slight parameter deviations.

[0049] For example, in a freight train scenario, the distance L between adjacent wheel hubs in the carriage is preset to 1.5m. The deceleration top is equipped with a miniature rubber wheel (made of high-friction rubber material, tightly attached to the piston side by a spring mechanism), a magnetically encoded wheel with 12 equidistant neodymium magnet rods (alternating N / S poles), and a Hall switch array fixed to the wheel axle bracket. When the train wheel passes over the deceleration top, the piston moves downward, driving the rubber wheel to rotate counterclockwise, and the Hall switch count N1 is 24. After the wheel leaves, the piston moves upward, driving the rubber wheel to rotate clockwise, and the Hall switch count N2 is 20. ΔN = |24 - 20| = 4 is calculated. The piston rebound start time t1 = 0.3s and end time t2 = 0.8s are recorded, resulting in T = 0.8 - 0.3 = 0.5s. The times when two consecutive wheel hubs pass over the deceleration top are recorded as t31 = 1.2s and t32 = 2.2s, and V = 1.5 / (2.2 - 1.2) × 3.6 = 5.4 km / h is calculated. If the threshold value of ΔN is 3 and the standard value of T is 0.4s, it is determined that the deceleration top has a piston jamming and insufficient air pressure fault.

[0050] Furthermore, referring to Figure 3 , Figure 3This is a schematic diagram of the hardware operating environment for this application. During the deceleration top detection process, the piston movement drives the magnetic encoder wheel to rotate. The magnetic field changes generated by the alternating magnetic poles of the magnetic encoder wheel are sensed by a Hall switch, and the electrical signal output by the Hall switch is transmitted to the signal acquisition unit. The signal acquisition unit sends the acquired signal to the data processing unit. After processing the signal, the data processing unit sends the data to the cloud platform via NB-IoT and RS485 transmission. The data processing unit, NB-IoT transmission module, RS485 transmission module, and cloud platform can be set up separately, with each module independently arranged and communicating with each other via communication lines. Alternatively, the data processing unit can be integrated with the NB-IoT and RS485 transmission modules and then separately arranged from the cloud platform. Furthermore, the data processing unit, NB-IoT, RS485, and cloud platform can be integrated into a unified device, allowing for flexible selection of the arrangement based on actual scenario requirements.

[0051] By using magnetic encoder wheels, miniature rubber wheels, and Hall switch arrays, the problems of low efficiency and poor accuracy of traditional manual inspection are solved, thereby improving the durability, fault detection rate, and diagnostic accuracy of deceleration top condition inspection.

[0052] Based on any of the above embodiments, in Embodiment 3 of this application, step S10 includes steps A11 to A13: Step A11: The Hall switch detects the alternating changes in magnetic poles generated when the piston drives the magnetic encoder wheel to rotate, and generates a magnetic pole change signal.

[0053] In this embodiment, the magnetic pole change signal refers to the electrical signal output by the Hall switch after it detects the magnetic pole switching, which reflects the timing and direction of the magnetic pole change.

[0054] As an optional implementation, the Hall switch is fixed to a bracket on the outside of the magnetic encoder wheel, with the sensing surface facing the circumferential magnetic pole distribution area of ​​the magnetic encoder wheel and maintaining a fixed distance from the wheel body. When the piston moves, it drives the magnetic encoder wheel to rotate around its axis, and the N pole and S pole on the wheel surface sequentially approach the sensing surface of the Hall switch as it rotates. When the Hall switch senses the approach of the N pole, its internal circuit turns on and outputs a high-level signal; when it senses the approach of the S pole, its internal circuit turns off and outputs a low-level signal. As the magnetic encoder wheel continues to rotate, the N pole and S pole alternately pass by, and the Hall switch continuously switches between high and low levels. The resulting alternating high and low level signal is the magnetic pole change signal. This method is suitable for scenarios with high real-time signal requirements and stable ambient magnetic fields, providing a basic signal source for subsequent pulse counting.

[0055] As an alternative implementation, a ring track is set inside the magnetic encoder wheel, and a Hall switch is mounted on a slider that can slide along the track. The radial distance between the Hall switch and the magnetic poles is changed by adjusting the position of the slider. A metal shield is added to the outside of the Hall switch to isolate stray external magnetic fields. When the piston drives the magnetic encoder wheel to rotate, the magnetic poles on the wheel surface alternately pass through the sensing area of ​​the Hall switch. The shield filters out external magnetic field interference, and the Hall switch only responds to changes in the magnetic poles of the magnetic encoder wheel. A first-type characteristic signal is output when the N pole is sensed, and a second-type characteristic signal is output when the S pole is sensed. The rising and falling edges of the signal are shaped by internal circuitry to remove signal jitter and generate a regular magnetic pole change signal. This method outputs a more stable magnetic pole change signal, suitable for scenarios with complex environmental magnetic fields and varying magnetic pole strengths in the magnetic encoder wheel.

[0056] Step A12: The Hall switch switches its state according to the magnetic pole change signal and generates the pulse signal.

[0057] As an optional implementation, the magnetic pole change signal output by the Hall switch is received and filtered in real time to remove stray signals caused by environmental electromagnetic interference, retaining clear high-low level switching characteristics. The switching direction of the high and low levels is then analyzed. When the magnetic pole change signal exhibits a continuous switching of low, high, low levels with an increasing switching rate, the corresponding magnetic encoder wheel is determined to be in the first rotation direction, and a positive polarity pulse signal is generated. When the magnetic pole change signal exhibits a continuous switching of high, low, high levels with a decreasing switching rate, the corresponding magnetic encoder wheel is determined to be in the second rotation direction, and a negative polarity pulse signal is generated. During the switching process, a pulse signal of the corresponding polarity is output after each complete high-low level cycle, ensuring that the pulse signal strictly corresponds to the rotation direction. This method has fewer signal processing steps, a fast pulse generation response speed, and can output pulses in real time following magnetic pole changes.

[0058] As an alternative implementation, the timing characteristics of the received magnetic pole change signal are extracted, the start and end times of each magnetic pole switch are recorded, and the time interval between two adjacent switches is calculated. Two preset timing threshold intervals are established, corresponding to the two rotation directions of the magnetic encoder wheel. When the calculated time interval remains within the first threshold interval, the magnetic encoder wheel is determined to be in the first rotation direction, and a rising edge-priority pulse signal is generated at a fixed time interval. When the time interval remains within the second threshold interval, the magnetic encoder wheel is determined to be in the second rotation direction, and a falling edge-priority pulse signal is generated. Simultaneously, the consistency between the timing interval and the rotation direction is checked in real time. If the interval deviates from the threshold, pulse output is paused, the direction is re-determined, and generation continues. This method is suitable for scenarios with complex electromagnetic environments and high requirements for pulse direction accuracy, and can reduce pulse direction errors caused by interference.

[0059] Step A13: Statistically analyze the periodically changing pulse signal to obtain the number of pulses corresponding to the pulse signal.

[0060] As an optional implementation, a periodically changing pulse signal is received, and the rising and falling edges of the signal are monitored in real time. Each detected rising or falling edge is considered a complete pulse and is counted. During the counting process, the rotation period of the magnetic encoder wheel is synchronously correlated to ensure that each signal change is within the effective range of the period, eliminating interference signals outside the period. The signal is continuously tracked until a complete period ends, at which point the counting stops and the total number of accumulated counts is recorded, obtaining the number of pulses corresponding to the pulse signal within that period. This method has strong real-time performance, can synchronously track pulse signal changes, has no counting delay, and is suitable for scenarios where the magnetic encoder wheel rotation is stable.

[0061] For example, in a scenario where the wheel hub of a passenger train presses against a deceleration platform, within a 0.7-second deceleration cycle, the piston drives a magnetically encoded wheel with 24 alternating N / S magnetic poles. During downward movement, the component rotates clockwise, and three fixed Hall sensor arrays detect the alternating magnetic pole changes, generating a magnetic pole change signal that includes high and low level switching. Based on this signal, a positive polarity pulse is generated during clockwise rotation (one pulse is output for each magnetic pole switch), and a negative polarity pulse is generated during counter-clockwise rotation (piston moving upward). By counting the pulses using dual counting channels, the number of pulses corresponding to clockwise rotation is 48, and the number of pulses corresponding to counter-clockwise rotation is 45. That is, the number of pulses in different rotational directions within one deceleration cycle is 48 and 45, respectively.

[0062] By combining a magnetic encoder wheel with a Hall switch, the problems of high false negative rate and pulse direction confusion in traditional single-sensor detection of magnetic pole changes are solved, thus improving the accuracy of fault detection.

[0063] Based on any of the above embodiments, in Embodiment 4 of this application, step S20 includes steps B11 to B13: Step B11: Based on the periodic change of the pulse signal, distinguish the number of pulses in the downward rotation direction of the piston from the number of pulses in the upward rotation direction of the piston, and obtain the number of pulses in the downward and upward rotation directions of the piston.

[0064] In this embodiment, piston downward movement refers to the process of the piston moving axially downward under the pressure of the hub. Piston upward movement refers to the process of the piston moving axially upward under the action of the restoring force.

[0065] As an optional implementation, the downward and upward movements of the piston correspond to two rotational directions of the magnetic encoder wheel, respectively, and the switching sequence of pulse signals under these two rotational directions is preset. After receiving the pulse signal, the initial signal switching sequence is monitored in real time, and the correspondence between the preset direction and the switching sequence is compared to determine the piston movement stage to which the current rotational direction of the magnetic encoder wheel belongs. The pulse signals within this stage are counted until a feature corresponding to the other direction is detected, indicating a piston movement stage switch. The counting of the previous stage is stopped, and the counting of the new stage begins. After the piston completes one full downward and upward movement, the counting results of the two stages are summarized to obtain the number of pulses corresponding to the downward and upward rotational directions of the piston. This method is suitable for scenarios where the magnetic encoder wheel rotates smoothly and there is little signal interference, and it can quickly distinguish the upward and downward stages of the piston and output the number of pulses.

[0066] As an alternative implementation, the pulse signal interval characteristics of the magnetic encoder wheel corresponding to the rotation direction during piston downward and upward movement are pre-stored. Multiple consecutive cycles of pulse signals are received, the interval time of each pulse is extracted and formed into a sequence; the current pulse interval sequence is compared with the preset downward and upward interval feature sequences, and the feature overlap is calculated. If the sequence with higher overlap is a downward feature sequence, it is determined that the pulse signal corresponds to piston downward movement and counted. If it is an upward feature sequence, it is determined that the corresponding piston is upward movement and counted. During piston movement, the interval sequence is continuously compared to dynamically confirm the movement stage and avoid misjudgment of the stage. After the piston completes one downward and upward movement, the counting results of the two stages are output respectively, obtaining the number of pulses corresponding to the rotation direction of piston downward and upward movement. This method is suitable for scenarios where the magnetic encoder wheel rotation has slight jitter and is susceptible to electromagnetic interference, ensuring the accuracy of the piston's upward and downward pulse count statistics, and providing reliable data for subsequent accurate calculation of stroke difference and determination of deceleration top fault type.

[0067] Step B12: Based on the number of pulses in the corresponding rotational directions of the piston's downward and upward movements, calculate the difference between the two types of pulse counts and output the pulse count difference.

[0068] In this embodiment, the difference between the two types of pulse quantities refers to the numerical difference between the two pulse quantities.

[0069] As an optional implementation, the method receives the number of pulses corresponding to the downward rotation of the piston and the number of pulses corresponding to the upward rotation of the piston. First, it verifies the validity of both counts, confirming that they are continuous counts within a complete deceleration cycle. After successful verification, it directly subtracts the number of upward pulses from the number of downward pulses. If the result is positive, the original value is retained; if it is negative, the absolute value is taken. The original number of pulses used in the calculation is recorded synchronously as a basis for subsequent traceability. Finally, the calculation result is output as the pulse count difference. This method has a straightforward calculation logic, few steps, fast processing speed, no need for complex segmentation and weighting, and low computational resource requirements.

[0070] Step B13: Based on the stroke calculation rules, the pulse number difference is calculated proportionally to generate the stroke difference.

[0071] As an optional implementation, a preset travel calculation rule is first invoked to extract the fixed ratio between single pulses and travel. Then, the calculated pulse number difference is obtained, and this difference is multiplied by the travel corresponding to the single pulse. During the calculation, it is simultaneously verified whether the pulse number difference is within the preset valid range of the rule; if the difference is valid, the calculation result is retained. Finally, the calculation result is converted to units, and the final travel difference is generated and output. If the difference is invalid, it is marked as a calculation failure, and feedback is provided that the pulse number difference needs to be re-acquired. This method is suitable for scenarios where magnetic encoder wheels are newly installed or used for short periods, and where the accuracy requirements for travel difference are not high, and can meet the travel data requirements for basic fault diagnosis.

[0072] As an alternative implementation, a dynamic calibration process is initiated within the stroke calculation rules. This involves detecting the current magnetic pole distribution density of the magnetic encoder wheel, comparing the initial magnetic pole density with the current density, and calculating a proportional correction coefficient. Then, the pulse count difference is obtained, multiplied by the ratio of the initial single pulse to the stroke in the rules, and then multiplied by the proportional correction coefficient. The corrected calculation result is then verified to match the maximum stroke threshold of the deceleration top piston; if a match is found, the result is confirmed. Finally, the dynamically calibrated stroke difference is generated and output, while the proportional correction coefficient is stored for subsequent calculations and calibrations of the same component. This method is suitable for scenarios requiring long-term continuous use of the magnetic encoder wheel and high accuracy in stroke difference calculations.

[0073] For example, in the scenario of an electric train, its wheel hub passes over a GD-3 type deceleration top. During the 0.6-second deceleration cycle, pulse signals from the magnetically encoded wheel are acquired. The piston's downward movement corresponds to clockwise rotation, with 36 pulses. The piston's upward movement corresponds to counter-clockwise rotation, with 32 pulses. The pulse counts for the downward and upward rotation directions are distinguished as 36 and 32 respectively. The difference between the two types of pulse counts is calculated as 36-32=4, and the output pulse count difference is 4. According to the stroke calculation rule (one pulse corresponds to 0.2mm of stroke), 4×0.2=0.8mm is calculated proportionally, generating a stroke difference of 0.8mm.

[0074] By integrating the deceleration top with the magnetic encoder wheel, the problems of fixed single-pulse ratio in traditional manual measurement of stroke difference are solved, thus improving the accuracy of stroke difference calculation.

[0075] Based on any of the above embodiments, in Embodiment 5 of this application, before step S30, steps C11 to C13 are further included: Step C11: Detect the trigger signal generated when the train car wheel hub passes over the deceleration top, distinguish the trigger signals corresponding to two consecutive wheel hubs, and output the trigger signals of the two consecutive wheel hubs.

[0076] As an optional implementation, when the first hub passes over the deceleration top, the piston moves downward, causing the magnetic encoder wheel to rotate. A Hall switch detects the alternating changes in magnetic poles, generating a continuous pulse trigger signal. The start time and pulse sequence characteristics of this signal are recorded. After the first hub leaves, the piston moves upward, the magnetic encoder wheel rotates in the opposite direction, and the trigger signal is interrupted. When the second hub passes over, the piston moves downward again, the magnetic encoder wheel rotates forward, and the Hall switch generates continuous pulses again. The time interval between the restart time after the signal interruption and the end time of the first trigger signal, combined with the pulse sequence direction, is determined to be the second trigger signal. Both trigger signals are then marked and output. This method relies on the time interval between signal interruption and restart, has simple judgment logic, and responds quickly.

[0077] Step C12: Based on the trigger signals of two consecutive wheel hubs, record the time point when each trigger signal is generated, and determine the trigger time point corresponding to the two consecutive wheel hubs.

[0078] In this embodiment, the trigger time points corresponding to two consecutive wheel hubs refer to the times corresponding to the trigger signals of the two adjacent wheel hubs.

[0079] As an optional implementation, when the first hub passes over the deceleration top, the piston drives the magnetic encoder wheel to rotate. The Hall switch detects the change in magnetic poles and generates a trigger signal. The moment the rising edge of the first pulse of this trigger signal appears is recorded as the first trigger time point. After the first hub leaves the deceleration top, the trigger signal is interrupted, and the piston moves upward, driving the magnetic encoder wheel to rotate in the opposite direction. When the second hub passes over the deceleration top, the Hall switch again detects the change in magnetic poles and generates a trigger signal. The moment the rising edge of the first pulse of this trigger signal appears is recorded as the second trigger time point, thus determining the trigger time points corresponding to two consecutive hubs. This method is suitable for scenarios where the signal quality of the magnetic encoder wheel and the Hall switch is good, and can quickly and accurately obtain the trigger time points.

[0080] Step C13: Based on the trigger time points corresponding to two consecutive wheel hubs, calculate the difference between the subsequent trigger time point and the previous trigger time point to obtain the time interval between two consecutive wheel hubs of the train car passing over the deceleration top.

[0081] As an optional implementation, the trigger time points corresponding to two consecutive wheel hubs are obtained. The value of the preceding trigger time point is directly subtracted from the value of the following trigger time point, and the result is the time interval. Before calculation, the validity of the two trigger time points is verified by the source identifier of the trigger signal. If the verification passes, the subtraction operation is performed; if it fails, an anomaly is marked, and a valid trigger time point is obtained again before calculation. This method has a direct calculation process, short processing time, and can quickly output the time interval, meeting real-time requirements.

[0082] For example, in a scenario involving a high-speed train, when the wheel hubs of the train carriages pass over an ST-1 type deceleration platform, a piston inside the platform drives a magnetic encoder wheel with 20 alternating magnetic poles distributed circumferentially to rotate. A Hall sensor detects the change in magnetic poles and generates a trigger signal. When the first wheel hub passes over, the Hall sensor generates a trigger signal containing 30 consecutive pulses, marked as the trigger signal for the first wheel hub. After the first wheel hub leaves, the piston moves upward, causing the magnetic encoder wheel to rotate in the opposite direction, and the trigger signal is interrupted. Subsequently, when the second wheel hub passes over, the Hall sensor generates a trigger signal containing 30 consecutive pulses, marked as the trigger signal for the second wheel hub, and outputs the trigger signals for these two consecutive wheel hubs. Based on these two trigger signals, the time point of the rising edge of the first pulse of the first trigger signal is recorded as t1, and the time point of the rising edge of the first pulse of the second trigger signal is recorded as t2, determining the trigger time points t1 and t2 corresponding to the two consecutive wheel hubs. The difference between t2 and t1 is calculated, yielding a time interval of 0.5 seconds between the two consecutive wheel hubs of the train carriage passing over the deceleration platform.

[0083] By combining the magnetic encoder wheel on the deceleration top with the Hall switch, the problems of traditional photoelectric detection trigger signals being easily interfered with by light and having large time interval calculation errors are solved, thus improving the detection efficiency of the deceleration top.

[0084] Based on any of the above embodiments, in Embodiment Six of this application, step S30 includes steps D11 to D13: Step D11: Based on the time interval and the preset distance between adjacent wheel hubs of the train carriage, the original speed value is obtained by dividing the preset distance by the time interval.

[0085] In this embodiment, the original speed value refers to the initial value of the train's travel speed obtained through the above division operation without subsequent correction.

[0086] As an optional implementation, the time interval between two consecutive wheel hubs of a train car passing over the deceleration platform is retrieved, along with the preset distance between adjacent wheel hubs corresponding to the train model. It is confirmed that the time interval is not zero and the preset distance matches the current train model. If both parameters are valid, the preset distance is directly divided by the time interval to obtain a preliminary value. Only the unit of the value is standardized; no further correction is needed, and the converted value is directly output as the original speed value. If the time interval is zero or the preset distance does not match, the parameters are marked as abnormal, the calculation is paused, and feedback is sent indicating that valid parameters need to be retrieved again. This method has a simple calculation process, requires no complex parameter preprocessing or result comparison, and can quickly output the original speed value.

[0087] As an alternative implementation, the acquired time interval is first preprocessed by analyzing the pulse continuity of the trigger signal generated by the magnetic encoder wheel to obtain a corrected time interval. Then, the train model database is retrieved to reconfirm the preset distance between adjacent wheel hubs of the current carriage. Subsequently, the preset distance is divided by the corrected time interval to obtain a preliminary value. This preliminary value is compared with the historical original speed value range of the same train model under similar operating conditions. If the value is within the range, it is output as the original speed value. If it exceeds the range, the time interval correction result is re-verified against the preset distance, and the calculation is repeated before output. This method eliminates outliers through time interval preprocessing, reducing the impact of magnetic encoder wheel signal fluctuations.

[0088] Step D12: Eliminate invalid original velocity values ​​caused by the time interval being zero or negative, retain the original velocity values ​​that conform to physical meaning, and determine the valid original velocity values.

[0089] In this embodiment, a time interval of zero or negative refers to an abnormal situation where the difference in the triggering time of two consecutive wheel hubs of a train car passing over the deceleration top is zero or negative. An invalid original speed value refers to an original speed value calculated due to an abnormal time interval that does not conform to the actual physical laws of train movement. An original speed value that conforms to physical meaning refers to an original speed value where the time interval is positive and the calculation result is within the normal operating speed range of the train. A valid original speed value refers to the original speed value that, after screening, truly reflects the train's speed.

[0090] As an optional implementation, the original speed value is obtained by dividing a preset distance by a time interval, and the corresponding time interval data is retrieved simultaneously. The time interval is judged; if it is zero or negative, the corresponding original speed value is directly marked as invalid and discarded. If the time interval is positive, it is further verified whether the original speed value is within a reasonable range of normal train speed. If it is within a reasonable range, the original speed value is determined as valid and retained; if it exceeds a reasonable range, it is still marked as invalid and discarded. Simultaneously, the corresponding time interval and pulse signal characteristics are recorded for subsequent anomaly analysis. This method is suitable for scenarios with fast train operation and the need for real-time output of valid speed values, and can quickly eliminate obviously abnormal speed data.

[0091] Step D13: Based on the preset speed unit standard, convert the unit of the effective original speed value to determine the train's passing speed.

[0092] In this embodiment, the preset speed unit standard refers to a unit specification that is pre-set according to the needs of train operation monitoring and is uniformly used to represent train speed.

[0093] As an optional implementation, a preset speed unit standard is retrieved to clarify the target conversion unit and its corresponding conversion rules. Then, a valid original speed value is obtained, and its current unit is confirmed. Based on the correspondence between the current unit and the target unit, a preset conversion coefficient is extracted, and the valid original speed value is multiplied by the conversion coefficient. After calculation, the result is checked to see if it falls within the preset normal train passing speed range. If it is within the range, the result is determined as the train passing speed. If it exceeds the range, the conversion coefficient and the valid original speed value are rechecked, and the conversion is performed again before outputting the speed. This method relies only on preset coefficients and range verification, has fewer operational steps, is less time-consuming, can quickly output train passing speeds, and does not require additional historical data on train models, thus having low storage resource requirements.

[0094] For example, in a scenario where a high-speed train is decelerating, the preset distance between adjacent wheel hubs of the train carriage is 1.8 meters. Two consecutive wheel hubs pass over the JT-3 deceleration cap in sequence, resulting in a trigger time interval of 0.6 seconds. Based on this time interval and the preset distance, the original speed value is calculated by dividing 1.8 meters by 0.6 seconds, yielding a value of 3 meters per second. Cases with zero or negative time intervals (where the time interval is positive and the original speed value is within the normal operating speed range of the high-speed train) are eliminated. This original speed value is retained and determined as the valid original speed value. According to the preset speed unit standard (km / h), 3 m / s is converted to 10.8 km / h, determining the train's passing speed to be 10.8 km / h.

[0095] The combined action of the magnetic encoder wheel on the deceleration top and the Hall switch solves the problem of large speed calculation deviations caused by abnormal time intervals and inconsistent units in traditional speed detection, thus improving the accuracy of train speed calculation.

[0096] Based on any of the above embodiments, in Embodiment Seven of this application, step S40 includes steps E11 to E13: Step E11: Integrate the stroke difference, the duration of the piston's up-and-down movement during the deceleration cycle, and the train's passing speed to determine the set of parameters to be diagnosed.

[0097] In this embodiment, the set of parameters to be diagnosed refers to the combination of parameters that integrate the stroke difference, the duration of piston up and down movement, and the train passing speed for subsequent fault diagnosis.

[0098] As an optional implementation, the stroke difference, the duration of the piston's up-and-down movement during the deceleration cycle, and the train's passing speed are retrieved. The validity of these three parameters is then verified: the stroke difference must be within a reasonable range of the piston's physical stroke difference, the duration must be positive and consistent with the deceleration cycle length, and the train's passing speed must conform to the normal train speed range. Abnormal parameters are eliminated, and the parameters are retrieved again. Finally, the parameters are integrated in a fixed order: stroke difference, piston up-and-down movement duration, and train passing speed, while also associating the corresponding magnetic coded wheel pulse sequence identifiers to form a set of parameters to be diagnosed. This method is suitable for scenarios with high real-time requirements for parameter set output and can quickly provide reliable data support for basic fault diagnosis.

[0099] Step E12: Based on the set of parameters to be diagnosed, match and compare them with the preset fault judgment rules in the database to determine the target rule entries that the parameter set conforms to.

[0100] In this embodiment, the target rule entry refers to a specific fault association rule in the preset fault judgment rules that the set of parameters to be diagnosed conforms to or mainly matches.

[0101] As an optional implementation, a set of parameters to be diagnosed is retrieved, and then all preset fault judgment rules are extracted from the database. Following a fixed order of stroke difference, piston up-and-down movement duration, and train speed, each parameter in the parameter set is compared one by one with the corresponding parameter range of each rule. If all three parameters fall completely within the parameter range of a certain rule, and the magnetically encoded wheel pulse characteristics required by that rule are consistent with the actual detection results, then that rule is initially determined as a candidate entry. If only one candidate entry exists, it is directly determined as the target rule entry. If multiple candidate entries exist, the correlation coefficient between stroke difference and duration in each rule is further verified, and the rule with the highest correlation coefficient to the actual parameter is selected as the target rule entry. This method is suitable for scenarios with few fault types and clear, non-overlapping rule parameter ranges. It can quickly complete basic fault rule matching, meet the needs of conventional deceleration top fault diagnosis, and avoid delays in diagnosis efficiency due to complex processing.

[0102] Step E13: Based on the target rule entry, identify the corresponding fault type of the deceleration top.

[0103] As an optional implementation, the method retrieves the identified target rule entries, extracts the correspondence between the preset rule features and fault types within each entry, and simultaneously associates the magnetically encoded wheel pulse features required by the rule entry. Then, it backtracks to the original magnetically encoded wheel pulse data when the set of parameters to be diagnosed was generated, verifying whether the current pulse features are completely consistent with the features required by the target rule entry. If the features are consistent, the fault type corresponding to the deceleration top is directly identified based on the association between the rule and the fault type. If there is a slight feature deviation, the deviation point is marked, and the fault type is still matched according to the main features, while the deviation information is recorded for subsequent verification. This method directly matches the target rule entries with the current pulse features, has a simple operation process, fast fault identification speed, does not require access to a large amount of historical data, and has low storage resource requirements.

[0104] For example, refer to Figure 4 , Figure 4 This is a schematic diagram of the diagnostic process for this application. In the scenario of an HXD3C freight train passing a deceleration pylon, the following parameters are integrated: the piston compression count N1 corresponding to the stroke difference is 28; the duration of the piston's up-and-down movement within the deceleration cycle corresponds to the rebound time T of 0.5 seconds; and the train's passing speed corresponds to the real-time vehicle speed V of 15 km / h. This determines the set of parameters to be diagnosed. Based on this set and the matching comparison with preset fault judgment rules in the database, the rebound rate ΔN (obtained from the correlation between N1 and T) is calculated to be 56. The number of compressions per unit time falls within the "medium frequency" range, and the correlation feature matching rule entry "R-003" between the real-time vehicle speed V and the rebound rate ΔN is also present. According to "R-003," the cylinder pressure state of the deceleration pylon is identified as "low pressure," and the fault decision tree further determines the fault type as "insufficient damping."

[0105] By integrating parameters such as piston compression count, rebound time, and real-time vehicle speed, and relying on a fault decision tree, the problem of low accuracy caused by reliance on manual labor and single parameters in traditional deceleration top fault diagnosis is solved, thus improving the efficiency of fault detection and maintenance.

[0106] Based on any of the above embodiments, in Embodiment Eight of this application, referring to Figure 5 , Figure 5 This is a flowchart illustrating the eighth embodiment of the deceleration top working condition detection method of this application. Step E13 includes steps F11 to F15: Step F11: Parse the target rule entry and extract the fault judgment conditions contained in the target rule entry.

[0107] In this embodiment, the fault judgment condition refers to the parameter range, logical relationship, and other requirements in the target rule entry used to determine the fault type of the deceleration top.

[0108] As an optional implementation, the identified target rule entries are retrieved and segmented according to a preset rule entry structure specification. The stroke difference, piston up-and-down movement duration, and train speed-related magnetic encoder wheel pulse characteristics, as well as the logical relationships between these parameters, are extracted from each entry. Simultaneously, the pulse record identifiers from when the Hall switch detects the magnetic encoder wheel are associated with these parameters. The extracted parameter ranges and logical relationships are then organized into a clear set of fault judgment conditions, ensuring that each condition corresponds to the pulse detection dimension of the magnetic encoder wheel. This method relies on a preset structure specification, has a simple and fast parsing process, and requires no complex semantic processing.

[0109] Step F12: Based on the fault judgment conditions, compare the set of parameters to be diagnosed with the fault judgment conditions one by one to determine the comparison result between the set of parameters to be diagnosed and the fault judgment conditions.

[0110] In this embodiment, the comparison result refers to the conclusion of whether the set of parameters to be diagnosed meets the fault judgment conditions.

[0111] As an optional implementation, the fault judgment conditions obtained from the analysis are acquired, and the parameter type corresponding to each condition is identified. Then, the set of parameters to be diagnosed is retrieved, and in the order of the fault judgment conditions, the stroke difference in the set is compared with the stroke difference range in the conditions, the piston up-and-down movement duration is compared with the time range in the conditions, and the train passing speed is compared with the speed range in the conditions. Simultaneously, the original magnetic coded wheel pulse data corresponding to each parameter is associated. If the parameter value is within the condition range and the pulse data is normal, the parameter is marked as "compliant"; otherwise, it is marked as "non-compliant". After all comparisons are completed, the "compliant / non-compliant" status of each parameter is summarized to obtain the overall comparison result between the set of parameters to be diagnosed and the fault judgment conditions. This method is suitable for scenarios where the fault judgment conditions have a clear range and the accuracy requirements are not high, providing basic conclusions for simple fault diagnosis.

[0112] Step F13: Based on the comparison results, determine whether the parameter to be diagnosed fully meets all the fault judgment conditions of the target rule entry, and output the judgment result.

[0113] In this embodiment, the determination result refers to the final conclusion of whether the parameter to be diagnosed fully meets all the fault judgment conditions.

[0114] As an optional implementation, the comparison results between the set of parameters to be diagnosed and the fault judgment conditions are obtained. These results include the status of whether each parameter meets the corresponding fault judgment condition. Then, the compliance status of each parameter is checked. If the stroke difference meets its corresponding condition, the piston's up-and-down movement duration meets its corresponding condition, and the train's passing speed also meets its corresponding condition, and the associated magnetic encoder wheel pulse data has no abnormal interruptions or incorrect polarity, then the parameter to be diagnosed is determined to fully meet all the fault judgment conditions of the target rule entry, and a fully compliant judgment result is output. If any parameter does not meet its corresponding condition, or if the magnetic encoder wheel pulse data is abnormal, then it is determined to be incompletely compliant, and this result is output. This method has a simple and direct judgment logic, strictly relying on whether all parameters meet their corresponding conditions, and the results are clear and comprehensively reflect the matching status of parameters and conditions.

[0115] Step F14: If the determination result is completely consistent, then according to the preset correspondence between rule entries and fault types, the corresponding fault type is selected from the target rule entries, and the preliminary matched fault type is output.

[0116] In this embodiment, the initially matched fault type refers to the deceleration top fault category to be confirmed, which is selected from the target rule entries.

[0117] As an optional implementation, after the judgment result is a complete match, a preset table of correspondence between rule entries and fault types is retrieved, the record of the target rule entry in the table is located, and the fault type associated with that record is extracted. Simultaneously, it is checked whether the magnetic encoder wheel pulse characteristics involved in the target rule entry are consistent with the typical pulse characteristics of that fault type. If they are consistent, the extracted fault type is directly determined as the preliminary matching fault type and output. If there are non-critical feature differences, the fault type is still output, along with a note indicating slight feature deviation. This method is suitable for scenarios where rule entries and fault types correspond one-to-one and pulse characteristics are stable, quickly outputting basic fault types and meeting routine diagnostic needs.

[0118] Step F15: Verify the validity of the initially matched fault type, confirm the consistency between the initially matched fault type and the actual working condition characteristics of the deceleration top, and output the fault type corresponding to the deceleration top.

[0119] In this embodiment, validity verification refers to the inspection process of verifying whether the initially matched fault type matches the actual operating state of the deceleration jack. The actual operating condition characteristics of the deceleration jack refer to the operating state of the deceleration jack reflected by the pulse signal generated by the magnetic encoder wheel detected by the Hall switch.

[0120] As an optional implementation, the typical magnetic encoder wheel pulse characteristics corresponding to the initially matched fault type are first extracted. Then, the actual working condition pulse data of the deceleration top detected in real time by the Hall switch is retrieved, including the pulse number difference associated with the stroke difference, the pulse duration corresponding to the piston's up and down movement within the deceleration cycle, and the rotation direction record of the pulse sequence. The real-time pulse data is compared with the typical characteristics one by one. If the pulse number difference is within the range, the pulse duration meets the threshold, and there is no abnormal reversal in the rotation direction, the initially matched fault type is confirmed to be valid, and the fault type is output. If any item does not match, the verification is marked as abnormal, and the original pulse data of the current magnetic encoder wheel is retrieved again for verification. After eliminating temporary signal interference, the comparison is repeated. This method does not rely on historical data and only uses real-time single-cycle pulse data to complete the verification. The process is simple, the response is fast, and no additional storage resources are required.

[0121] As an alternative implementation, a historical fault pulse sample library of the same deceleration top is retrieved, and historical pulse patterns corresponding to preliminary matching fault types are extracted. Then, actual pulse data from the magnetic encoder wheel detected by the Hall switch within a consecutive preset deceleration cycle are collected. The multi-cycle pulse data is compared with the historical patterns, while simultaneously checking whether the actual pulses exhibit frequent polarity reversals or a large number of missing pulses. If the matching degree between the multi-cycle pulse data and the historical patterns exceeds the preset requirements, and the pulse stability meets the standard, the preliminary fault type is confirmed, and the final fault type is output. If the matching degree is insufficient, the signal deviation caused by magnetic pole wear on the magnetic encoder wheel is investigated, and pulse data for the preset deceleration cycle is collected again for verification. This method is suitable for scenarios requiring high fault diagnosis accuracy, effectively avoiding misjudgments caused by single-cycle interference, providing a reliable basis for the root cause analysis of deceleration top faults, and reducing ineffective maintenance costs.

[0122] For example, refer to Figure 6 , Figure 6 This is a schematic diagram of the system architecture of this application. When the wheel hub of a freight train car passes over the deceleration top, the target rule entries are parsed from the train deceleration top fault diagnosis rule library. For example, "when the pulse frequency fluctuation value collected by the Hall element is >15% and the variance of the magnetic encoder wheel speed calculated by the ARM4 core MCU is >a preset threshold, it is determined to be a magnetic encoder wheel jamming fault." The fault judgment conditions "pulse frequency fluctuation value >15%" and "magnetic encoder wheel speed variance >preset threshold" are extracted. The set of parameters to be diagnosed, including the real-time pulse frequency sequence transmitted to the ARM4 core MCU after being collected by the Hall element and the real-time speed sequence of the magnetic encoder wheel calculated by the MCU, are compared one by one with the fault judgment conditions to obtain the comparison results of "pulse frequency fluctuation value 20% (meets >15%)" and "speed variance 0.3 (meets >preset threshold 0.2)". If the parameters to be diagnosed completely meet all the fault judgment conditions of the target rule entries, the judgment result of "completely meets" is output. If the judgment result is completely consistent, based on the preset correspondence between "magnetic encoder wheel jamming fault corresponding to this rule item", "magnetic encoder wheel jamming fault" is selected and the preliminary matching fault type is output. Combining the reset delay time of the deceleration top after the train passes and the appearance wear of the magnetic encoder wheel during on-site manual inspection, the validity of the preliminary matching fault type is verified, confirming that it is consistent with the actual working condition characteristics of the deceleration top, and the "magnetic encoder wheel jamming fault" corresponding to the deceleration top is output.

[0123] By accurately acquiring the pulse signals of piston movement through magnetic encoder wheels and Hall switches, and combining data analysis and calculation with rule matching and validity verification of the cloud platform, the problems of traditional deceleration top fault diagnosis relying on manual labor and low signal acquisition accuracy have been solved. This has improved the accuracy of stroke difference detection and the accuracy of fault judgment condition comparison, greatly improving the deceleration top maintenance efficiency and train operation safety.

[0124] This application provides a deceleration top detection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the deceleration top working condition detection method in Embodiment 1 above.

[0125] The following is for reference. Figure 7 The diagram illustrates a structural schematic of a detection device suitable for implementing the embodiments of this application. The detection device for the deceleration top in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, mechanical monitoring devices, personal digital assistants (PDAs), tablet computers (PADs), portable media players (PMPs), IoT monitoring system devices, and fixed terminals such as non-contact sensing devices and desktop computers. Figure 7 The detection device for the deceleration top shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0126] like Figure 7As shown, the deceleration top detection device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The random access memory 1004 also stores various programs and data required for the operation of the deceleration top detection device. The processing unit 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the deceleration head detection device to communicate wirelessly or wiredly with other devices to exchange data. Although a deceleration head detection device with various systems is shown in the figure, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0127] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0128] The deceleration top detection device provided in this application adopts the deceleration top working condition detection method in the above embodiments, which can solve the technical problem of poor detection effect of deceleration top. Compared with the prior art, the beneficial effects of the deceleration top detection device provided in this application are the same as the beneficial effects of the deceleration top working condition detection method provided in the above embodiments, and other technical features in the deceleration top detection device are the same as the features disclosed in the method of the previous embodiment, and will not be repeated here.

[0129] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0130] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0131] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the deceleration top condition detection method in the above embodiments.

[0132] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0133] The aforementioned computer-readable storage medium may be included in the detection device of the deceleration top; or it may exist independently and not be assembled into the detection device of the deceleration top.

[0134] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the detection device of the deceleration top, the detection device of the deceleration top causes the following: to count the pulse signals generated by the changes in the state of the Hall switch and obtain the number of pulses corresponding to the pulse signals; to perform segmented calculations according to the stroke calculation rules by substituting the number of pulses into the pulses to obtain the stroke difference value corresponding to the piston; to substitute the time interval of the periodic changes of the pulse signals and the preset distance between the adjacent wheel hubs of the train car into the speed formula to calculate the train passing speed; and to determine the fault type corresponding to the deceleration top by comparing the stroke difference value, the duration from the triggering to the stopping of the pulse signal, and the train passing speed according to the preset fault judgment rules.

[0135] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0136] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0137] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0138] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the deceleration top condition detection method, which can solve the technical problem of poor detection effect of the deceleration top. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the deceleration top condition detection method provided in the above embodiments, and will not be repeated here.

[0139] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A detection device for a deceleration top, characterized in that, include: A magnetic encoder wheel has multiple magnets spaced apart around its circumference. The edge of the magnetic encoder wheel contacts a deceleration top piston, so that the movement of the deceleration top piston can drive the magnetic encoder wheel to rotate. A Hall switch is deployed on the plane of the magnetic encoder wheel, such that when the magnetic encoder wheel rotates and drives the magnet to pass the Hall switch, the state of the Hall switch is changed. A signal acquisition unit, connected to the Hall switch, is used to acquire the state of the Hall switch and send it to the data processing unit.

2. A method for detecting the working condition of a deceleration jack, characterized in that, The deceleration top condition detection method, applied to the data processing unit, includes: The number of pulses corresponding to the pulse signals generated by the changes in the state of the Hall switch is obtained by counting the pulse signals. The stroke difference corresponding to the piston is obtained by substituting the pulse number into the stroke calculation rules and performing segmented calculations. The train speed is calculated by substituting the time interval of the periodic change of the pulse signal and the preset distance between adjacent wheel hubs of the train car into the speed formula. By comparing the travel difference, the duration from pulse signal triggering to stop, and the train's passing speed with preset fault judgment rules, the fault type corresponding to the deceleration top is determined.

3. The method for detecting the deceleration top working condition as described in claim 2, characterized in that, The step of obtaining the number of pulses corresponding to the pulse signals generated by the statistical Hall switch state changes includes: The Hall switch detects the alternating changes in magnetic poles generated when the piston drives the magnetic encoder wheel to rotate, and generates a magnetic pole change signal. The Hall switch switches its state according to the magnetic pole change signal, generating the pulse signal; The number of pulses corresponding to the periodically changing pulse signal is obtained by statistically analyzing the pulse signal.

4. The method for detecting the deceleration top working condition as described in claim 2, characterized in that, The step of substituting the pulse count into the segmented calculation according to the stroke calculation rules to obtain the stroke difference value corresponding to the piston includes: Based on the periodic changes of the pulse signal, the number of pulses corresponding to the downward rotation direction of the piston and the number of pulses corresponding to the upward rotation direction of the piston are distinguished, and the number of pulses corresponding to the downward and upward rotation directions of the piston is obtained. Based on the number of pulses in the corresponding rotational directions of the piston's downward and upward movements, calculate the difference between the two types of pulse counts and output the pulse count difference. Based on the aforementioned travel calculation rules, the pulse quantity difference is calculated proportionally to generate the travel difference.

5. The method for detecting the deceleration top working condition as described in claim 2, characterized in that, Before the step of substituting the time interval of the periodic change of the pulse signal and the preset distance between adjacent wheel hubs of the train car into the speed formula to calculate the train's passing speed, the deceleration top condition detection method further includes: The system detects the trigger signal generated when the wheel hub of the train car passes over the deceleration top, distinguishes the trigger signals corresponding to two consecutive wheel hubs, and outputs the trigger signals of the two consecutive wheel hubs. Based on the trigger signals of two consecutive wheel hubs, the time point when each trigger signal is generated is recorded to determine the trigger time point corresponding to the two consecutive wheel hubs; Based on the trigger time points corresponding to two consecutive wheel hubs, the difference between the subsequent trigger time point and the previous trigger time point is calculated to obtain the time interval between two consecutive wheel hubs of the train car passing over the deceleration top.

6. The method for detecting the deceleration top working condition as described in claim 2, characterized in that, The step of substituting the time interval of the periodic change of the pulse signal and the preset distance between adjacent wheel hubs of the train carriage into the speed formula to calculate the train's passing speed includes: Based on the time interval and the preset distance between adjacent wheel hubs of the train carriage, the original speed value is obtained by dividing the preset distance by the time interval. Invalid original velocity values ​​caused by the time interval being zero or negative are removed, and original velocity values ​​that conform to physical meaning are retained to determine the valid original velocity values; Based on a preset speed unit standard, the unit of the effective original speed value is converted to determine the train's passing speed.

7. The method for detecting the deceleration top working condition as described in claim 2, characterized in that, The step of determining the fault type corresponding to the deceleration peak by comparing the travel difference, the duration from pulse signal triggering to stop, and the train passing speed using preset fault judgment rules includes: By integrating the stroke difference, the duration of the piston's up-and-down movement during the deceleration cycle, and the train's passing speed, a set of parameters to be diagnosed is determined. Based on the set of parameters to be diagnosed, the system matches and compares them with the preset fault judgment rules in the database to determine the target rule entries that the parameter set conforms to. Based on the target rule entries, the corresponding fault type of the deceleration top is identified.

8. The method for detecting the deceleration top working condition as described in claim 7, characterized in that, The step of identifying the fault type corresponding to the deceleration top based on the target rule entry includes: Parse the target rule entries and extract the fault judgment conditions contained in the target rule entries; Based on the fault judgment conditions, the set of parameters to be diagnosed is compared with the fault judgment conditions one by one to determine the comparison result between the set of parameters to be diagnosed and the fault judgment conditions. Based on the comparison results, determine whether the parameter to be diagnosed fully meets all the fault judgment conditions of the target rule entry, and output the judgment result; If the determination result is a complete match, then according to the preset correspondence between rule entries and fault types, the corresponding fault type is selected from the target rule entries, and the preliminary matched fault type is output. The validity of the initially matched fault type is verified to confirm the consistency between the initially matched fault type and the actual working condition characteristics of the deceleration top, and the fault type corresponding to the deceleration top is output.

9. A detection device for a deceleration top, characterized in that, The detection device for the deceleration top includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the deceleration top working condition detection method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the deceleration top condition detection method as described in any one of claims 1 to 8.

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