Method for autonomously repairing and controlling bogie instability and rail vehicle

Abstract

The invention provides a method for autonomously repairing and controlling instability of a bogie and a railway vehicle. Wheel out-of-roundness problems such as wheel equivalent taper, radial run-out and wheel high-order polygon are autonomously repaired by detecting the wheel equivalent taper, the radial run-out and the wheel high-order polygon and grinding a wheel tread; releasing wheel equivalent taper, radial run-out and wheel high-order polygon alarms, automatically repairing high-pressure intermittence, low-pressure intermittence and low-pressure continuity through the wheel equivalent taper and radial run-out, and comparing a high-pressure continuity mode with a non-grinding sub-mode to obtain the relationship between the repairing action mileage and the wheel tread modification efficiency; the method is used for restraining rapid growth of wheel out-of-roundness problems such as wheel equivalent conicity, radial run-out and wheel high-order polygons. The relation between the millstone different-mode mileage and the wheel equivalent conicity radial run-out growth rate is obtained.

Description

Technical Field

[0001] This invention belongs to the field of bogie control, specifically relating to a method for autonomously repairing and controlling bogie instability and a rail vehicle. Background Technology

[0002] As the operating environments of high-speed trains become increasingly diverse, the wheel-rail matching relationship becomes more complex, leading to frequent problems such as wheel-rail wear, car body sway, and lateral instability of the bogie. Ensuring the safety of operating rail vehicles requires excellent lateral stability and derailment prevention. With increasing train speeds, the hazards of bogie hunting become more pronounced, and bogie instability seriously affects operational safety; therefore, controlling bogie instability is crucial.

[0003] Currently, the specific methods to prevent vehicle gooseing instability are: installing a real-time monitoring system during train operation to monitor the vibration of the bogie throughout the entire process; promptly reminding the driver to slow down when gooseing instability occurs to prevent the instability from continuing; and saving the vehicle's status information when instability occurs in the system to solve the problem of gooseing instability wheel turning. However, existing instability assessment conditions are relatively simple. For example, the bogie serpentine instability detection method disclosed in patent CN110411766A only collects the lateral vibration data of the bogie; the train instability monitoring method disclosed in patent CN118457676A only collects the lateral acceleration signal of the axle box. This leads to inaccurate bogie instability assessment and certain safety hazards. At the same time, as the tread wear intensifies, the equivalent taper of the wheel-rail matching continuously increases, which can lead to lateral instability of the frame in severe cases, but there is currently no specific solution. Summary of the Invention

[0004] In order to solve the technical problems existing in the prior art, the present invention provides a method for autonomously repairing and controlling bogie instability and a rail vehicle.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention proposes a method for autonomously repairing and controlling bogie instability, characterized by comprising the following steps: Step 1: Determine in real time whether the triggering conditions for the road cleaning and adhesion enhancement mode are met. When the triggering conditions are met, the road cleaning and adhesion enhancement mode is activated. Step 2: Real-time acquisition of axle box vibration acceleration and wheel tread equivalent taper; calculation of wheel polygon order and radial runout value based on axle box vibration acceleration; calculation of frame lateral acceleration based on wheel tread equivalent taper. Step 3: Determine whether the wheel polygon order or radial runout value exceeds the corresponding warning threshold. If not, continue with the road cleaning and adhesion enhancement mode. If yes, trigger the wheel high-order polygon and radial runout warning. The warning triggers the bogie instability alarm and proceeds to step 4. Based on the lateral acceleration of the frame and the equivalent cone of the wheel tread, determine whether the corresponding alarm threshold is exceeded. If not, continue with the road cleaning and adhesion enhancement mode; if so, trigger the bogie instability alarm and proceed to step 4. Step 4 determines the active shaping mode. If the active shaping conditions are not met, return to step 3. If the active shaping conditions are met, start the tread cleaning and shaping mode until the active shaping conditions are no longer met, then exit the active shaping mode. Step 5: After the bogie instability alarm is cleared, the vehicle continues to operate for a set distance, then checks again whether the bogie instability alarm is triggered, and returns to the road cleaning and adhesion enhancement mode.

[0006] As a further technical solution, the wheel polygon detection method is as follows: Real-time acquisition of axle box vibration acceleration; Construct a high-order polygon early warning monitoring and bogie instability control model for wheels; The wheel high-order polygon early warning monitoring and bogie instability control model judges the real-time acquired axle box vibration acceleration and outputs the detection results: normal, prediction, early warning or alarm.

[0007] As a further technical solution, the wheel radial runout detection method is as follows: Establish a model for early warning and monitoring of wheel radial runout and bogie instability control; Real-time acquisition of axle box vibration acceleration; The wheel radial runout early warning monitoring and bogie instability control model judges the real-time acquired axle box vibration acceleration and outputs the detection result: early warning or alarm.

[0008] As a further technical solution, the wheel equivalent conicity detection method is as follows: By establishing the mapping relationship between the equivalent conicity of the wheel tread and the lateral acceleration of the frame, a model for alarming wheel equivalent conicity and bogie instability is constructed. The real-time identification of the tread equivalent taper is input into the wheel equivalent taper and bogie instability alarm model. The wheel equivalent cone and bogie instability alarm model converts the tread equivalent cone into the frame lateral acceleration, and determines whether the frame lateral acceleration exceeds the threshold. If it does, an alarm is triggered.

[0009] As a further technical solution, the method for predicting bogie instability using wheel equivalent cone and bogie instability alarm model is as follows: If the first set value ≤ wheel equivalent cone < second set value, and the frame lateral acceleration has a consecutive peak values ​​that reach or exceed the first set threshold, it is judged as bogie instability prediction. If b consecutive peak values ​​are lower than the first set threshold, it is judged as bogie instability prediction cancellation. a and b are both natural numbers, and a > b.

[0010] As a further technical solution, the method for using wheel equivalent cone and bogie instability alarm model to perform bogie instability alarm is as follows: If the wheel equivalent cone is less than the first set value; if the frame lateral acceleration has a consecutive peak values ​​that reach or exceed the second set threshold, the bogie is judged to be unstable; if b consecutive peak values ​​(whole waves) are lower than the second set threshold, the bogie instability is judged to be resolved. a and b are both natural numbers, and a > b, and the second set threshold is greater than the first set threshold.

[0011] As a further technical solution, the shaping conditions in step 5 are as follows: The vehicle's operating speed is greater than or equal to the speed setting value. When the minimum characteristic value is greater than or equal to the set instability characteristic value c times within a set time period, the active shaping criterion is met, and the tread cleaning and shaping mode is activated.

[0012] As a further technical solution, after the bogie lateral acceleration is filtered, the minimum value among all b consecutive peak-to-peak values ​​within a set time is calculated. The maximum value among all the minimum values ​​calculated within the set time is divided by 2, and the minimum value characteristic value is calculated and output. A minimum value characteristic value is output every 1 second using a 1-second slip. As a further technical solution, when the vehicle experiences braking, coasting, or idling signals, or when the speed is less than the speed set value, the shaping mode will pause. The shaping mode will resume once the signal disappears or the vehicle's operating speed is greater than or equal to the speed set value, and mileage accumulation will not be paused.

[0013] As a further technical solution, the active shaping mode is a tread surface cleaning and shaping mode, and the specific method is as follows: The active reshaping mode is a tread surface cleaning and reshaping mode. The specific method is as follows: Once the tread cleaning and shaping conditions are met, the timing of the mileage begins. When the mileage is greater than or equal to the first set mileage, the first batch of shaping action loops is started. When the mileage is greater than or equal to the second set mileage, the second batch of shaping action loops is started. After the autonomous shaping mode completes the second batch of action loops, the autonomous shaping mode is restarted to judge whether the autonomous shaping conditions are met. If the autonomous shaping conditions are not met, the first batch of action loops and the second batch of action loops of the autonomous shaping mode are continued to be executed, and so on. If the autonomous shaping conditions are not met, the autonomous shaping mode is exited.

[0014] As a further technical solution, the tread cleaning and shaping modes include high-pressure intermittent, low-pressure intermittent, low-pressure continuous, and high-pressure continuous modes.

[0015] Secondly, the present invention also provides a vehicle in which the aforementioned autonomous repair control method for bogie instability is used for bogie instability control.

[0016] The beneficial effects of this invention are as follows: This invention utilizes real-time acquisition of axle box vibration acceleration and wheel tread equivalent taper. It calculates the wheel polygon order and radial runout based on the axle box vibration acceleration and the frame lateral acceleration based on the wheel tread equivalent taper. Then, based on their respective thresholds, it actively triggers a bogie instability alarm. After the alarm, it performs an active correction mode assessment. If the correction conditions are not met, the assessment continues. If the conditions are met, a tread cleaning correction mode is activated until the correction conditions are no longer met, at which point the active correction mode is exited. The entire process enables automatic correction, and the bogie instability triggering conditions include multiple factors, ensuring vehicle safety to a certain extent. This invention's bogie instability control method has advantages such as actively repairing wheel equivalent taper and real-time bogie instability control, avoiding concentrated wheel turning, and is particularly suitable for controlling bogie instability in high-speed trains.

[0017] During the automatic shaping process, this invention autonomously grinds the wheel tread using a tread cleaning mode, automatically repairing wheel out-of-roundness issues such as wheel equivalent taper, radial runout, and wheel high-order polygons, and eliminating alarms for wheel equivalent taper, radial runout, and wheel high-order polygons. Attached Figure Description

[0018] Figure 1 The process of wheel polygon suppression and tread repair method Figure 1 ; Figure 2 The process of wheel polygon suppression and tread repair method Figure 2 ; Figure 3 A flowchart for wheel polygon detection; Figure 4 Flowchart for wheel radial runout detection; Figure 5 Relationship between wheel surface roughness and order Figure 1 ; Figure 6 Relationship between the wave depth and order of a polygonal wheel Figure 1 ; Figure 7 Relationship between wheel surface roughness and order Figure 2 ; Figure 8Relationship between the wave depth and order of a polygonal wheel Figure 2 ; Figure 9 A schematic diagram of the rectangular coordinate representation of the out-of-roundness range of the wheel's circumferential position. Figure 1 ; Figure 10 Polar coordinate representation of the circumferential out-of-roundness of a wheel Figure 1 ; Figure 11 A schematic diagram of the rectangular coordinate representation of the out-of-roundness range of the wheel's circumferential position. Figure 2 ; Figure 12 Polar coordinate representation of the circumferential out-of-roundness of a wheel Figure 2 ; Figure 13 Schematic diagram of wheel runout repair in autonomous active reshaping mode for tread cleaning; Figure 14 This is a schematic diagram illustrating the variation of tread wear with mileage. Figure 15 This is a graph showing the relationship between the equivalent taper and the amplitude of the lateral acceleration of the frame. Figure 16 A trend diagram showing the influence of the grinding wheel on the growth rate of the equivalent taper of the wheel. Figure 17 A graph showing the relationship between the mileage of the grinding wheel under different grinding modes and the growth rate of the wheel's equivalent conicity. Detailed Implementation It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless otherwise expressly indicated by the invention, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. As described in the background section, there are shortcomings in the existing technology. In order to solve the above-mentioned technical problems, this invention proposes a method and train for autonomously repairing and controlling bogie instability.

[0020] In a typical embodiment of the present invention, such as Figure 1 As shown, this invention proposes a method for autonomously repairing and controlling bogie instability, comprising the following steps: Step 1: Determine in real time whether the triggering conditions for the road cleaning and adhesion enhancement mode are met. When the triggering conditions are met, the road cleaning and adhesion enhancement mode is activated. Step 2: Real-time acquisition of axle box vibration acceleration and wheel tread equivalent taper; calculation of wheel polygon order and radial runout value based on axle box vibration acceleration; calculation of frame lateral acceleration based on wheel tread equivalent taper. Step 3: Determine whether the wheel polygon order or radial runout value exceeds the corresponding warning threshold. If not, continue with the road cleaning and adhesion enhancement mode. If yes, trigger the wheel high-order polygon and radial runout warning. The warning triggers the bogie instability alarm and proceeds to step 4. Based on the lateral acceleration of the frame and the equivalent cone of the wheel tread, determine whether the corresponding alarm threshold is exceeded. If not, continue with the road cleaning and adhesion enhancement mode; if so, trigger the bogie instability alarm and proceed to step 4. Step 4 performs an active shaping mode judgment. If the shaping conditions are not met, return to step 3; if the shaping conditions are met, start the tread cleaning shaping mode until the shaping conditions are no longer met, then exit the active shaping mode. Step 5: After the bogie instability alarm is cleared, the vehicle continues to operate for a set distance, then checks again whether the bogie instability alarm is triggered, and returns to the road cleaning and adhesion enhancement mode.

[0021] In step 1, the tread cleaning and adhesion enhancement mode (routine repair) is mainly executed during vehicle operation when the following triggering conditions are met: 1. Vehicle braking action and speed > 30 km / h; 2. Anti-slip action, slippage, or freewheeling. Specifically, in this embodiment, the tread cleaning and adhesion enhancement mode uses a low-pressure intermittent action mode for the grinding wheel. The specific action logic is: 20 seconds of action, 10 seconds of release, and 30 seconds constitute one action cycle; the action pressure is 0.3 MPa. Of course, in a few cases, a high-pressure continuous action mode is also used, with an action pressure of 0.49 MPa. The advantages and disadvantages of the high-pressure continuous action mode are: good single-cycle shaping effect, but short grinding wheel life; the advantages and disadvantages of the low-pressure intermittent action mode are: slightly worse single-cycle shaping effect, but longer grinding wheel life. For details, please refer to Table 1. Table 1. Operation Logic of Tread Cleaning Device

[0022] Furthermore, the wheel polygon, radial runout, and equivalent taper detection in step 2 above include wheel high-order polygon detection, wheel radial runout detection, and wheel equivalent taper detection; Specifically, the method for high-order polygon detection of wheels is as follows: A high-order polygon early warning monitoring and bogie instability control model for wheels is established; axle box vibration acceleration is acquired in real time; the high-order polygon early warning monitoring and bogie instability control model for wheels judges the acquired axle box vibration acceleration in real time and outputs the detection result: normal, prediction, early warning, or alarm. The specific process is as follows: By real-time detection of axle box vibration acceleration and the relationship between wheel high-order polygons and axle box vibration acceleration, a wheel high-order polygon early warning monitoring and bogie instability control model is constructed. The model identifies wheel polygons of different severity levels, which are used to issue wheel high-order polygon early warnings based on the severity of the identified wheel polygons, activate the wheel autonomous repair mode, and control bogie instability.

[0023] Specifically, such as Figure 2 As shown, a 1000Hz low-pass filter is applied using the vertical acceleration of the axle box. The dominant frequency of the polygon and its amplitude X2 are obtained through polygon target frequency search. The polygon vibration evaluation index formula is: AdB=20log(X2 / CF), CF=0.02dB. Here, AdB represents the amplitude of the polygon dominant frequency X2, and CF is a correction coefficient.

[0024] The wheel high-order polygon early warning monitoring and bogie instability control model is divided into four levels: normal, prediction, early warning and alarm.

[0025] Table 2 Threshold Indicators for Early Warning Monitoring of Wheel Polygons

[0026] Furthermore, the specific method for detecting wheel radial runout includes: establishing a wheel radial runout early warning monitoring and bogie instability control model; acquiring axle box vibration acceleration in real time; the wheel radial runout early warning monitoring and bogie instability control model judging the real-time acquired axle box vibration acceleration and outputting the detection result: early warning or alarm.

[0027] Specifically, by real-time detection of axle box vibration acceleration and by establishing the relationship between wheel radial runout and axle box vibration acceleration, a wheel radial runout early warning monitoring and bogie instability control model is constructed. This model identifies different degrees of wheel radial runout and, based on the severity of the identified runout, issues a wheel radial runout warning, activates the wheel's self-repair mode, and controls bogie instability. The wheel radial runout detection model has two levels: warning and alarm. The model thresholds are shown in Table 3. For the specific detection algorithm, please refer to [Table 3]. Figure 4 The axle box vibration acceleration is low-pass filtered at 1000Hz, and then the root mean square value is calculated every 1 second. The wheel radial runout evaluation index is calculated smoothly over 10 seconds. If the value exceeds the set value 10 times or more consecutively, an alarm or warning is issued.

[0028] Table 3 Threshold Indicators for Early Warning Monitoring of Wheel Radial Runout

[0029] Furthermore, the specific method for detecting wheel equivalent taper is to establish a mapping relationship between wheel tread equivalent taper and frame lateral acceleration, construct an equivalent taper and bogie instability alarm model, identify wheel tread equivalent taper in real time, and trigger an alarm when the tread equivalent taper exceeds a threshold. The wheel tread cleaning device then autonomously initiates an active shaping mode to reduce the growth rate of wheel equivalent taper and control bogie instability.

[0030] Specifically, the measured relationship between the equivalent conicity and the lateral acceleration of the bogie is as follows: Based on the bogie instability alarm, the equivalent conicity of the train wheel is 0.27, and the lateral acceleration of the bogie structure is ≥0.8g, triggering the bogie instability alarm. Combining this with the tracking patterns of the lateral acceleration of the train structure in previous tests, the relationship between the equivalent conicity and the amplitude of the lateral acceleration of the bogie structure is as follows: Where x is the equivalent taper and y is the lateral acceleration amplitude of the frame, in g. (See...) Figure 7 ) By deriving the relationship between the equivalent wheel taper and the lateral acceleration amplitude of the frame, the logical relationship between the self-repair amount of the equivalent taper and the bogie instability alarm is obtained, thereby controlling the bogie instability alarm. This yields a method for controlling bogie instability through the self-repair of the wheel equivalent taper and radial runout, ensuring the safe operation of the vehicle.

[0031] Furthermore, wheel high-order polygon, radial runout warning and bogie instability alarm, including wheel high-order polygon, radial runout warning and bogie instability alarm; The wheel high-order polygon and radial runout warning is determined by the wheel polygon and radial runout model threshold: if the conditions of "① whether the threshold is ≥18dB or ② whether the threshold is ≥5g" are met, the wheel high-order polygon and radial runout warning is triggered.

[0032] The bogie instability alarm includes alarms triggered by wheel high-order polygons, radial runout warnings, and wheel equivalent cone alarms.

[0033] (1) By real-time detection of axle box vibration acceleration, and by using wheel high-order polygon, radial runout and axle box vibration acceleration model, a wheel high-order polygon, radial runout early warning monitoring and bogie instability control model is constructed. Wheel high-order polygon and radial runout of different severity are identified, wheel high-order polygon and radial runout early warning is issued, wheel autonomous repair mode is activated and bogie instability is controlled.

[0034] (2) The method for predicting bogie instability using the wheel equivalent cone and bogie instability alarm model is as follows: If the first set value ≤ wheel equivalent cone < second set value, and the frame lateral acceleration has a consecutive peak values ​​that reach or exceed the first set threshold, it is judged as bogie instability prediction. If b consecutive peak values ​​are lower than the first set threshold, it is judged as bogie instability prediction cancellation. a and b are both natural numbers, and a > b.

[0035] As a further technical solution, the method for using wheel equivalent cone and bogie instability alarm model to perform bogie instability alarm is as follows: If the wheel equivalent cone is less than the first set value; if the frame lateral acceleration has a consecutive peak values ​​that reach or exceed the second set threshold, the bogie is judged to be unstable; if b consecutive peak values ​​(whole waves) are lower than the second set threshold, the bogie instability is judged to be resolved. a and b are both natural numbers, and a > b, and the second set threshold is greater than the first set threshold.

[0036] Specifically, in this embodiment, it is as follows: The relationship between the equivalent conicity of the wheel and the amplitude of the lateral acceleration of the frame is as follows: If the wheel equivalent cone is less than 0.27 and the lateral acceleration of the frame reaches 10 consecutive peak values ​​with a lateral acceleration greater than or equal to 0.68g, then a bogie instability prediction is made. If the wheel equivalent cone is less than 0.24 and the vehicle experiences 6 consecutive peak values ​​with a lateral acceleration less than 0.68g, then the bogie instability prediction is lifted.

[0037] If the wheel equivalent cone is ≥0.27 and the frame lateral acceleration shows 10 consecutive peak values ​​with a frame lateral acceleration ≥0.8g, the bogie is considered unstable. If the wheel equivalent cone is <0.27 and the frame lateral acceleration shows 6 consecutive peak values ​​with a frame lateral acceleration <0.8g, the bogie instability is considered resolved.

[0038] Furthermore, when the train speed is below 30 km / h, the vehicle disables the instability detection alarm signal and prediction signal. When the instability detection device fails (including instability detection host failure, instability detection sensor failure, and communication failure), the train maintains normal operation.

[0039] Furthermore, the autonomous active shaping mode includes vehicle speed judgment, active shaping mode activation judgment, bogie lateral acceleration acquisition and minimum characteristic value calculation, mode judgment, shaping pause judgment, tread cleaning shaping mode, and shaping mode action pause. Specifically, when a bogie instability and high-order polygon alarm signal is received, and the vehicle speed is ≥300km / h, the vehicle activates the active shaping mode. If the minimum characteristic value is ≥300km / h or more within a set time, the active shaping criterion is met, and the tread cleaning shaping mode is activated. In this embodiment, the specific judgment method is: if the minimum characteristic value occurs 3 or more times within half an hour, and the minimum characteristic value is ≥3.4m / s 2 When the active reshaping criterion is met (mileage = 0km), the tread cleaning and reshaping mode is activated.

[0040] The method for calculating the minimum characteristic value described here is as follows: After filtering the lateral acceleration of the bogie, calculate the minimum value among all b consecutive peak-to-peak values ​​within a set time. Divide the maximum value among all the minimum values ​​calculated within the set time by 2 to calculate and output the minimum characteristic value. Use a 1s slip to output a minimum characteristic value every 1s.

[0041] In this embodiment, the time window length is 5s. The minimum value among all 10 consecutive peak-to-peak values ​​(using 1 full-wave slip) within 5s is calculated sequentially. The maximum value among all the minimum values ​​calculated within 5s is divided by 2, and the output is the minimum value feature value. A 1s slip is used, and a minimum value feature value is output every 1s.

[0042] The body correction mode pauses when braking, coasting, or wheel spin signals are detected, or when the speed is <300km / h. The body correction mode resumes once the signal disappears or the speed reaches ≥300km / h. Mileage accumulation is not paused.

[0043] In the tread cleaning and shaping mode, after the tread cleaning and shaping conditions are met, the mileage is accumulated. When the mileage is greater than or equal to the first set mileage, the first batch of shaping action loops is started; when the mileage is greater than or equal to the second set mileage, the second batch of shaping action loops is started. After the autonomous shaping mode completes the second batch of action loops, the autonomous shaping mode is restarted for judgment. If the autonomous shaping criteria are met, the first batch of shaping action loops and the second batch of action loops are executed again, and this process is repeated continuously. If the autonomous shaping criteria are not met, the autonomous shaping mode is exited. Specifically, in this embodiment, the details are as follows: 1. When the mileage is ≥500km, start the first batch of shaping action cycles, specifically: 16 low-pressure intermittent action cycles (cylinder pressure 0.3MPa, action 20s, release 10s, each action cycle is 30s). 2. When the mileage is ≥1000km, start the second batch of shaping action cycle 16 low-pressure intermittent action cycles (cylinder pressure 0.3MPa, action 20s, release 10s, every 30s is one action cycle). 3. After the autonomous active shaping mode completes 32 low-pressure intermittent action cycles, the shaping mode action pauses and restarts the active shaping mode judgment. If the active shaping criteria are met, the shaping mode continues to execute 32 action cycles. This process is repeated until the active shaping criteria are no longer met. If the active shaping criteria are no longer met, the shaping mode exits.

[0044] The main repair mileage judgment, alarm clearance is achieved by judging that the wheel equivalent cone is <0.24 and the vehicle has 6 consecutive peak frame lateral accelerations <0.68g. After the alarm is cleared, the time mileage is started. After 5000 kilometers of operation, it is judged again whether the wheel high-order polygon, radial runout warning and bogie instability alarm are triggered. If no alarm is triggered, the alarm is cleared and the autonomous active shape correction is successful. The tread cleaning device switches back to the normal shape correction mode.

[0045] It should be noted that the above-mentioned tread cleaning and shaping modes include high-pressure intermittent, low-pressure intermittent, low-pressure continuous, and high-pressure continuous modes, which can be selected according to the specific testing situation.

[0046] The alarm was cleared and the autonomous automatic repair was successful. The wheel tread can be ground by the tread cleaning and grinding action, which can autonomously repair the wheel's equivalent cone, radial runout, and wheel high-order polygon. The alarms for wheel equivalent cone, radial runout, and wheel high-order polygon were cleared. By comparing the autonomous repair action mode of the tread cleaning and grinding action with the condition without grinding, the relationship between the mileage of different grinding modes and the growth rate of wheel equivalent cone was obtained. This is used to suppress the rapid growth of wheel equivalent cone. By deriving the relationship between equivalent cone and the amplitude of frame lateral acceleration, the bogie instability alarm was controlled. The method of autonomous repair of wheel equivalent cone and radial runout to control bogie instability was obtained, which plays a role in ensuring the safe operation of the vehicle.

[0047] The present invention will be further described below with reference to specific embodiments: (1) Through the low-pressure intermittent operation of the tread cleaning abrasive, the wheel tread repair efficiency is 0.056 mm / 10,000 km. The relationship between the low-pressure intermittent operation repair mileage and the wheel tread repair efficiency is as follows: Where x is the vehicle repair mileage, in units of 10. 4 km, y is the wear of the wheel tread, and k0 is the repair coefficient; The relationship between high-pressure intermittent and low-pressure continuous action repair mileage and wheel tread repair efficiency: Where x is the vehicle repair mileage, in units of 10. 4km, y is the wheel tread wear, k1 is the repair coefficient, and the tread repair efficiency for both high-pressure intermittent and low-pressure continuous applications is 0.072 mm / 10,000 km. The relationship between high-pressure continuous mode repair mileage and wheel tread repair efficiency: Where x is the vehicle repair mileage, in units of 10. 4 km, y is the wheel tread wear, and k2 is the repair coefficient. The maximum wheel tread repair efficiency under continuous high pressure is 0.091 mm / 10,000 km, while the wheel tread repair efficiency without grinding action is 0.052 mm / 10,000 km. The wheel tread can be ground by the action of tread cleaning and grinding, which reduces the growth rate of wheel high-order polygons and radial runout. Table 4. Wheel high-order polygons and radial runout growth rate

[0048] By comparing the self-repair modes of high-pressure intermittent, low-pressure intermittent, low-pressure continuous, and high-pressure continuous modes of wheel equivalent taper and radial runout with the mode without grinding pads, the relationship between repair action mileage and wheel tread shaping efficiency was obtained. The relationship between the mileage of different grinding pad modes and the growth rate of wheel equivalent taper and radial runout was also obtained, which can be used to suppress the rapid growth of wheel out-of-roundness problems such as wheel equivalent taper, radial runout, and wheel high-order polygons.

[0049] Specific embodiments are given below; Example 1: A 1:1 braking power test bench and tread testing equipment were used to test the wheel reshaping effect of the grinding wheel during polygonal reshaping. The test program consisted of 500 brake cycles. The wheel material was SSW-Q3R. The reshaping test operation modes were: 0-150 brake cycles at 350 km / h with low-pressure intermittent operation; 150-500 brake cycles at 250 km / h with high-pressure continuous operation. Test conclusion: The grinding wheel wear effectively suppressed the rate of change of the 20th order polygonal wave depth and the rate of change of the 20th order polygonal roughness dB value on the tread surface.

[0050] Table 3 Comparison of tread wear and abrasive wear

[0051] Example 2: Tread cleaning abrasive accelerated profile correction mode: ① When the speed is greater than 60 km / h, the tread cleaning device operates intermittently (20s on, 10s off, maximum 2 cycles per station); when the speed is less than 60 km / h, it stops operating; operating pressure is 0.3 MPa; ② When the wheel slips or spins, the tread cleaning device is applied until the slip or spin signal disappears; operating air pressure is 0.3 MPa. After applying the abrasive for 67,000 km, the wheel radial runout value significantly decreased, with the average radial runout value decreasing from 0.14 to 0.1, and the maximum decrease in radial runout value being 0.075 mm.

[0052] Under four operating modes—high-pressure intermittent, low-pressure intermittent, low-pressure continuous, and high-pressure continuous—before 117,600 km, the equivalent cone growth rate of the vehicles under each operating mode was lower than that of vehicles without grinding wheels. After 117,600 km, the equivalent cone under the high-pressure intermittent, high-pressure continuous, and low-pressure continuous modes showed abrupt changes, suddenly increasing significantly, with clearly abnormal data. After 206,100 km following turning, due to the grinding wheels reaching their usage limit, new grinding wheels were replaced on a large scale. Under the four grinding wheel operating modes, the equivalent cone rapidly decreased (see the trend of the influence of grinding wheels on the growth rate of wheel equivalent cone). Figure 16 Since the equivalent cone data became significantly abnormal after 117,600 kilometers, data from before 117,600 kilometers were used for analysis.

[0053] Without a grinding wheel, the equivalent taper growth rate is 0.138 / 100,000 km. The equivalent taper growth rate is related to the vehicle's operating mileage of 10... 4 The relationship of km: Where x is the vehicle's operating mileage, in units of 10. 4 km, y is the equivalent taper growth rate.

[0054] Under low-pressure intermittent conditions, the equivalent taper growth rate of the grinding wheel is 0.083 / 100,000 km. The equivalent taper growth rate is related to the vehicle's operating mileage of 10 km. 4 The relationship between km is: Where x is the vehicle's operating mileage, in units of 10. 4 km, y is the equivalent taper growth rate, and the attenuation effect of the low-pressure intermittent action of the grinding head on the equivalent taper growth rate is: 等效锥度增长率 =-0.0055 / 10,000 km (see the relationship between mileage and wheel equivalent cone growth rate under different grinding wheel modes) Figure 17 ).

[0055] The relationship between the equivalent taper and the amplitude of the lateral acceleration of the frame is as follows: Where x is the equivalent taper and y is the amplitude of the lateral acceleration of the frame, in g (see the relationship between equivalent taper and amplitude of lateral acceleration of the frame). Figure 15 ).

[0056] The attenuation effect of the low-pressure intermittent action of the grinding element on the equivalent cone growth rate of the lateral acceleration amplitude of the bogie frame is as follows: 等效锥度增长率 =0.0055 / 10,000 km, the decrease in lateral acceleration amplitude of the bogie frame due to low-pressure intermittent operation of the grinding wheel. / 10,000 kilometers.

[0057] Example 3: Bogie instability alarm: , Bogie instability alarm deactivated: , , 0.03, the total length of a certain line is 38.57km, and the grinding wheel travels 3.77km. The corresponding total length to work ratio is 38.57:3.77 = 10.23:1. The work done by the grinding wheel over 10,000 kilometers is grinding wheel pressure * friction coefficient * travel distance. The work done in low-pressure intermittent mode is: W=275*0.45*100000000*(2 / 3) / 10.23=806451613J=806.45MJ The contribution of the work done by the tread cleaning abrasive per 10,000 kilometers to the decrease in the taper growth rate can be obtained as 0.0055 / 806.5 = 0.0068 / 1000 MJ. Contribution of bogie instability alarm deactivation to the work done by the tread cleaning grinder per 10,000 kilometers: 0.03 MJ.

[0058] This embodiment can grind the wheel tread using the action of a tread cleaning and grinding tool, autonomously repairing wheel out-of-roundness issues such as equivalent wheel taper, radial runout, and high-order polygons, and relieving alarms for these issues. The bogie instability control method of this invention has advantages such as actively repairing wheel equivalent taper and real-time control of bogie instability, avoiding centralized wheel turning, and is particularly suitable for controlling bogie instability in high-speed trains.

[0059] Furthermore, this embodiment also provides a rail vehicle that employs the aforementioned method for autonomously repairing and controlling bogie instability. Because this rail vehicle uses the aforementioned method for autonomously repairing and controlling bogie instability, it also possesses all the advantages described above. In some embodiments, the rail vehicle provided by this invention can be any suitable type of vehicle, such as conventional trains, high-speed trains, subway vehicles, urban rail vehicles, etc. This invention is not limited to any particular type of rail vehicle.

[0060] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for autonomously repairing and controlling bogie instability, characterized in that, Includes the following steps: Step 1: Determine in real time whether the triggering conditions for the road cleaning and adhesion enhancement mode are met. When the triggering conditions are met, the road cleaning and adhesion enhancement mode is activated. Step 2: Real-time acquisition of axle box vibration acceleration and wheel tread equivalent taper; calculation of wheel polygon order and radial runout value based on axle box vibration acceleration; calculation of frame lateral acceleration based on wheel tread equivalent taper. Step 3: Determine whether the wheel polygon order or radial runout value exceeds the corresponding warning threshold. If not, continue with the road cleaning and adhesion enhancement mode. If yes, trigger the wheel high-order polygon and radial runout warning. The warning triggers the bogie instability alarm and proceeds to step 4. Based on the lateral acceleration of the frame and the equivalent cone of the wheel tread, determine whether the corresponding alarm threshold is exceeded. If not, continue with the road cleaning and adhesion enhancement mode; if so, trigger the bogie instability alarm and proceed to step 4. Step 4 determines the active shaping mode. If the active shaping conditions are not met, return to step 3. If the active shaping conditions are met, start the tread cleaning and shaping mode until the active shaping conditions are no longer met, then exit the active shaping mode. Step 5: After the bogie instability alarm is cleared, the vehicle continues to operate for a set distance, then checks again whether the bogie instability alarm is triggered, and returns to the road cleaning and adhesion enhancement mode.

2. The method for autonomously repairing and controlling bogie instability as described in claim 1, characterized in that, The method for detecting the polygon order of a wheel is as follows: Real-time acquisition of axle box vibration acceleration; Construct a high-order polygon early warning monitoring and bogie instability control model for wheels; The wheel high-order polygon early warning monitoring and bogie instability control model judges the real-time acquired axle box vibration acceleration and outputs the detection results: normal, prediction, early warning or alarm.

3. The method for autonomously repairing and controlling bogie instability as described in claim 1, characterized in that, The method for detecting wheel radial runout is as follows: Establish a model for early warning and monitoring of wheel radial runout and bogie instability control; Real-time acquisition of axle box vibration acceleration; The wheel radial runout early warning monitoring and bogie instability control model judges the real-time acquired axle box vibration acceleration and outputs the detection result: early warning or alarm.

4. The method for autonomously repairing and controlling bogie instability as described in claim 1, characterized in that, The wheel equivalent taper detection method is as follows: By establishing the mapping relationship between the equivalent taper of the wheel tread and the lateral acceleration of the frame, an instability alarm model of the frame based on the equivalent taper of the wheel and the active steering profile is constructed. The real-time identification of the tread equivalent taper is input into the wheel equivalent taper and bogie instability alarm model. The wheel equivalent cone and bogie instability alarm model converts the tread equivalent cone into the frame lateral acceleration, determines whether the frame lateral acceleration exceeds the threshold, and alarms if it does.

5. The method for autonomously repairing and controlling bogie instability as described in claim 4, characterized in that, The method for predicting bogie instability using wheel equivalent cone and bogie instability alarm model is as follows: If the first set value ≤ wheel equivalent cone < second set value, and the frame lateral acceleration has a consecutive peak values ​​that reach or exceed the first set threshold, it is judged as bogie instability prediction. If b consecutive peak values ​​are lower than the first set threshold, it is judged as bogie instability prediction cancellation. a and b are both natural numbers, and a > b.

6. The method for autonomously repairing and controlling bogie instability as described in claim 5, characterized in that, The method for using wheel equivalent cone and bogie instability alarm model to generate bogie instability alarm is as follows: If the wheel equivalent cone is less than the first set value; if the frame lateral acceleration has a consecutive peak values ​​that reach or exceed the second set threshold, the bogie is judged to be unstable; if b consecutive peak values ​​(whole waves) are lower than the second set threshold, the bogie instability is judged to be resolved. a and b are both natural numbers, and a > b, and the second set threshold is greater than the first set threshold.

7. The method for autonomously repairing and controlling bogie instability as described in claim 1, characterized in that, In step 5, the specific shaping conditions are as follows: The vehicle's operating speed is greater than or equal to the speed setting value. When the minimum characteristic value is greater than or equal to the set instability characteristic value c times within a set time period, the active shaping criterion is met, and the tread cleaning and shaping mode is activated.

8. The method for autonomously repairing and controlling bogie instability as described in claim 7, characterized in that, The method for calculating the minimum eigenvalue is as follows: After filtering the lateral acceleration of the bogie, the minimum value among all b consecutive peak-to-peak values ​​within a set time is calculated. The maximum value among all the minimum values ​​calculated within the set time is divided by 2, and the minimum value characteristic value is calculated and output. A minimum value characteristic value is output every 1 second using a 1-second slip.

9. The method for autonomously repairing and controlling bogie instability as described in claim 1, characterized in that, When the vehicle experiences braking, coasting, or idling signals, or when the speed is less than the speed set value, the active shaping mode will pause. It will resume active shaping mode once the signal disappears or the vehicle's operating speed is greater than or equal to the speed set value. Mileage accumulation will not be paused.

10. The method for autonomously repairing and controlling bogie instability as described in claim 1, characterized in that, The active reshaping mode is a tread surface cleaning and reshaping mode. The specific method is as follows: Once the tread cleaning and shaping conditions are met, the timing of the mileage begins. When the mileage is greater than or equal to the first set mileage, the first batch of shaping action loops is started. When the mileage is greater than or equal to the second set mileage, the second batch of shaping action loops is started. After the autonomous shaping mode completes the second batch of action loops, the autonomous shaping mode is restarted to judge whether the autonomous shaping conditions are met. If the autonomous shaping conditions are not met, the first batch of action loops and the second batch of action loops of the autonomous shaping mode are continued to be executed, and so on. If the autonomous shaping conditions are not met, the autonomous shaping mode is exited.

11. The method for autonomously repairing and controlling bogie instability as described in claim 10, characterized in that, The tread cleaning and shaping modes include high-pressure intermittent, low-pressure intermittent, low-pressure continuous, and high-pressure continuous modes.

12. A rail vehicle, characterized in that, The vehicle described herein employs the self-repairing control method for bogie instability control as described in any one of claims 1-11.

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