A vehicle component health and operational quality monitoring method, apparatus, and medium

Abstract

The application relates to the technical field of vehicle state monitoring, and discloses a kind of monitoring method, device and medium of vehicle component health state and running quality, comprising: respectively obtaining the vibration acceleration of the vehicle body and / or bogie of vehicle, and / or angular velocity and / or inclination, processing vibration acceleration, angular velocity and inclination to obtain corresponding feature data, and performing trend analysis on various feature data to output corresponding alarm signal. As can be seen, the technical scheme provided in the application can obtain the angular velocity and / or inclination of the vehicle body and / or bogie of the vehicle on the basis of analyzing the running stability of the vehicle according to the vibration acceleration, thereby determining the vehicle component health state and running quality based on the analysis of the corresponding feature data of the vibration acceleration, angular velocity and inclination, improving the accuracy of stability judgment with multi-dimensional data analysis, thereby improving the vehicle running safety factor and enhancing user experience.

Description

Technical Field

[0001] This application relates to the field of vehicle condition monitoring technology, and in particular to a method, device and medium for monitoring the health status and operational quality of vehicle components. Background Technology

[0002] With the continuous development of urban rail transit construction, people are paying increasing attention to the operational stability and safety of urban rail vehicles. Currently, the stability of vehicle operation is mainly determined by collecting and analyzing the vibration acceleration of the car body and bogies. It can be understood that monitoring the vibration acceleration of the car body and bogies is equivalent to monitoring their lateral instability. However, monitoring vehicle vibration acceleration only focuses on the vehicle's state during translation, neglecting the attitude of the car body and bogies, i.e., the rotation of the monitored object around the central axis. Therefore, analyzing only the vibration acceleration of the monitored object to determine the operational stability of the vehicle is incomplete.

[0003] Furthermore, as a vehicle's mileage increases, the car body undergoes prolonged exposure to varying loads and wheel-rail forces, which may lead to deformation, fatigue, or changes in damping in the car body and suspension system. This can alter the attitude of the car body and bogies, threatening the vehicle's safe operation. For example, it may cause unstable operation, swaying from side to side, front to back vibration, tilting, or even serious consequences such as vehicle overturning. In addition, changes in the vehicle's structural design, including variations in the distance of the suspension system, also affect the vehicle's ride quality.

[0004] Therefore, improving the monitoring of vehicle operational stability, thereby enhancing vehicle operational safety and improving users' comprehensive understanding of vehicle status, is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this application is to provide a method, device, and medium for monitoring the health status and operational quality of vehicle components, thereby improving the monitoring of the health status and operational quality of vehicle components, enhancing the vehicle's operational safety factor, and improving the user's comprehensive understanding of the vehicle's status.

[0006] To address the aforementioned technical problems, this application provides a method for monitoring the health status and operational quality of vehicle components, comprising:

[0007] Obtain the vibration acceleration, and / or angular velocity and / or tilt angle of the vehicle body and / or bogie respectively;

[0008] The vibration acceleration, angular velocity, and tilt angle are processed to obtain corresponding feature data;

[0009] Perform trend analysis on various feature data to output corresponding alarm signals.

[0010] Preferably, the trend analysis on each type of feature data to output the corresponding alarm signal comprises:

[0011] Obtaining kilometer post related data of train operation;

[0012] Based on the kilometer post related data, frequency statistical analysis is performed on each type of feature data to output the alarm signal of the corresponding line state.

[0013] Preferably, the frequency statistical analysis on each type of feature data based on the kilometer post related data to output the alarm signal of the corresponding line state comprises:

[0014] In time sequence, target data of each type of feature data greater than the corresponding preset threshold value is extracted;

[0015] In the kilometer post related data, the kilometer post corresponding to the target data is stored in a kilometer post record table;

[0016] Each time a kilometer post corresponding to the target data is obtained, the difference between the current kilometer post and each kilometer post in the kilometer post record table is calculated;

[0017] Each of the differences is sequentially determined whether within a preset range;

[0018] If within the preset range, the kilometer post counter is incremented by 1, and the current kilometer post is discarded;

[0019] If all the differences are not within the preset range, the current kilometer post is stored in the kilometer post record table;

[0020] Within a first preset period L1, it is determined whether the kilometer post counter is greater than a count threshold K1 every first preset time T1, and if so, an alarm signal of the corresponding line state is outputted;

[0021] Further, when it is determined that the kilometer post counter has not increased within the first preset period L1, the corresponding kilometer post in the kilometer post record table is deleted.

[0022] Preferably, before the determination of whether the kilometer post counter is greater than the count threshold K1 every first preset time T1 within the first preset period L1, it further comprises:

[0023] Obtaining driving speed related data of vehicle operation;

[0024] When it is determined that the driving speed in the driving speed related data has not reached a preset speed level within a second preset time T2, the feature data within the second preset time T2 is excluded;

[0025] and / or when it is determined that the number of kilometers traveled in a second preset time period T2 is less than a preset number of kilometers M, the feature data in the second preset time period is excluded.

[0026] Preferably, the trend analysis of each type of feature data to output the corresponding alarm signal comprises:

[0027] The analysis of each type of feature data to determine whether there is a continuous rise and / or fluctuation anomaly and / or trend overrun situation to output the corresponding car body and / or bogie alarm signal.

[0028] Preferably, the analysis of each type of feature data to determine whether there is a continuous rise and / or fluctuation anomaly and / or trend overrun situation to output the corresponding car body and / or bogie alarm signal comprises:

[0029] Obtaining driving speed related data of train operation;

[0030] Extracting target analysis data corresponding to the driving speed related data satisfying a first preset condition in a second preset period L2; wherein the target analysis data includes vibration acceleration related data and / or angular velocity related data and / or inclination related data, and the first preset condition is that the driving speed reaches a preset speed level and the driving speed is within a preset speed interval;

[0031] Calculating the mean value Aud of each target analysis data in a third preset time period T3;

[0032] Taking a fourth preset time period T4 as a sliding window, calculating the average value Aw, the variance Sw and the slope Bw of each sliding window; wherein the third preset time period T3 is less than the fourth preset time period T4;

[0033] Screening target sliding windows with a variance Sw less than a first preset variance S1, and calculating the first reference value Ah and the second reference value Bh by averaging each average value Aw and each slope Bw in the target sliding windows, respectively;

[0034] When it is determined that the average value Aw of any one type of data in the target analysis data of the car body and / or the bogie is greater than the first reference value Ah for a first preset number of times continuously, and the variance Sw is greater than the second reference value Bh, outputting a car body and / or bogie index trend continuous rise alarm signal corresponding;

[0035] When it is determined that the variance Sw of any one type of data in the target analysis data of the car body and / or the bogie is greater than the first preset variance S1 for a second preset number of times continuously, outputting a car body and / or bogie index trend fluctuation anomaly alarm signal corresponding;

[0036] output an alarm signal of a trend of an index of the car body and / or the bogie when it is determined that the first reference value Ah corresponding to any one of the target analysis data of the car body and / or the bogie is greater than a reference threshold A1 and the second reference value Bh corresponding to the target analysis data is greater than a reference threshold B1.

[0037] Preferably, before the step of calculating the first reference value Ah and the second reference value Bh by averaging each average value Aw and each slope Bw in the target sliding window in which the variance Sw is less than the first preset variance S1, the method further comprises the steps of:

[0038] discard all the target analysis data in the third preset period L3 when it is determined that the running speed reaches a preset speed level and / or the running distance is less than a preset distance and / or the slope Bw is less than a preset slope.

[0039] Preferably, after the step of obtaining the inclination angles of the car body and the bogie, the method further comprises the steps of:

[0040] analyzing the inclination angle related data to determine whether an index trend of the inclination angle difference between the car body and the bogie in each direction continuously rises and / or fluctuates abnormally and / or trends beyond a limit;

[0041] output an alarm signal of a component between the car body and the bogie corresponding to the alarm signal.

[0042] Preferably, the step of analyzing the inclination angle related data to determine whether an index trend of the inclination angle difference between the car body and the bogie in each direction continuously rises and / or fluctuates abnormally and / or trends beyond a limit comprises the steps of:

[0043] obtaining running speed related data of the train;

[0044] extracting inclination angle related data corresponding to the running speed related data satisfying a second preset condition in a fourth preset period L4; wherein the second preset condition is that the running speed reaches a preset speed level and the running speed is within a preset speed range;

[0045] calculating inclination angle differences between the car body and the bogie in a roll direction and / or a pitch direction and / or a yaw direction, respectively;

[0046] calculating a mean value Ave of each of the inclination angle differences in a fifth preset time length T5;

[0047] calculating an average value Ax, a variance Sx and a slope Bx of each sliding window with a sixth preset time length T6 as one sliding window; wherein the fifth preset time length T5 is less than the sixth preset time length T6.

[0048] screening a target sliding window with a variance Sx less than a second preset variance S2, and averaging each average value Ax and each slope Bx in the target sliding window to obtain a third reference value An and a fourth reference value Bn, respectively;

[0049] when it is determined that the average value Ax of any one type of the inclination difference value is greater than the third reference value An continuously for a first preset number of times, and the variance Sx is greater than the fourth reference value Bn, outputting an alarm signal indicating that the trend of the inclination difference value between the car body and the bogie in each direction is continuously rising;

[0050] when it is determined that the variance Sx of any one type of the inclination difference value is greater than the second preset variance S2 continuously for a first preset number of times, outputting an alarm signal indicating that the trend of the inclination difference value between the car body and the bogie in each direction is fluctuating abnormally;

[0051] when it is determined that the third reference value An corresponding to any one type of the inclination difference value is greater than a reference threshold A2, and the second reference value Bh corresponding thereto is greater than a reference threshold B2, outputting an alarm signal indicating that the trend of the inclination difference value between the car body and the bogie in each direction is out of limit.

[0052] Preferably, the trend analysis on each type of feature data to output a corresponding alarm signal comprises:

[0053] obtaining driving speed related data of the train running;

[0054] analyzing each type of the feature data of different vehicles of the same train to determine whether the dispersion of the vehicle indicators is abnormal, to output an alarm signal of the corresponding car body, and / or bogie, and / or components between the car body and the bogie.

[0055] Preferably, the analysis of each type of the feature data of different vehicles of the same train to determine whether the dispersion of the vehicle indicators is abnormal, to output an alarm signal of the corresponding car body, and / or bogie, and / or components between the car body and the bogie comprises:

[0056] extracting target analysis data corresponding to the driving speed related data in which the driving speed reaches a preset speed level and the driving speed is in a preset speed range within a fifth preset period L5 from the driving speed related data; wherein the target analysis data comprises vibration acceleration related data and / or angular velocity related data, and / or inclination related data, and / or inclination difference value between the car body and the bogie in each direction;

[0057] respectively calculating the average value Au of each target analysis data of the vehicle within a seventh preset time length T7;

[0058] calculating the average value At and the variance St of each target analysis data of the vehicle at different driving speed levels within a sixth preset period L6.

[0059] When it is determined that the variance St of any one type of data in the target analysis data corresponding to the vehicle is greater than the variance threshold Sm within the eighth preset time length T8, it is determined that the corresponding index dispersion of the vehicle is abnormal, and an alarm signal of the corresponding car body and / or bogie is output.

[0060] When it is determined that the variance St of any one type of data in the target analysis data corresponding to the vehicle is greater than the variance threshold Sm within the ninth preset time length T9, and the maximum value of the variance St is the same target vehicle, it is determined that the corresponding index dispersion of the target vehicle is abnormal, and an alarm signal of the corresponding car body and / or bogie is output.

[0061] Preferably, the characteristic data corresponding to the vibration acceleration, the angular velocity and the inclination angle of the bogie are acceleration characteristic values, angular velocity extreme values and angle extreme values, respectively.

[0062] Preferably, the acceleration characteristic values are effective value of lateral vibration acceleration, maximum value of lateral vibration acceleration, effective value of vertical vibration acceleration, maximum value of vertical vibration acceleration, effective value of longitudinal vibration acceleration and maximum value of longitudinal vibration acceleration; the angular velocity extreme values are extreme values of roll angular velocity, extreme values of pitch angular velocity and extreme values of yaw angular velocity; and the angle extreme values are extreme values of roll angle, extreme values of pitch angle and extreme values of yaw angle.

[0063] Preferably, the characteristic data corresponding to the vibration acceleration, the angular velocity and the inclination angle of the car body are acceleration characteristic values, angular velocity extreme values, angle extreme values and smoothness indexes, respectively.

[0064] Preferably, the acceleration characteristic values are effective value of lateral vibration acceleration, maximum value of lateral vibration acceleration, effective value of vertical vibration acceleration, maximum value of vertical vibration acceleration, effective value of longitudinal vibration acceleration and maximum value of longitudinal vibration acceleration; the angular velocity extreme values are extreme values of roll angular velocity, extreme values of pitch angular velocity and extreme values of yaw angular velocity; the angle extreme values are extreme values of roll angle, extreme values of pitch angle and extreme values of yaw angle; and the smoothness indexes are lateral smoothness index, vertical smoothness index and longitudinal impulse index.

[0065] Preferably, the inclination angle includes roll angle, pitch angle and yaw angle, and the inclination angle difference values include roll angle difference values, pitch angle difference values and yaw angle difference values.

[0066] Preferably, after the angular velocities of the car body and / or bogie are obtained, the method further comprises:

[0067] analyzing the angular velocity distribution characteristics of each type to output a first vehicle instability alarm signal.

[0068] Preferably, the analyzing of the angular velocity distribution characteristics of each type to output the vehicle first instability warning signal comprises:

[0069] sequentially sorting the angular velocities of each type according to time sequence;

[0070] judging whether the angular velocities are greater than a first threshold value according to the sorting result;

[0071] if greater than the first threshold value, increasing a counter by 1;

[0072] if not greater than the first threshold value, clearing the counter;

[0073] determining whether a value corresponding to the counter is greater than a first preset value;

[0074] if greater than the first preset value, outputting the vehicle first instability warning signal and clearing the counter;

[0075] if not greater than the first preset value, returning to the step of judging whether the angular velocities are greater than a first threshold value according to the sorting result.

[0076] Preferably, the analyzing of the angular velocity distribution characteristics of each type to output the vehicle first instability warning signal comprises:

[0077] sequentially sorting the angular velocities of each type according to time sequence within a preset time length;

[0078] judging whether the angular velocities are greater than a second threshold value according to the sorting result;

[0079] if greater than the second threshold value, increasing a counter by 1;

[0080] if not greater than the second threshold value, decreasing the counter by 1;

[0081] determining whether a value corresponding to the counter after the preset time length is greater than a second preset value;

[0082] if greater than the second preset value, outputting the vehicle first instability warning signal and clearing the counter;

[0083] if not greater than the second preset value, clearing the counter and returning to the step of judging whether the angular velocities are greater than a second threshold value according to the sorting result.

[0084] Preferably, the separately acquiring the inclination angles of the vehicle body and / or the bogie comprises:

[0085] analyzing the inclination angle distribution characteristics to output a vehicle overturning warning signal.

[0086] Preferably, the analyzing of the distribution characteristics of the various types of roll angles to output the vehicle rollover warning signal comprises:

[0087] sequentially sorting the various types of roll angles in time sequence;

[0088] sequentially determining whether each type of roll angle is greater than a corresponding third threshold value according to the sorting result;

[0089] if greater than the third threshold value, increasing a counter by 1;

[0090] if not greater than the third threshold value, resetting the counter to 0;

[0091] determining whether a value corresponding to the counter is greater than a third preset value;

[0092] if greater than the third preset value, outputting the vehicle rollover warning signal and resetting the counter to 0;

[0093] if not greater than the third preset value, returning to the step of sequentially determining whether each type of roll angle is greater than a corresponding third threshold value according to the sorting result.

[0094] Preferably, the analyzing of the distribution characteristics of the various types of roll angles to output the vehicle rollover warning signal comprises:

[0095] sequentially sorting the various types of roll angles in time sequence within a preset time period;

[0096] sequentially determining whether each type of roll angle is greater than a corresponding fourth threshold value according to the sorting result;

[0097] if greater than the fourth threshold value, increasing a counter by 1;

[0098] if not greater than the fourth threshold value, decreasing the counter by 1;

[0099] determining whether a value corresponding to the counter after the preset time period is greater than a fourth preset value;

[0100] if greater than the fourth preset value, outputting the vehicle rollover warning signal and resetting the counter to 0;

[0101] if not greater than the fourth preset value, resetting the counter to 0 and returning to the step of sequentially determining whether each type of roll angle is greater than a corresponding fourth threshold value according to the sorting result.

[0102] Preferably, the separately obtaining of the vibration acceleration of the car body and / or the bogie comprises:

[0103] analyzing the distribution characteristics of the various types of vibration accelerations to output a second vehicle instability warning signal.

[0104] Preferably, the analyzing of the vibration acceleration distribution characteristics of each type to output the second vehicle instability warning signal comprises:

[0105] sequentially sorting each type of the vibration acceleration according to time within a preset time length;

[0106] determining whether the vibration acceleration is greater than a fifth threshold value according to the sorting result;

[0107] if greater than the fifth threshold value, increasing a counter by 1;

[0108] if not greater than the fifth threshold value, resetting the counter to 0;

[0109] determining whether a value corresponding to the counter is greater than a fifth preset value;

[0110] if greater than the fifth preset value, outputting the second vehicle instability warning signal and resetting the counter to 0;

[0111] if not greater than the fifth preset value, returning to the step of determining whether the vibration acceleration is greater than the fifth threshold value according to the sorting result.

[0112] To solve the above technical problems, the application further provides a vehicle component health state and operation quality monitoring device, comprising:

[0113] an acquisition module configured to acquire vibration acceleration and / or angular velocity and / or inclination angle of a vehicle body and / or a bogie;

[0114] a processing module configured to process the vibration acceleration and / or the angular velocity and / or the inclination angle to obtain corresponding feature data;

[0115] an analysis module configured to perform trend analysis on each type of feature data to output a corresponding warning signal.

[0116] To solve the above technical problems, the application further provides a vehicle component health state and operation quality monitoring device, comprising a memory configured to store a computer program;

[0117] a processor configured to execute the computer program to implement the steps of the vehicle component health state and operation quality monitoring method.

[0118] To solve the above technical problems, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps.

[0119] The application provides a vehicle component health state and operation quality monitoring method, which comprises the following steps: acquiring vibration acceleration, angular velocity and / or inclination angle of a vehicle body and / or a bogie of a vehicle; processing the vibration acceleration, angular velocity and inclination angle to obtain corresponding characteristic data; and performing trend analysis on various characteristic data to output corresponding alarm signals.

[0120] 1) The application provides a method for obtaining vibration acceleration, angular velocity and / or inclination angle of a vehicle body and / or a bogie of a vehicle to analyze the health state of the vehicle components and the smoothness of the vehicle operation. The application can determine the health state of the vehicle body, the bogie, and the components between the vehicle body and the bogie based on the analysis of the corresponding characteristic data of the vibration acceleration, angular velocity and inclination angle, thereby providing support for the smoothness analysis of the vehicle operation. The use of multi-dimensional data type analysis improves the accuracy of the judgment of the health state of the vehicle components and the smoothness, thereby more comprehensively mastering the vehicle state and ensuring the safe operation of the vehicle.

[0121] 2) The application extends the monitoring of the translational motion of the vehicle to the rotational motion of the bogie and the vehicle body around a certain direction during operation, further improves the dimension of the analysis data, and improves the accuracy of the health state monitoring of the vehicle components and the smoothness.

[0122] 3) The application further focuses on the long-term accumulation and analysis of the vibration acceleration, inclination angle and inclination angle difference of the bogie and the vehicle body. By extracting the characteristic values of the above data, trend analysis and discrete analysis are performed on the characteristic values from different angles such as time and space to obtain the health state of the bogie, the vehicle body, and the components between the bogie and the vehicle body, thereby determining the development law of the vehicle operation posture and the vehicle maintenance threshold to enable the train operation and maintenance personnel to master the vehicle and train state in advance and provide support for the maintenance work of the operation and maintenance personnel.

[0123] 4) The application further focuses on the data distribution characteristics of the vibration acceleration, angular velocity and inclination angle of the bogie and the vehicle body, and performs real-time monitoring analysis to determine whether the vehicle operation is at risk of instability and overturning, thereby realizing the on-board diagnosis of the vehicle operation state.

[0124] 5) The application uses the characteristic values such as the vibration acceleration, angular velocity and inclination angle of the vehicle body and the bogie, combined with the kilometer marker data, to perform frequency statistics on various existing characteristic data to realize the working condition state of the poor working condition line (for example, special lines with poor bridge, tunnel and track states), thereby helping the line maintenance personnel to maintain the line and ensure the safety of train operation.

[0125] In addition, the application further provides a vehicle component health state and operation quality monitoring device and medium, which correspond to the vehicle component health state and operation quality monitoring method and have the same effects. BRIEF DESCRIPTION OF DRAWINGS

[0126] In order to more clearly illustrate the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0127] Figure 1 A flow chart of a vehicle component health state and operation quality monitoring method provided by an embodiment of the present application;

[0128] Figure 2 A schematic diagram of a train reference coordinate system provided by an embodiment of the present application;

[0129] Figure 3 A structural diagram of a vehicle component health state and operation quality monitoring device provided by an embodiment of the present application;

[0130] Figure 4 A structural diagram of a vehicle component health state and operation quality monitoring device provided by another embodiment of the present application. DETAILED DESCRIPTION

[0131] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0132] The core of the present application is to provide a vehicle component health state and operation quality monitoring method, device and medium. On the basis of analyzing the vehicle operation smoothness according to the vibration acceleration, the angular velocity and / or the inclination angle of the vehicle body and / or the bogie are further obtained. Thus, the characteristic data corresponding to the vibration acceleration, the angular velocity and the inclination angle can be analyzed to output the corresponding alarm signal, and then the operation smoothness of the vehicle is determined.

[0133] In order to make those skilled in the art better understand the present application, the present application will be further described in detail in combination with the drawings and specific embodiments.

[0134] With the continuous development of urban rail transit construction, people pay more and more attention to the stability and safety of urban rail vehicles. At present, the stability of the vehicle is determined by collecting and analyzing the vibration acceleration of the vehicle body and the bogie. It can be understood that the vibration acceleration monitoring of the vehicle body and the bogie is the monitoring of the lateral instability of the vehicle body and the bogie. However, the monitoring of the vibration acceleration of the vehicle only focuses on the state of the vehicle in the translation process, and does not focus on the attitude of the vehicle body and the bogie, that is, does not focus on the rotation of the monitoring object around the central axis. Therefore, the analysis of the vibration acceleration of the monitoring object alone to determine the stability of the vehicle is not comprehensive.

[0135] In addition, as the running mileage of the vehicle increases, the vehicle body and the suspension system of the vehicle may be deformed, fatigued or changed in damping due to the excitation of the vehicle compartment by different loads and wheel-rail forces for a long time, thereby changing the attitude of the vehicle body and the bogie, which threatens the safe operation of the vehicle. For example, it may cause the vehicle body to run unstably, shake left and right, vibrate back and forth, tilt, and even overturn the vehicle, and other serious consequences. In addition, changes in the design of the vehicle structure and the distance of the vehicle suspension device also affect the running quality of the vehicle.

[0136] In order to solve the above technical problems, improve the monitoring of the stability of the vehicle, and further improve the safety factor of the vehicle operation and the user's comprehensive understanding of the state of the vehicle, the embodiments of the present application provide a monitoring method for the health state and running quality of a vehicle component, which respectively acquires the vibration acceleration, and / or angular velocity and / or inclination angle of the vehicle body and / or bogie of the vehicle, and processes the vibration acceleration, angular velocity and inclination angle to obtain corresponding feature data to output corresponding alarm signals. Thus, the stability of the vehicle operation can be determined according to multi-dimensional data, and the safety factor of the vehicle operation is improved.

[0137] Figure 1 The flowchart of the monitoring method for the health state and running quality of a vehicle component provided by the embodiments of the present application is shown in Figure 1 The method comprises:

[0138] S10: respectively acquiring the vibration acceleration, and / or angular velocity and / or inclination angle of the vehicle body and / or bogie of the vehicle;

[0139] In specific embodiments, the stability of the vehicle can be analyzed according to the vehicle body related data, or the stability of the vehicle can be analyzed according to the bogie related data, or the vehicle body related data and the bogie related data can be acquired simultaneously for analysis to determine the stability of the vehicle, which is not limited by the present application. Of course, from the perspective of accuracy of determination, it is preferred that the related data of the vehicle body and the bogie are acquired simultaneously for analysis, wherein the related data refers to the vibration acceleration, and / or angular velocity and / or inclination angle.

[0140] It should be noted that the vibration acceleration and the angular velocity can be respectively collected by installing vibration acceleration sensors and angular velocity sensors on the vehicle body and the bogie. The vibration acceleration sensors can be two-axis vibration acceleration sensors (including vertical and lateral vibration acceleration sensors) or three-axis vibration acceleration sensors (including vertical, lateral and longitudinal vibration acceleration), which are not limited in the present application. From the perspective of monitoring accuracy, the three-axis vibration acceleration sensors are preferred. Similarly, the angular velocity sensors can be two-axis angular velocity sensors or three-axis angular velocity sensors, and the three-axis angular velocity sensors are preferred.

[0141] The inclination angle can be collected by an inclination sensor, or can be calculated according to the vibration acceleration data and the angular velocity data after the vibration acceleration sensors and the angular velocity sensors are obtained, which is not limited in the present application. That is, the present application does not limit the way of obtaining the vibration acceleration, the angular velocity and / or the inclination angle of the vehicle body and / or the bogie.

[0142] S11: processing the vibration acceleration, the angular velocity and the inclination angle to obtain corresponding feature data;

[0143] After the vibration acceleration, the angular velocity and the inclination angle of the vehicle body and the bogie are obtained through step S10, the various data are processed to obtain corresponding feature data. It should be noted that the feature data obtained is different for different objects.

[0144] Table 1 is various feature data of the bogie provided by the embodiment of the present application. As shown in Table 1, the feature data corresponding to the vibration acceleration, the angular velocity and the inclination angle of the bogie are acceleration feature values, angular velocity extreme values and angle extreme values, respectively.

[0145] The acceleration feature values include lateral vibration acceleration effective value, lateral vibration acceleration maximum value, vertical vibration acceleration effective value, vertical vibration acceleration maximum value, longitudinal vibration acceleration effective value and longitudinal vibration acceleration maximum value. The angular velocity extreme values include lateral roll angular velocity extreme value, pitch angular velocity extreme value and yaw angular velocity extreme value. The angle extreme values include lateral roll angle extreme value, pitch angle extreme value and yaw angle extreme value.

[0146] It should be noted that the effective value is also called the root mean square value, and each type of feature data is actually a numerical value calculated by the vehicle-mounted host computer every second. In addition, it should be noted that the angular velocity extreme value refers to the numerical value corresponding to the peak or trough of the angular velocity signal. If the peak is determined to be used as the extreme value for counting, the numerical value corresponding to the peak cannot be represented, that is, the numerical values corresponding to the peak and the trough cannot be used at the same time.

[0147] Table 1 Various feature data of the bogie

[0148]

[0149] Table 2 is various characteristic data of the vehicle body provided by the embodiment of the present application, as shown in Table 1, the characteristic data corresponding to the vibration acceleration, angular velocity and inclination angle of the vehicle body are acceleration characteristic value, angular velocity extreme value, angle extreme value and smoothness index.

[0150] The acceleration characteristic value includes lateral vibration acceleration effective value, lateral vibration acceleration maximum value, vertical vibration acceleration effective value, vertical vibration acceleration maximum value, longitudinal vibration acceleration effective value and longitudinal vibration acceleration maximum value. The angular velocity extreme value includes lateral roll angular velocity extreme value, vertical pitch angular velocity extreme value and longitudinal yaw angular velocity extreme value. The angle extreme value includes lateral roll angle extreme value, vertical pitch angle extreme value and longitudinal yaw angle extreme value. The smoothness index includes lateral smoothness index, vertical smoothness index and longitudinal impulse index.

[0151] Table 2 is various characteristic data of the vehicle body provided by the embodiment of the present application, as shown in Table 1, the characteristic data corresponding to the vibration acceleration, angular velocity and inclination angle of the vehicle body are acceleration characteristic value, angular velocity extreme value, angle extreme value and smoothness index.

[0152]

[0153] It can be understood that the vehicle suspension is composed of primary suspension and secondary suspension. The primary spring is the spring between the vehicle axle box and the bogie, and the secondary spring is the spring between the bogie and the vehicle body, which is generally an air spring. Figure 2 A schematic diagram of a train reference coordinate system provided by the embodiment of the present application is shown in FIG. 1. As shown in FIG. 1, the train reference coordinate system is established with the train lateral direction as the X axis, the longitudinal direction as the Y axis and the vertical direction as the Z axis. When the vehicle rotates around the X axis, it is lateral roll, and the included angle between the lateral roll and the horizontal plane formed by the X-Y axis is the lateral roll angle. When the vehicle rotates around the Y axis, it is pitch, and the included angle between the pitch and the horizontal plane formed by the X-Y axis is the pitch angle. When the vehicle rotates around the Z axis, it is yaw, and the included angle between the yaw and the plane formed by the X-Z axis is the yaw angle. Figure 2 Therefore, the inclination angle includes the lateral roll angle, the pitch angle and the yaw angle. In the implementation, after the lateral roll angle, the pitch angle and the yaw angle are determined, the running posture of the vehicle can be basically determined.

[0154] S12: performing trend analysis on the various characteristic data to output the corresponding alarm signal.

[0155] Further, the trend analysis is performed on the various characteristic data to output the corresponding alarm signal, that is, the analysis is performed on the various characteristic data to determine the smoothness of the vehicle running.

[0156]

[0157] ​In implementation, trend analysis can be performed on various characteristic data of the bogie and the car body to obtain the corresponding attitude under different line excitations. In analysis, the kilometer marker related data of the train operation is acquired first, and then frequency statistical analysis is performed on various characteristic data according to the kilometer marker related data to output the alarm signal of the corresponding line state.

[0158] Further, it is also possible to determine whether there is a continuous rise and / or fluctuation anomaly and / or trend over-limit condition by analyzing the trend of various characteristic data, and then output the corresponding alarm signal of the car body and / or the bogie.

[0159] Of course, the running speed related data of the train operation can also be acquired, and then the various characteristic data of different vehicles of the same train are analyzed to determine whether the vehicle index is abnormal in dispersion, so as to output the alarm signal of the corresponding car body, and / or the bogie, and / or the components between the car body and the bogie.

[0160] In specific implementation, the technical solution provided in the present application respectively monitors the vibration acceleration, angular velocity and inclination angle, realizes the combination of dynamic monitoring and static monitoring, and then determines the running attitude of the vehicle. Therefore, after the angular velocity of the car body and / or the bogie is acquired, the distribution characteristics of various angular velocities are analyzed to output the first instability alarm signal of the vehicle. After the inclination angle of the car body and / or the bogie is acquired, the distribution characteristics of various inclination angles are analyzed to output the overturning alarm signal of the vehicle. And after the vibration acceleration of the car body and / or the bogie is acquired, the distribution characteristics of various vibration accelerations are analyzed to output the second instability alarm signal of the vehicle. Thus, through the above analysis, different alarm signals are output to determine the current vehicle running quality state.

[0161] It should be noted that the technical solution provided in the present application, when the monitoring object is the car body, analyzes any one or more of the vibration acceleration, angular velocity and inclination angle data of the car body to determine the vehicle running state. Similarly, when the monitoring object is the bogie, any one or more of the vibration acceleration, angular velocity and inclination angle data of the bogie is acquired to determine the vehicle running state. In addition, if the monitoring object is the suspension component between the car body and the bogie, the inclination angle difference of the car body and the bogie in each direction needs to be acquired, and the inclination angle difference is analyzed to determine the vehicle running stability.

[0162] The working state of the bogie, the car body and the vehicle suspension part will affect the smooth running of the vehicle. The vehicle part health state and running quality monitoring method provided by the embodiment of the application comprises: obtaining the vibration acceleration, and / or angular velocity and / or inclination of the car body and / or bogie of the vehicle respectively, processing the vibration acceleration, angular velocity and inclination to obtain corresponding feature data, and performing trend analysis on various feature data to output a health state alarm signal of the corresponding part, so as to simultaneously realize the monitoring of the smooth running of the vehicle. The technical solution provided by the application expands the original monitoring of vibration acceleration data to the monitoring of acceleration, angular velocity and inclination data, and expands the original monitoring of the translation motion of the vehicle to the concern of the rotation motion of the bogie and the car body around a direction during the running process, further improves the analysis method, and thus more comprehensively masters the vehicle state and ensures the running safety of the vehicle.

[0163] In specific embodiments, after obtaining the kilometer marker related data of the train running, the frequency statistical analysis is performed on various feature data based on the kilometer marker related data to output an alarm signal of the corresponding line state, which comprises:

[0164] Step 1: sequentially extracting target data of various feature data greater than the corresponding preset threshold value in time sequence.

[0165] In the implementation, the data is analyzed according to the time of saving the data, that is, the target data of various feature data greater than the corresponding preset threshold value is extracted in time sequence. For example, in the feature data corresponding to the vibration acceleration, the preset threshold value corresponding to the effective value of the lateral vibration acceleration is Q, and when the target data is extracted, only the data with the effective value of the lateral vibration acceleration greater than Q is extracted as the target data.

[0166] Step 2: storing the kilometer marker corresponding to the target data in the kilometer marker record table.

[0167] The kilometer marker k corresponding to the target data in the obtained kilometer marker related data is stored in the kilometer marker record table. For example, there may be kilometer markers meeting the condition in one day, which are recorded as k1, k2…kn respectively, forming a dynamically updated kilometer marker record table.

[0168] Step 3: when the kilometer marker corresponding to each target data is obtained, the difference between the current kilometer marker and each kilometer marker in the kilometer marker record table is calculated, and whether each difference is within the preset range is sequentially judged. If it is within the preset range, the kilometer marker counter is incremented by 1, and the current kilometer marker is discarded. If all the differences are not within the preset range, the current kilometer marker is stored in the kilometer marker record table.

[0169] When each target data corresponding to the kilometer marker k is obtained in step 2, the difference between the current kilometer marker and each kilometer marker in the kilometer marker record table is calculated, and then it is determined whether the difference is within a preset range, for example, whether the difference is within [-1 km, +1 km]. If yes, the kilometer marker counter is increased by 1, indicating that the current kilometer marker is unavailable and is discarded. If all the differences are not within the preset range, the current kilometer marker is stored in the kilometer marker record table.

[0170] In step 4, it is determined whether the kilometer marker counter is greater than the count threshold K1 every first preset time length T1 within the first preset period L1. If yes, an alarm signal of the corresponding line state is output. When it is determined that the kilometer marker counter is not increased within the first preset period L1, the corresponding kilometer marker in the kilometer marker record table is deleted.

[0171] Suppose the first preset period L1 is 3 days and the first preset time length T1 is 1 day. Within 3 days, it is determined once a day whether the kilometer marker counter is greater than the count threshold K1. If yes, an alarm signal of the corresponding line state is output to remind the ground maintenance personnel to maintain the road. If the kilometer marker counter is not increased within 3 consecutive days, the corresponding kilometer marker in the kilometer marker record table is deleted.

[0172] In implementation, in order to ensure the accuracy of the output result, the data to be counted needs to be filtered. That is, before it is determined whether the kilometer marker counter is greater than the count threshold K1 every first preset time length T1 within the first preset period L1, the driving speed related data of the vehicle is obtained. When it is determined that the driving speed in the driving speed related data does not reach the preset speed level (for example, does not reach the speed level of 250 km / h) within the second preset time length T2 (for example, within one day), the feature data within the second preset time length is discarded. And / or when it is determined that the driving distance within the second preset time length T2 is less than the preset distance M, the feature data within the second preset time length is discarded.

[0173] The vehicle component health state and running quality monitoring method provided by the embodiment of the application can not only realize the state monitoring of the vehicle body, the bogie and the suspension component and the running stability monitoring of the vehicle, but also can monitor the working condition state of the running line with poor working condition (for example, the line with poor bridge, tunnel and track states) by frequency counting of various existing feature data after combining the kilometer marker related data, and output an alarm signal of the corresponding line state to remind the ground maintenance personnel to maintain the line.

[0174] Further, the trend analysis of various feature data to output corresponding alarm signals can also be that the various feature data is analyzed to determine whether there is a continuous rise and / or fluctuation anomaly and / or trend overrun, to output the alarm signals of the corresponding vehicle body and / or bogie. Specifically, the following steps are included:

[0175] Step S10: Obtain the running speed related data of the train operation, and extract the target analysis data corresponding to the running speed related data meeting the first preset condition in the second preset period L2; wherein the target analysis data includes vibration acceleration related data and / or angular velocity related data and / or inclination related data, and the first preset condition is that the running speed reaches a preset speed level and the running speed is in a preset speed interval.

[0176] In implementation, after obtaining the running speed related data of the train operation, the running speed related data in the second preset period L2 (for example, 2 months) is selected, and the target analysis data corresponding to the running speed related data in which the running speed reaches a preset speed level and the running speed is in a preset speed interval is extracted. For example, the vibration acceleration related data and / or angular velocity related data and / or inclination related data corresponding to the running speed related data in which the running speed levels reach 250km / h, 300km / h and 350km / h respectively and the running speed is in the preset interval of [-10km / h, +10km / h] is extracted.

[0177] Corresponding vibration acceleration related data, angular velocity related data and inclination related data will be generated at each running speed. When analyzing the running stability of the vehicle, some invalid data needs to be removed according to the running speed related data, and then the vibration acceleration related data and / or angular velocity related data and / or inclination related data corresponding to the valid running speed are taken as the target analysis data.

[0178] It can be understood that the vibration acceleration related data, angular velocity related data and inclination related data include various feature data described in the above embodiments, and when extracting the target analysis data, any one or more types of data meeting the first preset condition can be selected for analysis.

[0179] Step 1: Calculate the mean value Aud of each target analysis data in the third preset time length T3, and take the fourth preset time length T4 as a sliding window to calculate the average value Aw, the variance Sw and the slope Bw of each sliding window; wherein the third preset time length T3 is less than the fourth preset time length T4;

[0180] For example, the third preset time length T3 is 1 day, and the fourth preset time length T4 is n days, the average value Aud of the target analysis data per day is calculated, and then the average value Aud of each type of data under each speed level is analyzed. That is, taking n days as a fixed sliding window, sliding one day each time, the average value Aw, the variance Sw and the slope Bw of each sliding window are calculated, wherein the calculation formulas of the average value Aw, the variance Sw and the slope Bw are respectively:

[0181] ;

[0182] ;

[0183] ;

[0184] Step 2: screening the target sliding window with the variance Sw less than the first preset variance S1, and calculating the first reference value Ah and the second reference value Bh by averaging the average value Aw and the slope Bw in the target sliding window respectively;

[0185] Further, the historical average value and the historical slope are calculated as the analysis basis for updating data. That is, the target sliding window with Sw < S1 is screened, and in fact, the screened target sliding window is the window with smaller data fluctuation. Then the first reference value Ah and the second reference value Bh are calculated by averaging the average value Aw and the slope Bw in each target sliding window. Of course, the average value can be further calculated based on the first reference value Ah and the second reference value Bh, and whether to further calculate the average value can be determined according to the data search amount of the ground analysis system.

[0186] Step 3: analyzing each type of data to output the continuous rising and / or fluctuation anomaly and / or trend overrun alarm signal corresponding to the car body and / or bogie.

[0187] Specifically, when it is determined that the average value Aw of any one type of data in the target analysis data of the car body and / or bogie continuously reaches the first preset number of times, and the variance Sw is greater than the second reference value Bh, the continuous rising trend alarm signal of the corresponding car body and / or bogie index is output.

[0188] When it is determined that the variance Sw of any one type of data in the target analysis data of the car body and / or bogie continuously reaches the second preset number of times, and the first preset variance S1 is greater than the first reference value Ah, the fluctuation anomaly trend alarm signal of the corresponding car body and / or bogie index is output.

[0189] When it is determined that the first reference value Ah corresponding to any one type of data in the target analysis data of the car body and / or bogie is greater than the reference threshold A1, and the second reference value Bh corresponding thereto is greater than the reference threshold B1, the trend overrun alarm signal of the corresponding car body and / or bogie index is output.

[0190] In the implementation, in order to ensure the monitoring accuracy of the smooth running of the vehicle, the data needs to be filtered. As a preferred embodiment, before the first reference value Ah and the second reference value Bh are calculated, if it is determined that the driving speed reaches the preset speed level (for example, the driving speed does not reach 250 km / h) in the third preset period L3, and / or the driving distance is less than the preset distance (for example, the driving distance is less than 50 kilometers), and / or the slope Bw is less than the preset slope (for example, Bw < -10), all target analysis data in the third preset period L3 are excluded.

[0191] It can be understood that when the driving speed does not reach the preset level or the driving distance is small, it indicates that the vehicle may not have traveled, and the generated data is invalid data, so it needs to be excluded. When the slope Bw is small, it indicates that the data fluctuation in the sliding window is large, and it also needs to be excluded, thereby improving the monitoring accuracy.

[0192] The vehicle component health state and running quality monitoring method provided in the embodiments of the application focuses on the accumulation and analysis of various data over a long period of time. By analyzing the time distribution of various data, whether there is a continuous rise and / or fluctuation anomaly and / or trend exceeding limit of various characteristic data is analyzed to determine the health state of the corresponding vehicle body and / or bogie. An alarm signal of the corresponding vehicle body and / or bogie is outputted to remind ground workers to maintain the corresponding components, thereby improving the driving safety of the vehicle and providing support for the smoothness monitoring of the vehicle running.

[0193] As a preferred embodiment, after the inclination angles of the vehicle body and the bogie are obtained, the inclination angle related data is analyzed to determine whether the inclination angle difference index trend between the vehicle body and the bogie in each direction continuously rises and / or fluctuates abnormally and / or trends exceed limit, and then an alarm signal of the corresponding component between the vehicle body and the bogie is outputted. Specifically, the following steps are included:

[0194] Step 1: Obtain driving speed related data of the train running, and extract inclination angle related data corresponding to the driving speed related data meeting a second preset condition in a fourth preset period L4; wherein the second preset condition is that the driving speed reaches a preset speed level and the driving speed is in a preset speed interval.

[0195] For example, the inclination angle related data corresponding to the driving speed related data whose speed level reaches 250 km / h and whose driving speed is in the preset interval [-10 km / h, +10 km / h] is extracted. The inclination angle related data includes roll angle, pitch angle and yaw angle.

[0196] Step 2: calculate the angle difference between the car body and the bogie in the roll and / or pitch and / or yaw directions respectively, and calculate the average value Ave of each angle difference in the fifth preset time T5;

[0197] Step 3: take the sixth preset time T6 as a sliding window, calculate the average value Ax, the variance Sx and the slope Bx of each sliding window; wherein the fifth preset time T5 is less than the sixth preset time T6;

[0198] Wherein, the calculation formula of the average value Ax, the variance Sx and the slope Bx are respectively:

[0199] ;

[0200] ;

[0201] ;

[0202] Step 4: screen the target sliding window with the variance Sx less than the second preset variance S2, and calculate the third reference value An and the fourth reference value Bn by averaging each average value Ax and each slope Bx in the target sliding window respectively;

[0203] The window with Sx < S2 is taken as the target sliding window, and then the third reference value An and the fourth reference value Bn are obtained by averaging each average value Ax and each slope Bx in the target sliding window. Similarly, the average value can be further calculated on the basis of the third reference value An and the fourth reference value Bn, which is not limited by the present application, and can be adjusted according to the actual data amount.

[0204] Step S24: analyze various types of data to output the continuous rising and / or fluctuation abnormality and / or trend overrun alarm signal corresponding to the angle difference between the car body and the bogie in each direction.

[0205] Specifically, when it is determined that the average value Ax of any one type of angle difference is greater than the third reference value An continuously for the first preset number of times, and the variance Sx is greater than the fourth reference value Bn, the angle difference index trend continuous rising alarm signal between the car body and the bogie in each direction is output.

[0206] When it is determined that the variance Sx of any one type of angle difference is greater than the second preset variance S2 continuously for the first preset number of times, the angle difference index trend fluctuation abnormality alarm signal between the car body and the bogie in each direction is output.

[0207] When it is determined that the third reference value An corresponding to any one of the inclination angle difference values is greater than the reference threshold A2, and the second reference value Bh corresponding thereto is greater than the reference threshold B2, an inclination angle difference value index trend out-of-limit alarm signal between the vehicle body and the bogie in each direction is output. The vehicle component health state and operation quality monitoring method provided in the embodiments of the present application focuses on the accumulation and analysis of various types of data over a long period of time. By analyzing the time distribution of various types of data, the inclination angle related data is analyzed to determine whether the inclination angle difference value index trend between the vehicle body and the bogie in each direction is continuously rising and / or abnormally fluctuating and / or out-of-trend alarm signal, and then the health state alarm signal of the component, i.e., the suspension component, between the vehicle body and the bogie of the vehicle can be output according to the inclination angle difference related data, so as to remind the staff to maintain the corresponding component, thereby improving the driving safety of the vehicle, and also providing support for the smoothness monitoring of the vehicle operation.

[0208] In specific embodiments, the technical solutions provided in the present application can also perform trend analysis and comparison on different individuals of the same type of monitoring object. Taking a train as the analysis object, different vehicles constituting the train are analyzed. In implementation, first, the driving speed related data of the train operation is obtained, and then various types of feature data of different vehicles of the same train are analyzed, and then it is determined whether the vehicle index is abnormally discrete, and the alarm signal of the corresponding vehicle body, and / or bogie, and / or component between the vehicle body and the bogie is output. The analysis process specifically includes the following steps:

[0209] Step 1: Extract target analysis data corresponding to the driving speed related data in which the driving speed reaches a preset speed level and the driving speed fluctuates within a preset speed interval in a fifth preset period L5; wherein the target analysis data includes vibration acceleration related data and / or angular velocity related data, and / or inclination angle related data, and / or inclination angle difference values between the vehicle body and the bogie in each direction;

[0210] For example, the fifth preset period L5 is 10 days, the preset speed level is 250 km / h, and the preset speed interval is [-10 km / h, +10 km / h], and the vibration acceleration related data and / or angular velocity related data, and / or inclination angle related data, and / or inclination angle difference values between the vehicle body and the bogie in each direction corresponding to the driving speed related data in which the driving speed reaches 250 km / h and the driving speed fluctuates within [-10 km / h, +10 km / h] in 10 days are taken as the target analysis data.

[0211] Step 2: Calculate the mean value Au of each target analysis data of the vehicle in a seventh preset time length T7, and calculate the average value At and the variance St of each target analysis data of the vehicle at different driving speed levels in a sixth preset period L6;

[0212] For example, the seventh preset time length T7 is one day, and the average value At and the variance St of the train at different speed levels are calculated in one day as a unit, and the calculation formulas of the average value At and the variance St are respectively:

[0213] ;

[0214] ;

[0215] Wherein, n is the number of vehicles in a train, i.e. the number of carriages.

[0216] Step 3: analyze various types of data to output corresponding alarm signals.

[0217] Specifically, when it is determined that the variance St of any one type of data in the target analysis data corresponding to the vehicle is greater than the variance threshold Sm within the eighth preset time length T8 (for example, for 3 consecutive days), it is determined that the dispersion degree of the corresponding index of the vehicle is abnormal, and the alarm signal of the corresponding car body and / or bogie is output.

[0218] If it is determined that the variance St of any one type of data in the target analysis data corresponding to the vehicle is greater than the variance threshold Sm within the ninth preset time length T9 (for example, for 5 consecutive days), and the maximum value of the variance St is the same target vehicle, it is determined that the dispersion degree of the corresponding index of the target vehicle is abnormal, and the alarm signal of the corresponding car body and / or bogie is output.

[0219] The vehicle component health state and running quality monitoring method provided by the embodiment of the application pays attention to the long-time accumulation and analysis of various types of data, and performs dispersion analysis, i.e. spatial analysis, on the distribution of various types of data of the bogie and the car body of different vehicles of the same train, so as to output a pre-warning of the dispersion degree abnormality of a certain vehicle, thereby outputting the health state alarm signal of the corresponding car body and / or bogie and / or the suspension component between the car body and the bogie, so as to remind the staff to maintain the corresponding components, improve the driving safety of the vehicle, and also provide support for the smoothness monitoring of the vehicle running.

[0220] As a preferred embodiment, after the angular velocity of the car body and / or the bogie is obtained, the distribution characteristics of various types of angular velocity can be analyzed to output a first instability alarm signal of the vehicle. Specifically, in the implementation, the angular velocities are sorted in time sequence to obtain a sorting result, and it is judged in turn according to the sorting result whether the angular velocity is greater than a first threshold G1, if it is greater than the first threshold, the counter is incremented by 1, otherwise, the counter is cleared.

[0221] When the value corresponding to the current counter is greater than a first preset value H1, the first instability alarm signal of the vehicle is output, and the counter is cleared. When the value corresponding to the current counter is not greater than the first preset value H1, it is continued to be judged whether the angular velocity is greater than the first threshold G1.

[0222] In addition, the analysis of the angular velocity distribution characteristics can also be to sort the angular velocities in a preset time period in time sequence, and then determine whether the angular velocity is greater than the second threshold G2 based on the sorting result. If it is greater, the counter is incremented by 1, otherwise, the counter is decremented by 1. If the value corresponding to the counter is greater than the second preset value H2 after the preset time period, a first vehicle instability warning signal is output, and the counter is cleared. Of course, if the value corresponding to the counter is not greater than the second preset value H2 after the preset time period, the counter is cleared first, and then it is determined whether the angular velocity is greater than the second threshold G2.

[0223] It can be seen that the vehicle component health state and running quality monitoring method provided by the embodiments of the application is not limited to monitoring the health state of the vehicle body, the bogie, and the suspension components between the vehicle body and the bogie. The real-time monitoring of the vehicle running stability state is realized by analyzing the angular velocity distribution characteristics, and a first vehicle instability warning signal is output. That is, the vehicle running stability is determined by analyzing the angular velocity distribution characteristics, and the user's overall understanding of the vehicle running state is improved.

[0224] Of course, after obtaining the inclination angles of the vehicle body and / or the bogie, the inclination angle distribution characteristics can also be analyzed to output a vehicle overturning warning signal.

[0225] Specifically, the inclination angles can be sorted in time sequence, and it is determined whether the inclination angles are greater than the corresponding third threshold G3 based on the sorting result. If it is greater than the third threshold G3, the counter is incremented by 1, otherwise, the counter is cleared. If the value corresponding to the counter is greater than the third preset value H3, a vehicle overturning warning signal is output, and the counter is cleared. If the value corresponding to the counter is not greater than the third preset value H3, it is determined whether the inclination angles are greater than the corresponding third threshold G3.

[0226] In addition, the analysis of the inclination angle distribution characteristics can also be to sort the inclination angles in a preset time period in time sequence, and then determine whether the inclination angles are greater than the corresponding fourth threshold G4 based on the sorting result. If it is greater, the counter is incremented by 1, otherwise, the counter is decremented by 1. When it is determined that the value corresponding to the counter is greater than the fourth preset value H4 after the preset time period, a vehicle overturning warning signal is output, and the counter is cleared. If the value corresponding to the counter is not greater than the fourth preset value H4, the counter is cleared first, and then it is determined whether the inclination angles are greater than the corresponding fourth threshold G4.

[0227] It can be seen that the vehicle component health state and running quality monitoring method provided by the embodiment of the present application is not limited to monitoring the health state of the vehicle body, the bogie, and the suspension component between the vehicle body and the bogie. After the inclination angles of the vehicle body and / or the bogie are acquired, the inclination angle distribution characteristics can be monitored and analyzed in real time to output a vehicle overturning warning signal, so as to determine whether the vehicle has the risk of overturning and improve the running safety of the vehicle.

[0228] Similarly, after the vibration acceleration of the vehicle body and / or the bogie is acquired, the vibration acceleration distribution characteristics can be analyzed to output a second vehicle instability warning signal.

[0229] Specifically, the vibration accelerations in a preset time period are sorted in time sequence, and whether the vibration acceleration is greater than a fifth threshold G5 is determined according to the sorting result in sequence. If the vibration acceleration is greater than the fifth threshold G5, the counter is incremented by 1. If the vibration acceleration is not greater than the fifth threshold G5, the counter is cleared.

[0230] When it is determined that the value corresponding to the current counter is greater than a fifth preset value, the second instability warning signal is output, and the counter is cleared. If the value corresponding to the counter is not greater than the fifth preset value, whether the vibration acceleration is greater than the fifth threshold G5 is determined.

[0231] The vehicle component health state and running quality monitoring method provided by the embodiment of the present application is not limited to monitoring the health state of the vehicle body, the bogie, and the suspension component between the vehicle body and the bogie. After the vibration acceleration of the vehicle body and / or the bogie is acquired, the vibration acceleration distribution characteristics are analyzed to realize real-time monitoring of the running stability state of the vehicle, so as to output the second vehicle instability warning signal, further improve the monitoring accuracy of the running stability of the vehicle, and improve the comprehensive understanding of the running state of the vehicle by the user.

[0232] In the above embodiment, the vehicle component health state and running quality monitoring method is described in detail, and the present application also provides a corresponding embodiment of a vehicle component health state and running quality monitoring device. It should be noted that the embodiment of the device part is described from two angles, one is based on the functional module, and the other is based on the hardware structure.

[0233] Figure 3 The structure diagram of a vehicle component health state and running quality monitoring device provided by the embodiment of the present application is shown in FIG. 1. The device includes: Figure 3

[0234] The acquisition module 10 is configured to acquire the vibration acceleration and / or the angular velocity and / or the inclination angle of the vehicle body and / or the bogie.

[0235] ​The processing module 11 is configured to process the vibration acceleration and / or the angular velocity and / or the inclination angle to obtain corresponding feature data.

[0236] The analysis module 12 is configured to perform trend analysis on the feature data to output a corresponding alarm signal.

[0237] Since the embodiments of the device part correspond to the embodiments of the method part, the embodiments of the device part are described in the description of the embodiments of the method part, and are not described here.

[0238] The vehicle component health state and running quality monitoring device provided in the embodiments of the present application comprises: vibration acceleration and / or angular velocity and / or inclination angle of a vehicle body and / or a bogie are acquired respectively, the vibration acceleration, the angular velocity and the inclination angle are processed to obtain corresponding feature data, and trend analysis is performed on the feature data to output a corresponding alarm signal. As can be seen, the technical solution provided in the present application can obtain the angular velocity and / or the inclination angle of the vehicle body and / or the bogie on the basis of analyzing the vibration acceleration to analyze the running stability of the vehicle. Thus, the running stability of the vehicle can be determined based on the analysis of the corresponding feature data of the vibration acceleration, the angular velocity and the inclination angle, the judgment accuracy of the stability is improved in multiple dimensions, and the running safety factor of the vehicle is improved, and the user experience is improved.

[0239] Figure 4 A structural diagram of a vehicle component health state and running quality monitoring device provided in another embodiment of the present application is shown in FIG. 2. The vehicle component health state and running quality monitoring device comprises: a memory 20 configured to store a computer program; Figure 4

[0240] A processor 21 is configured to execute the computer program to realize the steps of the vehicle component health state and running quality monitoring method mentioned in the above embodiments.

[0241] The vehicle component health state and running quality monitoring device provided in the embodiments of the present application can include but is not limited to a smart phone, a tablet computer, a notebook computer or a desktop computer, etc.

[0242] ​The processor 21 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one of a hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA), etc. The processor 21 can also include a main processor and a co-processor. The main processor is a processor for processing data in a wake-up state, also referred to as a central processing unit (CPU). The co-processor is a low-power processor for processing data in a standby state. In some embodiments, the processor 21 can be integrated with a graphics processor (GPU) for rendering and drawing content to be displayed by a display screen. In some embodiments, the processor 21 can further include an artificial intelligence (AI) processor for processing machine learning-related computing operations.

[0243] The memory 20 can include one or more computer-readable storage media that can be non-transitory. The memory 20 can further include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein the computer program is loaded and executed by the processor 21, and can implement the related steps of the vehicle component health state and operation quality monitoring method disclosed in any of the preceding embodiments. In addition, the resources stored by the memory 20 can further include an operating system 202 and data 203, etc., and the storage mode can be temporary storage or permanent storage. The operating system 202 can include Windows, Unix, Linux, etc. The data 203 can include, but is not limited to, related data involved in the vehicle component health state and operation quality monitoring method, etc.

[0244] In some embodiments, the vehicle component health state and operation quality monitoring device can further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0245] Those skilled in the art can understand that the structure shown in the above embodiments does not constitute a limitation on the vehicle component health state and operation quality monitoring device, and can include more or fewer components than those shown in the drawings. Figure 4 The structure shown in the above embodiments does not constitute a limitation on the vehicle component health state and operation quality monitoring device, and can include more or fewer components than those shown in the drawings.

[0246] The vehicle component health state and operation quality monitoring device provided by the embodiment of the application comprises a memory and a processor. When the processor executes a program stored in the memory, the following method can be realized: a vehicle component health state and operation quality monitoring method.

[0247] The vehicle component health state and operation quality monitoring device provided by the embodiment of the application can obtain the angular velocity and / or the inclination angle of the vehicle body and / or the bogie of the vehicle on the basis of analyzing the vibration acceleration to analyze the smoothness of the vehicle operation, so that the smoothness of the vehicle operation can be determined based on the analysis of the corresponding characteristic data of the vibration acceleration, the angular velocity and the inclination angle, the judgment accuracy of the smoothness is improved by multi-dimensional data analysis, and the safety factor of the vehicle operation is improved, and the user experience is improved.

[0248] Finally, the application also provides an embodiment corresponding to a computer readable storage medium. The computer readable storage medium stores a computer program. When the computer program is executed by a processor, the steps described in the above method embodiment are realized.

[0249] It can be understood that if the method in the above embodiment is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and executes all or part of the steps of the method described in each embodiment of the application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0250] The above describes in detail the vehicle component health state and operation quality monitoring method, device and medium provided by the application. The embodiments in the specification are described in a progressive manner, and each embodiment mainly describes the differences from other embodiments. The same or similar parts of each embodiment can be referred to. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part. It should be pointed out that, for ordinary skilled in the art, without departing from the principles of the application, some improvements and modifications can be made to the application, and these improvements and modifications also fall within the protection scope of the claims of the application.

[0251] It also needs to be explained that in the present specification, the relational terms such as first and second and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

Claims

1. A method of monitoring the health and operational quality of a vehicle component, characterized by, The method comprises: obtaining vibration acceleration and / or angular velocity and / or inclination angle of a vehicle body and / or bogie respectively; processing the vibration acceleration, the angular velocity and the inclination angle to obtain corresponding feature data; when the inclination angles of the vehicle body and the bogie are obtained respectively, further comprising: analyzing the inclination angle related data to determine whether the inclination angle difference index trend between the vehicle body and the bogie in each direction continuously rises and / or fluctuates abnormally and / or trends beyond the limit; outputting an alarm signal of a component between the vehicle body and the bogie corresponding to the analysis result; the analysis of the inclination angle related data to determine whether the inclination angle difference index trend between the vehicle body and the bogie in each direction continuously rises and / or fluctuates abnormally and / or trends beyond the limit comprises: obtaining train running speed related data; extracting inclination angle related data corresponding to the train running speed related data satisfying a second preset condition in a fourth preset period L4; wherein the second preset condition is that the train running speed reaches a preset speed level and the train running speed is in a preset speed interval; calculating the inclination angle difference between the vehicle body and the bogie in the roll, pitch and / or yaw directions respectively; calculating the average value Ave of each inclination angle difference in a fifth preset time T5; taking a sixth preset time T6 as a sliding window, calculating the average value Ax, the variance Sx and the slope Bx of each sliding window; wherein the fifth preset time T5 is less than the sixth preset time T6; screening target sliding windows with the variance Sx less than a second preset variance S2, and calculating the average value An and the average value Bn of each average value Ax and each slope Bx in the target sliding windows respectively; when it is determined that any one type of average value Ax of the inclination angle difference continuously exceeds the third reference value An for a first preset number of times, and the variance Sx exceeds the fourth reference value Bn, outputting an inclination angle difference index trend continuously rising alarm signal between the vehicle body and the bogie in each direction; when it is determined that any one type of variance Sx of the inclination angle difference continuously exceeds the second preset variance S2 for a first preset number of times, outputting an inclination angle difference index trend fluctuation abnormality alarm signal between the vehicle body and the bogie in each direction; when it is determined that any one type of third reference value An of the inclination angle difference exceeds a reference threshold A2, and any one type of second reference value Bh exceeds a reference threshold B2, outputting an inclination angle difference index trend beyond limit alarm signal between the vehicle body and the bogie in each direction; performing trend analysis on each type of feature data to output a corresponding alarm signal.

2. The method of claim 1, wherein The trend analysis on each type of feature data to output a corresponding alarm signal comprises: obtaining train kilometer marker related data; performing frequency statistical analysis on each type of feature data based on the kilometer marker related data to output an alarm signal of a corresponding line state.

3. The method of claim 2, wherein, The frequency statistical analysis on each type of feature data based on the kilometer marker related data to output an alarm signal of a corresponding line state comprises: extracting target data of each type of feature data greater than a corresponding preset threshold in time sequence; storing the kilometer marker corresponding to the target data in the kilometer marker record table in the kilometer marker related data; When each milepost corresponding to the target data is obtained, a difference between the current milepost and each milepost in the milepost record table is calculated; It is judged in turn whether each difference is within a preset range; If it is within the preset range, the milepost counter is incremented by 1, and the current milepost is discarded; If all the differences are not within the preset range, the current milepost is stored in the milepost record table; It is determined whether the milepost counter is greater than a count threshold K1 every first preset time length T1 within a first preset period L1, and if so, an alarm signal of a corresponding line state is outputted; When it is determined that the milepost counter is not increased within the first preset period L1, the corresponding milepost in the milepost record table is deleted.

4. The method of claim 3, wherein, Before the determination whether the milepost counter is greater than the count threshold K1 every first preset time length T1 within the first preset period L1, the method further comprises: Obtaining driving speed related data of vehicle operation; When it is determined that the driving speed in the driving speed related data does not reach a preset speed level within a second preset time length T2, the feature data within the second preset time length T2 is excluded; And / or when it is determined that the driving distance within a second preset time length T2 is less than a preset distance M, the feature data within the second preset time length is excluded.

5. The method of claim 1, wherein, The trend analysis of each type of feature data to output a corresponding alarm signal comprises: Analyzing each type of feature data to determine whether there is a continuous rise and / or fluctuation anomaly and / or trend overrun, to output an alarm signal of a corresponding car body and / or bogie.

6. The method of claim 5, wherein, The analysis of each type of feature data to determine whether there is a continuous rise and / or fluctuation anomaly and / or trend overrun, to output an alarm signal of a corresponding car body and / or bogie comprises: Obtaining driving speed related data of train operation; Extracting target analysis data corresponding to the driving speed related data satisfying a first preset condition within a second preset period L2; wherein the target analysis data comprises vibration acceleration related data and / or angular velocity related data and / or inclination related data, and the first preset condition is that the driving speed reaches a preset speed level and the driving speed is within a preset speed interval; Respectively calculating the mean value Aud of each target analysis data within a third preset time length T3; Taking a fourth preset time length T4 as a sliding window, calculating the average value Aw, the variance Sw and the slope Bw of each sliding window; wherein the third preset time length T3 is less than the fourth preset time length T4; Filtering target sliding windows with the variance Sw less than a first preset variance S1, and respectively calculating the mean value of each average value Aw and each slope Bw in the target sliding window to obtain a first reference value Ah and a second reference value Bh; When it is determined that the average value Aw of any one type of data in the target analysis data of the car body and / or the bogie is greater than the first reference value Ah continuously for a first preset number of times, and the variance Sw is greater than the second reference value Bh, an alarm signal of a continuous rise of a corresponding car body and / or bogie index trend is outputted; output an alarm signal of a corresponding car body and / or bogie when it is determined that the variance Sw of any one of the target analysis data of the car body and / or the bogie is greater than the first preset variance S1 for a second preset number of times in succession; output an alarm signal of a corresponding car body and / or bogie when it is determined that the first reference value Ah corresponding to any one of the target analysis data of the car body and / or the bogie is greater than the reference threshold A1, and the second reference value Bh is greater than the reference threshold B1.

7. The method of claim 6, wherein, Before the step of screening the target sliding window with the variance Sw less than the first preset variance S1, the method further comprises: discard all the target analysis data in the third preset period L3 when it is determined that the running speed reaches a preset speed level, and / or the running distance is less than a preset distance, and / or the slope Bw is less than a preset slope.

8. The method of claim 1, wherein, The step of performing trend analysis on each type of feature data to output a corresponding alarm signal comprises: obtain running speed related data of a train; analyze each type of feature data of different vehicles of the same train to determine whether the dispersion of the vehicle indicators is abnormal, and output an alarm signal of a corresponding car body, and / or bogie, and / or a component between the car body and the bogie.

9. The method of claim 8, wherein, The step of analyzing each type of feature data of different vehicles of the same train to determine whether the dispersion of the vehicle indicators is abnormal, and output an alarm signal of a corresponding car body, and / or bogie, and / or a component between the car body and the bogie comprises: extract target analysis data corresponding to the running speed related data in which the running speed reaches a preset speed level and the running speed is within a preset speed range in a fifth preset period L5 from the running speed related data; wherein the target analysis data comprises vibration acceleration related data and / or angular velocity related data, and / or inclination related data, and / or inclination difference values between the car body and the bogie in each direction; calculate the mean value Au of each target analysis data of the vehicle in a seventh preset time period T7; calculate the mean value At and the variance St of each target analysis data of the vehicle at different running speed levels in a sixth preset period L6; determine that the corresponding indicators of the target vehicle are abnormal in dispersion and output an alarm signal of a corresponding car body and / or bogie when it is determined that the variance St of any one of the target analysis data corresponding to the vehicle is greater than the variance threshold Sm in an eighth preset time period T8; determine that the corresponding indicators of the target vehicle are abnormal in dispersion and output an alarm signal of a corresponding car body and / or bogie when it is determined that the variance St of any one of the target analysis data corresponding to the vehicle is greater than the variance threshold Sm in a ninth preset time period T9, and the maximum value of the variance St is the same target vehicle.

10. The method of claim 1, wherein, The feature data corresponding to the vibration acceleration, the angular velocity and the inclination of the bogie are acceleration feature values, angular velocity extreme values and angle extreme values, respectively. The acceleration characteristic value is specifically a lateral vibration acceleration effective value, a lateral vibration acceleration maximum value, a vertical vibration acceleration effective value, a vertical vibration acceleration maximum value, a longitudinal vibration acceleration effective value, and a longitudinal vibration acceleration maximum value; the angular velocity extreme value is specifically a roll angular velocity extreme value, a pitch angular velocity extreme value, and a yaw angular velocity extreme value; and the angle extreme value is specifically a roll angle extreme value, a pitch angle extreme value, and a yaw angle extreme value.

11. The method of claim 1, wherein, The characteristic data corresponding to the vibration acceleration, the angular velocity, and the inclination angle of the vehicle body are an acceleration characteristic value, an angular velocity extreme value, an angle extreme value, and a smoothness index. The acceleration characteristic value is specifically a lateral vibration acceleration effective value, a lateral vibration acceleration maximum value, a vertical vibration acceleration effective value, a vertical vibration acceleration maximum value, a longitudinal vibration acceleration effective value, and a longitudinal vibration acceleration maximum value; the angular velocity extreme value is specifically a roll angular velocity extreme value, a pitch angular velocity extreme value, and a yaw angular velocity extreme value; and the angle extreme value is specifically a roll angle extreme value, a pitch angle extreme value, and a yaw angle extreme value; and the smoothness index is specifically a lateral smoothness index, a vertical smoothness index, and a longitudinal impulse index.

12. The method of claim 1, wherein, The inclination angle includes a roll angle, a pitch angle, and a yaw angle, and correspondingly, the inclination angle difference value includes a roll angle difference value, a pitch angle difference value, and a yaw angle difference value.

13. The method of claim 1, wherein, After the angular velocities of the vehicle body and / or the bogie are acquired respectively, the following steps are further included: The distribution characteristics of the angular velocities are analyzed to output a first vehicle instability warning signal.

14. The method of claim 13, wherein, The distribution characteristics of the angular velocities are analyzed to output a first vehicle instability warning signal, including the following steps: The angular velocities are sorted in time sequence; It is determined in sequence according to the sorting result whether the angular velocities are greater than a first threshold value; If the angular velocities are greater than the first threshold value, a counter is increased by 1; If the angular velocities are not greater than the first threshold value, the counter is cleared; It is determined whether a value corresponding to the counter is greater than a first preset value; If the value corresponding to the counter is greater than the first preset value, the first vehicle instability warning signal is output, and the counter is cleared; If the value corresponding to the counter is not greater than the first preset value, the step of determining in sequence according to the sorting result whether the angular velocities are greater than the first threshold value is returned to.

15. The method of claim 13, wherein, The distribution characteristics of the angular velocities are analyzed to output a first vehicle instability warning signal, including the following steps: The angular velocities within a preset time length are sorted in time sequence; It is determined in sequence according to the sorting result whether the angular velocities are greater than a second threshold value; If the angular velocities are greater than the second threshold value, a counter is increased by 1; If the angular velocities are not greater than the second threshold value, the counter is decreased by 1; It is determined whether a value corresponding to the counter after the preset time length is greater than a second preset value; If the value corresponding to the counter is greater than the second preset value, the first vehicle instability warning signal is output, and the counter is cleared; If the value corresponding to the counter is not greater than the second preset value, the counter is cleared, and the step of determining in sequence according to the sorting result whether the angular velocities are greater than the second threshold value is returned to.

16. The method of claim 1, wherein After the inclination angles of the vehicle body and / or the bogie are acquired respectively, the following steps are further included: The distribution characteristics of the inclination angles are analyzed to output a vehicle rollover warning signal.

17. The method of claim 16, wherein The analysis of the distribution characteristics of the various roll angles to output a vehicle rollover warning signal comprises: sorting the various roll angles in time sequence; determining whether each of the roll angles is greater than a corresponding third threshold value according to the sorting result; if greater than the third threshold value, then the counter is incremented by 1; if not greater than the third threshold value, then the counter is cleared; determining whether the current value corresponding to the counter is greater than a third preset value; if greater than the third preset value, outputting the vehicle rollover warning signal and clearing the counter; if not greater than the third preset value, returning to the step of determining whether each of the roll angles is greater than a corresponding third threshold value according to the sorting result.

18. The method of claim 16, wherein, The analysis of the distribution characteristics of the various roll angles to output a vehicle rollover warning signal comprises: sorting the various roll angles in time sequence within a preset time period; determining whether each of the roll angles is greater than a corresponding fourth threshold value according to the sorting result; if greater than the fourth threshold value, then the counter is incremented by 1; if not greater than the fourth threshold value, then the counter is decremented by 1; determining whether the value corresponding to the counter after the preset time period is greater than a fourth preset value; if greater than the fourth preset value, outputting the vehicle rollover warning signal and clearing the counter; if not greater than the fourth preset value, clearing the counter and returning to the step of determining whether each of the roll angles is greater than a corresponding fourth threshold value according to the sorting result.

19. The method of claim 1, wherein After the vibration accelerations of the car body and / or the bogie are obtained respectively, the method further comprises: analyzing the distribution characteristics of the various vibration accelerations to output a second vehicle instability warning signal.

20. The method of claim 19, wherein The analysis of the distribution characteristics of the various vibration accelerations to output a second vehicle instability warning signal comprises: sorting the various vibration accelerations in time sequence within a preset time period; determining whether each of the vibration accelerations is greater than a fifth threshold value according to the sorting result; if greater than the fifth threshold value, then the counter is incremented by 1; if not greater than the fifth threshold value, then the counter is cleared; determining whether the current value corresponding to the counter is greater than a fifth preset value; if greater than the fifth preset value, outputting the second vehicle instability warning signal and clearing the counter; if not greater than the fifth preset value, returning to the step of determining whether each of the vibration accelerations is greater than a fifth threshold value according to the sorting result.

21. A device for monitoring the health and operational quality of a vehicle component, characterized by, comprises: an acquisition module, configured to acquire vibration accelerations and / or angular velocities and / or roll angles of a car body and / or a bogie; a processing module, configured to process the vibration accelerations and / or the angular velocities and / or the roll angles to obtain corresponding feature data; after the roll angles of the car body and the bogie are obtained respectively, the method further comprises: analyzing roll angle related data to determine whether an index trend of a roll angle difference between the car body and the bogie in each direction is continuously rising and / or fluctuating abnormally and / or trend overrunning; outputting an alarm signal of a corresponding component between the car body and the bogie; the analysis of the roll angle related data to determine whether an index trend of a roll angle difference between the car body and the bogie in each direction is continuously rising and / or fluctuating abnormally and / or trend overrunning comprises: acquiring train running speed related data; extracting the inclination angle related data corresponding to the driving speed related data meeting a second preset condition in a fourth preset period L4; wherein the second preset condition is that the driving speed reaches a preset speed level and the driving speed is in a preset speed interval; calculating inclination angle difference values of the car body and the bogie in the roll and / or pitch and / or yaw directions respectively; calculating the average value Ave of each of the inclination angle difference values in a fifth preset time length T5; calculating the average value Ax, the variance Sx and the slope Bx of each of the sliding windows with a sixth preset time length T6 as a sliding window; wherein the fifth preset time length T5 is less than the sixth preset time length T6; screening target sliding windows with the variance Sx less than a second preset variance S2, and obtaining the third reference value An and the fourth reference value Bn by averaging each average value Ax and each slope Bx in the target sliding windows respectively; outputting a car body and bogie inclination angle difference value index trend continuous rise alarm signal when it is determined that any one type of the inclination angle difference value has the average value Ax greater than the third reference value An for a first preset number of times continuously, and the variance Sx is greater than the fourth reference value Bn; outputting a car body and bogie inclination angle difference value index trend fluctuation abnormality alarm signal when it is determined that any one type of the inclination angle difference value has the variance Sx greater than the second preset variance S2 for a first preset number of times continuously; outputting a car body and bogie inclination angle difference value index trend over-limit alarm signal when it is determined that any one type of the inclination angle difference value has the third reference value An greater than a reference threshold A2 and the second reference value Bh greater than a reference threshold B2; an analysis module configured to perform trend analysis on each type of feature data to output a corresponding alarm signal.

22. A device for monitoring the health and operational quality of a vehicle component, characterized by a memory configured to store a computer program; a processor configured to execute the computer program to implement the steps of the vehicle component health state and operation quality monitoring method according to any one of claims 1 to 20.

23. A computer-readable storage medium, characterized in that, a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the steps of the vehicle component health state and operation quality monitoring method according to any one of claims 1 to 20.

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