Analysis method for abnormal wear of pantograph carbon slide plate

Abstract

The present application belongs to the technical field of pantograph carbon slide plate detection, and particularly relates to a pantograph carbon slide plate abnormal wear analysis method, comprising multi-source online collection of vehicle positioning, pantograph posture, overhead line geometric parameters and environmental temperature data; posture statistical features are extracted through a probability density function, and a pull-out value spatial distribution weight is calculated; pantograph posture abnormalities are determined based on a statistical distribution confidence interval, and the correlation between temperature fluctuations and geometric parameter deviations is analyzed using a Pearson correlation coefficient to identify the influence of frost heaving; and finally, operation and maintenance decisions are generated according to a multi-dimensional fusion model. The present application realizes quantitative tracing of wear states, breaks down professional data barriers, and ensures operation safety.

Description

Technical Field

[0001] This invention belongs to the field of pantograph carbon sliding plate detection technology, and particularly relates to a method for analyzing abnormal wear of pantograph carbon sliding plates. Background Technology

[0002] In the operation of urban rail transit systems, the dynamic coupling relationship between the pantograph and the overhead contact line is the core foundation for maintaining vehicle power acquisition and ensuring the safe and stable operation of the line. As a key medium for energy transfer, the quality of the sliding contact between the pantograph's carbon sliding plate and the overhead contact line directly determines the stability of current collection and the service life of key components.

[0003] With the continuous expansion of urban rail transit operations, the problem of abnormal wear on the carbon sliding plates of the pantograph has become increasingly prominent. Especially in the early stages of new line opening, during seasonal changes with drastic temperature differences, or under special geographical conditions, the non-uniform wear of the carbon sliding plates often exhibits characteristics of sudden onset, high frequency, and complex causes. This abnormal wear not only leads to a sharp increase in the replacement cost of the carbon sliding plates, but more seriously, its potential mechanical impact risk directly threatens current collection safety and may even cause pantograph-catenary accidents.

[0004] In the existing technology, research on the wear problem of the carbon sliding plate of the pantograph has mainly followed two relatively independent technical paths.

[0005] The first approach focuses on real-time monitoring and prediction at the vehicle end. This involves capturing images of the carbon fiber skateboard using high-definition imaging equipment mounted on the vehicle roof, quantifying wear depth using image recognition algorithms, or collecting the dynamic response of the pantograph using acceleration and strain sensors, and assessing the skateboard's remaining lifespan using a digital twin model. The advantage of this approach is that it provides intuitive quantitative data on wear, but it is essentially "post-event monitoring" or "symptom prediction." Its analytical depth is limited to the vehicle's internal workings, making it difficult to trace the underlying causes—such as external environmental factors or infrastructure—after detecting abnormal wear.

[0006] The second approach focuses on the static design and geometric optimization of the overhead contact system. This includes improving the polygonal planar layout of the rigid overhead contact system, or using optimization algorithms such as particle swarm optimization to refine the pull-out value and anchor length of the contact wire. The aim is to induce uniform wear of the carbon sliding plate from a physical layout perspective. While this approach fully considers current balance during the design phase, it often neglects dynamically changing external variables during operation because it is based on static parameters under ideal operating conditions.

[0007] However, in-depth analysis of a large amount of engineering practice data reveals a deep and inherent technical contradiction in the two aforementioned technical approaches when dealing with modern complex operating environments. Specifically, the abnormal wear of the pantograph carbon skid plate is not a single-dimensional physical process, but a comprehensive result of the high coupling between vehicle dynamics, catenary geometry, and environmental climate evolution. Existing monitoring systems, lacking cross-disciplinary collaborative analysis logic, result in a severe disconnect between technical dimensions: vehicle-side sensors can detect abnormal pantograph posture or a surge in acceleration, but cannot determine whether this abnormality stems from mechanical fatigue of the pantograph support or from excessive gradient of the catenary in a specific section; while catenary monitoring methods can detect deviations in the pull-out value of the positioning point, it is difficult to quantify the contribution of this deviation to the transient lateral force generated by the pantograph during operation under specific ambient temperatures. Especially during seasonal changes or extremely cold weather, abnormal frost heave caused by thermal expansion and contraction of the catenary can lead to minute but critical drifts in the geometric parameters of the positioning point. This dynamic disturbance, which changes with the environment, is difficult to capture in existing static layout models, and is often misjudged as random noise in single skid plate prediction models.

[0008] The main reason is that existing technical solutions have failed to establish a comprehensive analytical model that integrates "pantograph attitude, overhead contact line geometry, and environmental meteorology." This information silo effect means that in the event of a severe wear-prone fault, the operations department can often only speculate based on phenomena observed in a single discipline. This leads to long-standing disputes between vehicle maintenance and power supply maintenance departments regarding fault attribution and responsibility allocation, making it difficult to establish an effective closed-loop management system.

[0009] Therefore, breaking down data barriers between disciplines and integrating the pantograph's forward and backward tilt angles, the real-time pull-out value and conductor height of the overhead contact line, and dynamic changes in ambient temperature into a unified spatiotemporal analysis framework, and accurately identifying the root cause of abnormal wear of the carbon sliding plate through feature extraction and probability statistics of multidimensional data, whether it is pantograph's own attitude inaccuracy, statistical deviation of the distribution of overhead contact line pull-out value, or contact line freezing and heave deformation driven by ambient temperature, has become a technical problem that urgently needs to be solved in the current rail transit field to improve the level of refined operation and maintenance and ensure operational safety. Summary of the Invention

[0010] To address the technical problems in the aforementioned background technology, such as the disconnect between pantograph monitoring and catenary geometric parameter analysis, the inability to accurately pinpoint the root cause of abnormal wear on the carbon contactor in complex coupled environments, unclear division of maintenance responsibilities, and low maintenance efficiency, this invention provides a method for analyzing abnormal wear on the pantograph carbon contactor. By establishing a deep fusion model of pantograph dynamic attitude, catenary static and dynamic geometric parameters, and multi-dimensional environmental meteorological indicators, this method enables quantitative tracing and accurate assessment of the wear state of the pantograph carbon contactor.

[0011] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for analyzing abnormal wear of the carbon sliding plate of a pantograph includes the following steps: S1: Acquiring Heterogeneous Data: During the vehicle's operation, a hardware acquisition cluster deployed on the vehicle's roof collects real-time vehicle positioning information, pantograph attitude information, overhead contact line geometric parameters, and real-time ambient temperature information; wherein, the pantograph attitude information includes the forward and backward tilt angles output by the pantograph tilt angle measurement component. i 1 and left and right tilt angles i 2; The contact wire geometric parameter information includes the contact wire guide height value at the current vehicle position obtained through a non-contact measurement component. d x With pull value l x .

[0012] In the aforementioned data acquisition process, an online monitoring system based on multi-source sensing fusion is implemented. This online monitoring system is deployed on the vehicle under test, utilizing the vehicle's dynamic operation to collect real-time vehicle positioning information, pantograph attitude information, overhead contact line geometric parameters, and real-time ambient temperature information. The vehicle positioning information is acquired through a combination of an onboard high-precision global navigation satellite system and an inertial navigation system, and its output parameters include the current route number, travel direction, section identifier, kilometer marker value, and real-time vehicle speed. The pantograph attitude information is acquired through a pantograph tilt measurement component installed on the pantograph frame and slide bracket. This component uses a high-frequency response microelectromechanical system tilt sensor and outputs a pantograph attitude vector. G θ =( i 1, i 2), where, i 1 represents the forward and backward tilt angle of the pantograph carbon slider relative to the horizontal reference plane. i 2. Characterizes the left and right tilt angles of the pantograph carbon contactor relative to the horizontal reference plane. The contact wire geometric parameters are acquired using a non-contact lidar or high-speed imaging measurement component mounted on the vehicle roof, which detects and outputs the contact wire guide height value at the current vehicle position (xx) in real time. d x With pull value l x This constitutes the geometric parameter vector of the overhead contact system. J x =( d x , l xThe real-time ambient temperature information is acquired through an external integrated high-precision platinum resistance temperature sensor, and the ambient temperature value T is output in real time.

[0013] S2: Data preprocessing: Spatiotemporal synchronization, signal cleaning, and statistical feature extraction are performed on the collected heterogeneous data; for pantograph attitude data, the pantograph attitude probability density function is constructed by aggregating observation data from the same geographical location under different running trips; for pull-out value data, the pull-out value distribution function reflecting the symmetry of the force point distribution on the carbon slide plate surface is constructed using physical intervals as statistical units.

[0014] This invention performs spatiotemporal synchronization processing and statistical feature extraction on massive amounts of heterogeneous data collected. Firstly, for pantograph attitude data, this invention performs spatiotemporal synchronization processing and statistical feature extraction on data from the same location. x In different running trips N The observed data are aggregated to construct a probability density function for the pantograph's attitude. Specifically, the pantograph's position... x Forward and backward tilt angles i 1,x and left and right tilt angle i 2,x All variables are treated as random variables, and their expected values ​​and standard deviations are calculated using the maximum likelihood estimation method.

[0015] For the forward and backward tilt angles, its mean The standard deviation is obtained by calculating the arithmetic mean of N sample values. This reflects the dispersion of the pantograph's attitude at that location. Similarly, the mean value is calculated for the left and right tilt angles. with standard deviation Based on the above statistical parameters, this invention establishes a pantograph attitude probability density model, including a forward / backward tilt angle probability density model and a left / right tilt angle probability density model. The pantograph attitude probability density model eliminates random errors caused by accidental track impacts or wind load interference during a single operation, providing a robust benchmark for subsequent attitude anomaly determination.

[0016] S3: Data Analysis: Based on the feature parameters obtained from preprocessing, anomaly tracing is carried out from three dimensions: First, perform pantograph attitude anomaly analysis: by checking whether the pantograph attitude values ​​observed in real time fall within the confidence interval based on long-term statistical distribution, determine whether there is an attitude anomaly of the pantograph caused by mechanical structure deviation. Second, conduct anomaly analysis of pull-out value distribution: calculate the ratio of the weight of positive pull-out value distribution to the weight of negative pull-out value distribution within the target interval, and determine whether there is a systematic statistical bias in the catenary layout by the degree of deviation of the ratio from the preset threshold interval; Third, conduct an analysis of abnormal frost heave of the contact wire and its correlation with the environment: calculate the Pearson correlation coefficient between the ambient temperature fluctuation ΔT and the offset of the contact wire geometric parameters, and determine whether there is dynamic geometric drift of the contact wire induced by drastic changes in ambient temperature based on the correlation test results. S4: Anomaly Assessment: Based on the anomaly assessment results obtained from data analysis, match the corresponding physical maintenance items and automatically generate a decision conclusion that includes the specific fault source and maintenance handling suggestions.

[0017] Preferably, in step S1, the vehicle positioning information is obtained through a combination of an onboard high-precision global navigation satellite system and an inertial navigation system. The output parameters include the route number, travel direction, section identifier, kilometer marker value, and real-time vehicle speed. The pantograph tilt measurement component uses a microelectromechanical system tilt sensor with a sampling frequency set to no less than 50Hz to fully capture the transient pitch and roll characteristics of the pantograph when the vehicle passes through a position where the stiffness of the contact wire changes abruptly. The real-time ambient temperature information is collected by a high-precision platinum resistance temperature sensor equipped with a radiation shield, and the real-time ambient temperature value T is output.

[0018] Preferably, step S2, which involves signal cleaning and spatiotemporal synchronization of the acquired heterogeneous data, includes the following processes: A signal smoothing algorithm based on median filtering is used to eliminate pulse-type noise generated by electromagnetic interference from pantograph sparks. Using spatial resampling technology, data collected at different operating speeds are mapped onto a standard kilometer grid based on vehicle positioning information. The resampling step size is set to 0.1 meters. Cubic spline interpolation is used to fill in missing grid data, and weighted average method is used to fuse duplicate data to ensure strong consistency alignment of data from multiple trips in the physical coordinate dimension.

[0019] Preferably, the specific process for constructing the pantograph attitude probability density function is as follows: S21: Position the pantograph. x Forward and backward tilt angles i 1,x and left and right tilt angle i 2,x Treating them as random variables, the maximum likelihood estimation method is used to... N Statistical analysis was performed on sample values ​​from each run. S22: Calculate the position of the pantograph carbon sliding plate x The mean of the forward and backward tilt angles at the location and standard deviation : ; ; S23: Calculate the position of the pantograph carbon sliderx The mean of the left and right tilt angles at the location and standard deviation : ; ; S24: Establish a pantograph attitude probability density model based on the mean and standard deviation, including: Forward and backward tilt angle probability density model: ; Left and right tilt angle probability density model: ; Here: i This represents the train number. For example: i =6 represents the 6th train trip so far; i 1,x ( i ) represents the train at the i During the trip, the pantograph is in position x The angle of inclination at the front and rear; i 2,x ( i ) represents the train at the i During the trip, the pantograph is in position x The left and right tilt angles at that location; The probability distribution represents the forward and backward tilt angle of the pantograph at position x; The probability distribution represents the left and right tilt angles of the pantograph at position x; S25: Filtering random orbital impact interference using the pantograph attitude probability density model: Track impact, wind disturbance, and transient vibration are all short-term random noises. N The average was applied in the trip statistics; Probability density model with mean m Centered, standard deviation s The fluctuation bandwidth forms the normal attitude distribution range; Transient spikes and pulse offsets during a single run are judged to be low-probability events and are directly filtered out. Extracting the mechanical characteristics benchmark of the pantograph itself: by , As the inherent mechanical attitude reference of the pantograph at this position; in terms of standard deviation , As the boundary of normal fluctuations; The final result is a stable benchmark that is unaffected by random disturbances and reflects only the mechanical structural characteristics of the pantograph itself, which is used for subsequent anomaly detection.

[0020] Preferably, the specific determination process for pantograph attitude anomaly analysis in step S3 is as follows: Set a safety factor n To verify the current real-time observation of the pantograph's position. x Forward and backward tilt angles i 1,x and left and right tilt angle i 2,x Does it meet the corresponding confidence interval constraints? ; ; If the real-time observation value exceeds the above confidence interval, it is determined that the pantograph has an abnormal attitude at the corresponding position and is associated with the vehicle pantograph bracket mechanical loosening, balancing mechanism failure or geometric deviation fault. Wherein, the safety factor n It features dynamic weight configuration: when a vehicle passes through a curved section, the system automatically adjusts the left and right tilt angles based on the superelevation parameters of the outer rail. i The judgment threshold correction coefficient of 2 is increased by 20% to compensate for normal attitude deviation caused by the physical tilt of the vehicle body.

[0021] Preferably, the safety factor n It also performs dynamic attenuation correction based on the cumulative operating mileage of the pantograph slider: When the wear of the pantograph slider reaches more than 80% of the warning value, the system automatically reduces the safety factor. n The value is used to improve the detection sensitivity of pantograph attitude instability anomalies; Simultaneously, during the preprocessing stage, the aerodynamic lift compensation coefficient table based on the real-time operating vehicle speed is invoked to calculate the average forward and backward tilt angles. Dynamic corrections are performed to eliminate the impact of differences in aerodynamic forces at different operating speeds on attitude determination results.

[0022] Preferably, the process of analyzing the anomaly distribution of the pull-out value in step S3 includes: Define the pull-out value distribution function within the specified physical range. L ( x ): ; in, L ( x () represents the distribution function of the output value; l ( x ) represents the probability density function of the pulled value; The cumulative probability distribution of positive values ​​within this interval is calculated using integration: ; The cumulative probability distribution of negative values ​​within this interval is calculated using integration: ; in, l ( x () represents the actual measured value function; L max 、L min Set value constraint limits for the overhead contact line design. L max Possible value +350 mm , L min Possible value: -350 mm .

[0023] Calculate the forward pull-out value distribution weight L + Weight L of the negative pull-out value distribution − The ratio, i.e., L + / L − ; Determine whether the ratio is within a preset threshold range. r 1, r 2], that is r 1≤L + / L − ≤ r 2. If the ratio deviates from this range, it is determined that the layout of the contact wire in this range has a statistical bias, which induces excessive wear on one side of the carbon sliding plate.

[0024] The preferred threshold range is [0.8, 1.2].

[0025] By comparing the probability coverage range of positive and negative pull-out values, the symmetry of the force point distribution on the carbon slide plate surface within this interval can be quantitatively evaluated. Simultaneously, for the contact line guide height data, the preprocessing module calculates the average guide height of all anchor segment positioning points on an interval-by-interval basis. μd x with standard deviation σd x It is used to characterize the smoothness of the overhead contact line.

[0026] Preferably, the specific process for conducting abnormal frost heave and environmental correlation analysis of the contact line in step S3 is as follows: The average ambient temperature at the reference time point is defined as the reference temperature. T m0 Calculate the absolute value of the difference between the real-time average ambient temperature and the reference temperature to obtain the ambient temperature fluctuation ΔT = |T mi −T m0 |; When ΔT exceeds a preset significance threshold, the geometric parameter offset calculation is triggered to extract the location. x Change in conduction height Δ at point D x Change in pull-out value Δ L x ; The correlation coefficient between guide height offset and temperature fluctuation is calculated using the Pearson correlation coefficient formula. : ; Calculate the correlation coefficient between pull-out value offset and temperature fluctuation. : ; in, n 1 represents the number of consecutive statistical days, ranging from 3 to 7 days.

[0027] Preferably, the statistical days n The value of 1 is controlled by the temperature gradient monitoring logic: When the system detects that the real-time temperature gradient exceeds the preset rate of change threshold, it automatically records the number of days. n 1. Shorten to the lower limit value to improve the speed of capturing the dynamic response trend of the overhead contact line; When determining the correlation coefficient A correlation coefficient greater than 0.5 and between the pull-out value offset and temperature fluctuation. When the value is greater than 0.5, the system determines that the contact wire has experienced freezing expansion or thermal contraction jamming caused by drastic temperature fluctuations, resulting in abnormal concentration of local contact pressure, which in turn leads to uneven wear.

[0028] Finally, based on the output of the analysis module, maintenance decision suggestions are automatically generated to achieve anomaly assessment. If the analysis result indicates an abnormal pantograph attitude, the output is "Adjust pantograph attitude" and the corresponding vehicle number; if the analysis result indicates an abnormal pull-out value distribution, the output is "Adjust the pull-out value distribution of the corresponding interval positioning point"; if the analysis result determines that the contact wire is abnormally frost-prone, the assessment conclusion is "Adjust the contact wire slope of the corresponding interval and check the busbar jamming status". The anomaly assessment process in step S4 is as follows: If the determination result is that the pantograph attitude is abnormal, the command "Adjust the pantograph attitude of the corresponding vehicle number" will be output. If the determination result is that the distribution of pull-out values ​​is abnormal, the command "Adjust the distribution of pull-out values ​​of positioning points in the corresponding kilometer marker interval" will be output. If the determination result is an environmental correlation anomaly, the command "Adjust the slope of the contact line in the corresponding section and check the blockage status of the busbar" will be output. And based on the change in guide height Δ D x The system will issue graded warnings based on whether the preset safety threshold is exceeded, and automatically match the maintenance and emergency repair path based on the geographic information system in the judgment conclusion.

[0029] The beneficial effects of this invention include: The beneficial effects of this invention are reflected in: First, it breaks down the data barriers between vehicle and power supply specialties in traditional rail transit maintenance. By integrating pantograph attitude, catenary geometry, ambient temperature, and spatial location information in multiple dimensions, a closed-loop logic from "phenomenal monitoring" to "root cause analysis" is established, which can automatically identify the physical source of abnormal wear on carbon sliding plates, greatly shortening the fault diagnosis cycle.

[0030] Second, statistical feature extraction technology based on long-term big data was introduced. By utilizing the probability density function of the pantograph attitude and the safety factor judgment criterion, it is possible to accurately distinguish between the vehicle's own mechanical deviation and the transient response caused by random track fluctuations, effectively reducing the false alarm rate of anomaly judgment and providing a scientific quantitative basis for precise maintenance.

[0031] Third, by statistically analyzing the spatial distribution of pull-out values, the rationality of the overhead contact system design and the balance of slip plate wear were quantitatively assessed. Compared with traditional fixed-point measurements, this evaluation method based on statistical distribution is better able to reflect the systemic risks during the operation of the section and is conducive to guiding the optimization of the overhead contact system layout.

[0032] Fourth, a correlation model between temperature fluctuations and the offset of contact network geometric parameters was proposed. By calculating the Pearson correlation coefficient, the impact of ambient temperature on contact network frost heave and jamming can be quantitatively identified, solving the technical problem of difficulty in quantifying the causes of wear and tear in cold seasons or under conditions of drastic temperature changes, and providing early warning support for seasonal operation and maintenance.

[0033] Fifth, it possesses a high degree of intelligent decision-making capability. The output conclusions directly correspond to specific physical maintenance items, significantly improving the precision of urban rail transit operation and maintenance, and ensuring the safety and economy of line operation. Attached Figure Description

[0034] Figure 1 This is a schematic flowchart of the abnormal wear analysis method for the pantograph carbon sliding plate of the present invention; Figure 2 This is a schematic diagram of the forward and backward tilt angle of the pantograph carbon sliding plate of the present invention - upward movement; Figure 3 This is a schematic diagram of the forward and backward tilt angle of the pantograph carbon sliding plate of the present invention during descent. Figure 4This is a schematic diagram of the left and right tilt angles of the pantograph carbon sliding plate of the present invention - right turn; Figure 5 This is a schematic diagram of the left and right tilt angles of the pantograph carbon sliding plate of the present invention - left turn. Detailed Implementation

[0035] The following is in conjunction with the appendix Figure 1~Figure 5 The present invention will be further described in detail below: Example 1 See appendix Figure 1-Figure 5 As shown, a method for analyzing abnormal wear of the pantograph carbon contactor is presented. This method relies on a highly integrated multi-source sensing fusion online monitoring architecture. At the physical level, this architecture consists of a hardware acquisition cluster deployed on the top of the vehicle under test. Its core logic lies in constructing a multi-dimensional spatiotemporal correlation database by simultaneously capturing the pantograph's dynamic attitude, catenary geometric parameters, and environmental meteorological indicators. Specifically, the data acquisition stage serves as the starting point of the entire analysis process. It utilizes the natural dynamic process of the vehicle's operation to extract physical quantities that characterize the coupling state between the pantograph and the catenary in real time. Vehicle positioning information is obtained through an onboard high-precision global navigation satellite system and inertial navigation system (GNSS / INS). This system can maintain centimeter-level positioning accuracy in weak signal environments common in urban rail transit, such as underground tunnels and high-rise building obstructions, through the dead reckoning function of the inertial measurement unit (IMU). The output raw data stream is parsed by the onboard processing unit and transformed into a standard message format containing the vehicle's current line number, line direction, section identifier, kilometer marker value, and real-time operating speed.

[0036] Meanwhile, pantograph attitude information is acquired through a pantograph tilt measurement component installed at key stress nodes of the pantograph's lower frame and slide plate support. This component incorporates a high-frequency response microelectromechanical system (MEMS) triaxial tilt sensor, possesses strong electromagnetic interference resistance, and can output the pantograph's dynamic attitude vector in three-dimensional space. G θ =( i 1 ,i 2). In this vector system, i 1 is defined as the forward and backward tilt angle of the pantograph carbon slide relative to the horizontal reference plane of the vehicle's running direction. It is mainly used to capture the pitch deviation caused by the aerodynamic lift during the pantograph raising and lowering process or high-speed operation. iThe second parameter characterizes the left and right tilt angles of the pantograph's carbon sliding plate relative to the horizontal reference plane. Abnormal fluctuations in this value are usually directly related to the lateral stability of the pantograph support or the geometric asymmetry of the pantograph itself. To ensure the transient integrity of the captured data, this embodiment requires that the sampling frequency of the pantograph tilt angle measurement component must be no less than 50Hz. This frequency parameter was selected based on the results of dynamic simulation, aiming to ensure that the system can completely record the transient impact response of the pantograph generated when the vehicle passes through locations where the stiffness of the contact wire changes abruptly, such as tunnel entrances and segment insulators.

[0037] For detecting the geometric parameters of the overhead contact system, a non-contact lidar or high-speed imaging measurement module mounted on the vehicle roof was used. This module detects and outputs the current vehicle position in real time during vehicle operation using laser scanning or structured light vision algorithms. x Contact wire conductance value at the location d x With pull value l x This constitutes the geometric parameter vector of the overhead contact system. J x =( d x ,l x High-level guide value d x This reflects the perpendicular distance between the contact line and the rail surface, while the pull-out value... l x This reflects the lateral offset of the contact wire relative to the centerline of the pantograph. Furthermore, considering the long-term impact of environmental factors on the physical condition of the contact network, the system synchronously collects real-time ambient temperature information through an externally integrated high-precision platinum resistance temperature sensor, outputting the ambient temperature value T. This sensor is typically installed in a well-ventilated, shaded area on the roof of the vehicle and is equipped with a radiation shield to reduce measurement errors caused by direct sunlight.

[0038] Data cleaning and spatiotemporal synchronization were performed on the collected heterogeneous data. Due to differences in sampling frequency, clock reference, and physical installation location among the sensors, a signal smoothing algorithm based on median filtering was first used to remove pulse-type clutter caused by electromagnetic interference from the pantograph sparks. For the pantograph attitude data, a statistical aggregation strategy based on long-period operating trajectories was adopted. Specifically, for data from the same geographical location... x In different running trips N Based on the observed data, a probability density function for the pantograph's attitude was constructed. Under this model, the pantograph's position... x Forward and backward tilt angles i 1,x and left and right tilt angle i 2,xAll variables are considered to have normally distributed characteristics. The system calculates the corresponding expected value and standard deviation using the maximum likelihood estimation method. The mean of the forward and backward tilt angles... The standard deviation is obtained by taking the arithmetic mean of N historical valid sample values. This is used to quantify the dispersion of the pantograph's attitude at that location. Through this statistical method, the system successfully constructed a pantograph attitude probability density model, which can effectively filter out accidental interference caused by random track irregularities or instantaneous wind loads during a single operation, thereby extracting a robust benchmark that reflects the mechanical characteristics of the vehicle's pantograph itself.

[0039] Furthermore, for the pull-out value data within the interval, using the physical anchor section interval as the basic statistical unit, the spatial distribution uniformity of the contact wire pull-out value across the entire interval is analyzed in depth. The pull-out value distribution function L(x) is strictly defined within the safety constraints of the contact wire design, which can range from -350mm to +350mm. To quantify the wear distribution on the carbon sliding plate surface, this invention uses integral calculations to statistically determine the cumulative probability distribution L+(x) for positive pull-out values ​​and the cumulative probability distribution L for negative pull-out values ​​within the interval. + (x), the formula is expressed as as well as Here, l ( x The function represents the measured pull-out values ​​of all anchor points within the interval at different coordinate points. By comparing the probability coverage of positive and negative pull-out values, the system can accurately evaluate the symmetry of the force distribution on the carbon slide plate surface within the interval, thereby predicting whether there is a risk of unilateral wear due to the overall displacement of the contact wire.

[0040] During data analysis, a three-dimensional integrated anomaly tracing system was implemented based on the preprocessed feature parameters. First, pantograph attitude anomaly analysis was performed, with the system incorporating a dynamically weighted safety factor n. Under normal operating conditions... n The preferred setting is 2. The analysis module determines the pantograph's attitude by checking whether the real-time observed pantograph attitude values ​​fall within a confidence interval based on a long-term statistical distribution. If the real-time observed value exceeds the confidence interval, it indicates that the pantograph's dynamic response at that point deviates from its historical baseline. This deviation often points to mechanical loosening of the pantograph bracket, damping failure of the hydraulic / pneumatic balancing mechanism, or geometric deviation of the pantograph itself. In particular, when the vehicle passes through a curved section, considering that the outer rail superelevation will cause normal physical tilting of the vehicle body, the system will automatically adjust... i The judgment threshold correction coefficient of 2 is increased by 20% to compensate for this attitude deviation caused by the line design.

[0041] Secondly, anomaly analysis of pull-out value distribution is performed. Within a straight section, the ideal design of the contact wire requires the pull-out value to be evenly distributed alternately on both sides of the center of the sliding plate. This invention calculates the forward pull-out value distribution weight L... + Weight L of the negative pull-out value distribution − The ratio is set, and an empirical threshold range [0.8, 1.2] is defined. If the ratio deviates from this range, it means that there is a systematic deviation in the setting of the contact wire positioning points in this range. The pantograph slide will be in an offset contact state for a long time during operation, resulting in the lateral wear rate of the carbon slide far exceeding the design expectation.

[0042] Finally, there is the analysis of abnormal frost heave and environmental correlation of the contact line. This is an in-depth investigation process targeting environmentally sensitive uneven wear. This invention defines the first... m The average ambient temperature at the beginning of the month is used as the base temperature. T m0 The temperature collected in real time T mi In comparison, the fluctuation ΔT = | T mi −T m0 When the temperature fluctuation exceeds 5 degrees Celsius, the system will automatically trigger the calculation of geometric parameter offset and extract the change in elevation Δ at that location. D x Change in pull-out value Δ L x To eliminate measurement errors at a single time point, the Pearson correlation coefficient was introduced to test the correlation of multi-day data. The correlation coefficient between guide height offset and temperature fluctuation was used as the basis for this analysis. For example, its calculation is done through the formula To achieve, count the number of days n The optimal time is 3 to 7 days. When the correlation coefficient is greater than 0.5, it indicates that there is a significant positive correlation between the change in the geometric parameters of the contact wire and the ambient temperature. This indicates that the contact wire has experienced frost heave or thermal contraction jamming. This dynamic drift directly leads to abnormal concentration of local contact pressure, which is the root cause of seasonal uneven wear.

[0043] Finally, based on the above multi-dimensional analysis results, the system automatically generates operation and maintenance decision suggestions through a logical reasoning engine. If the attitude anomaly determination is valid, the system will automatically associate the vehicle number and output the instruction "adjust pantograph attitude"; if the pull-out value distribution anomaly is valid, the system will output the instruction "adjust the pull-out value distribution of the corresponding kilometer marker interval"; if the environmental correlation determination is valid, the system will output the suggestion "check the busbar jam and adjust the contact wire slope".

[0044] A method for analyzing abnormal wear of the pantograph carbon sliding plate includes the following specific steps: S1: Acquiring Heterogeneous Data: During the vehicle's operation, a hardware acquisition cluster deployed on the vehicle's roof collects real-time vehicle positioning information, pantograph attitude information, overhead contact line geometric parameters, and real-time ambient temperature information; wherein, the pantograph attitude information includes the forward and backward tilt angles output by the pantograph tilt angle measurement component. i 1 and left and right tilt angles i 2; The contact wire geometric parameter information includes the contact wire guide height value at the current vehicle position obtained through a non-contact measurement component. d x With pull value l x .

[0045] S2: Data preprocessing: Spatiotemporal synchronization, signal cleaning, and statistical feature extraction are performed on the collected heterogeneous data; for pantograph attitude data, the pantograph attitude probability density function is constructed by aggregating observation data from the same geographical location under different running trips; for pull-out value data, the pull-out value distribution function reflecting the symmetry of the force point distribution on the carbon slide plate surface is constructed using physical intervals as statistical units.

[0046] S3: Data Analysis: Based on the feature parameters obtained from preprocessing, anomaly tracing is carried out from three dimensions: First, perform pantograph attitude anomaly analysis: by checking whether the pantograph attitude values ​​observed in real time fall within the confidence interval based on long-term statistical distribution, determine whether there is an attitude anomaly of the pantograph caused by mechanical structural deviation.

[0047] Second, conduct anomaly analysis of pull-out value distribution: calculate the ratio of the weight of positive pull-out value distribution to the weight of negative pull-out value distribution within the target interval, and determine whether there is a systematic statistical bias in the catenary layout by the degree of deviation of the ratio from the preset threshold interval.

[0048] Third, conduct an analysis of abnormal frost heave of the contact wire and its correlation with the environment: calculate the Pearson correlation coefficient between the ambient temperature fluctuation ΔT and the offset of the contact wire geometric parameters, and determine whether there is dynamic geometric drift of the contact wire induced by drastic changes in ambient temperature based on the correlation test results.

[0049] S4: Anomaly Assessment: Based on the anomaly assessment results obtained from data analysis, match the corresponding physical maintenance items and automatically generate a decision conclusion that includes the specific fault source and maintenance handling suggestions.

[0050] In this embodiment, the vehicle positioning information mentioned in step S1 is obtained through a combination of a vehicle-mounted high-precision global navigation satellite system and an inertial navigation system. The output parameters include the route number, travel direction, section identifier, kilometer marker value, and real-time vehicle speed. The pantograph tilt angle measurement component uses a microelectromechanical system tilt sensor with a sampling frequency set to no less than 50Hz to fully capture the transient pitch and roll characteristics of the pantograph when the vehicle passes through a position where the stiffness of the contact wire changes abruptly. The real-time ambient temperature information is collected by a high-precision platinum resistance temperature sensor equipped with a radiation shield, and the real-time ambient temperature value T is output.

[0051] Step S2 involves signal cleaning and spatiotemporal synchronization of the acquired heterogeneous data, including the following processes: A signal smoothing algorithm based on median filtering is used to eliminate pulse-type noise generated by electromagnetic interference from pantograph sparks. Using spatial resampling technology, data collected at different operating speeds are mapped onto a standard kilometer grid based on vehicle positioning information. The resampling step size is set to 0.1 meters. Cubic spline interpolation is used to fill in missing grid data, and weighted average method is used to fuse duplicate data to ensure strong consistency alignment of data from multiple trips in the physical coordinate dimension.

[0052] The specific process of constructing the pantograph attitude probability density function is as follows: S21: Position the pantograph. x Forward and backward tilt angles i 1,x and left and right tilt angle i 2,x Treating them as random variables, the maximum likelihood estimation method is used to... N Statistical analysis was performed on sample values ​​from each run. S22: Calculate the position of the pantograph carbon sliding plate x The mean of the forward and backward tilt angles at the location and standard deviation : ; ; S23: Calculate the position of the pantograph carbon slider x The mean of the left and right tilt angles at the location and standard deviation : ; ; S24: Establish a pantograph attitude probability density model based on the mean and standard deviation, including: Forward and backward tilt angle probability density model: ; Left and right tilt angle probability density model: ; S25: Filtering random orbital impact interference using the pantograph attitude probability density model: Track impact, wind disturbance, and transient vibration are all short-term random noises. N The average was applied in the trip statistics; Probability density model with mean m Centered, standard deviation s The fluctuation bandwidth forms the normal attitude distribution range; Transient spikes and pulse offsets during a single run are judged to be low-probability events and are directly filtered out. Extracting the mechanical characteristics benchmark of the pantograph itself: by , As the inherent mechanical attitude reference of the pantograph at this position; in terms of standard deviation , As the boundary of normal fluctuations; The final result is a stable benchmark that is unaffected by random disturbances and reflects only the mechanical structural characteristics of the pantograph itself, which is used for subsequent anomaly detection.

[0053] In a preferred embodiment of the present invention, a strong consistency alignment technique based on kilometer marker grids is employed during spatial resampling in the preprocessing stage. Because vehicle speeds vary significantly across different trips (e.g., from 30 km / h to 100 km / h), the original time-series data cannot be directly statistically aggregated. This invention projects all sampling points onto a standard 0.1-meter grid using high-precision kilometer marker mapping. If multiple sampling points exist within a grid, a weighted average method is used for fusion; if data is missing from a grid, cubic spline interpolation is used to complete it. This process ensures the consistency of physical coordinates in subsequent probability density function calculations.

[0054] Example 2 Based on Example 1, the specific determination process for pantograph attitude anomaly analysis in step S3 is as follows: Set a safety factor n To verify the current real-time observation of the pantograph's position. x Forward and backward tilt angles i 1,x and left and right tilt angle i 2,x Does it meet the corresponding confidence interval constraints? ; ; If the real-time observation value exceeds the above confidence interval, it is determined that the pantograph has an abnormal attitude at the corresponding position and is associated with the vehicle pantograph bracket mechanical loosening, balancing mechanism failure or geometric deviation fault. Wherein, the safety factor n It features dynamic weight configuration: when a vehicle passes through a curved section, the system automatically adjusts the left and right tilt angles based on the superelevation parameters of the outer rail. i The judgment threshold correction coefficient of 2 is increased by 20% to compensate for normal attitude deviation caused by the physical tilt of the vehicle body.

[0055] The safety factor n It also performs dynamic attenuation correction based on the cumulative operating mileage of the pantograph slider: When the pantograph slider's service life is nearing its end, and the wear on the pantograph slider reaches more than 80% of the warning value, the system's center of gravity will shift slightly, and the system will automatically adjust the safety factor. n The value was increased to 1.8 to improve the detection sensitivity of pantograph attitude instability anomalies.

[0056] Simultaneously, during the preprocessing stage, the aerodynamic lift compensation coefficient table based on the real-time operating vehicle speed is invoked to calculate the average forward and backward tilt angles. Dynamic corrections are performed to eliminate the impact of differences in aerodynamic forces at different operating speeds on attitude determination results.

[0057] The process of analyzing the anomaly distribution of the pulled-out values ​​in step S3 includes: Define the pull-out value distribution function within the specified physical range. L ( x ): ; The cumulative probability distribution of positive values ​​within this interval is calculated using integration: ; The cumulative probability distribution of negative values ​​within this interval is calculated using integration: ; in, l ( x () represents the actual measured value function; L max 、L min Set value constraint limits for the overhead contact line design; Calculate the forward pull-out value distribution weight L + Weight L of the negative pull-out value distribution − The ratio; Determine whether the ratio is within a preset threshold range. r 1, rIf the ratio deviates from the range within 2], it is determined that there is a statistical bias in the layout of the contact network in the range, which induces excessive wear on one side of the carbon sliding plate.

[0058] The preferred threshold range is 0.8 to 1.2.

[0059] The specific process for analyzing abnormal frost heave and environmental correlation of the contact wire in step S3 is as follows: The average ambient temperature at the reference time point is defined as the reference temperature. T m0 Calculate the absolute value of the difference between the real-time average ambient temperature and the reference temperature to obtain the ambient temperature fluctuation ΔT = | T mi −T m0 |; When ΔT exceeds a preset significance threshold, the geometric parameter offset calculation is triggered to extract the location. x Change in conduction height Δ at point D x Change in pull-out value Δ L x ; The correlation coefficient between guide height offset and temperature fluctuation is calculated using the Pearson correlation coefficient formula. : ; Calculate the correlation coefficient between pull-out value offset and temperature fluctuation. : ; in, n 1 represents the number of consecutive statistical days, ranging from 3 to 7 days.

[0060] The number of days in the statistics n The value of 1 is controlled by the temperature gradient monitoring logic: When the system detects that the real-time temperature gradient exceeds the preset rate of change threshold, it automatically records the number of days. n 1. Shorten to the lower limit value to improve the speed of capturing the dynamic response trend of the overhead contact line; When determining the correlation coefficient A correlation coefficient greater than 0.5 and between the pull-out value offset and temperature fluctuation. When the value is greater than 0.5, the system determines that the contact wire has experienced freezing expansion or thermal contraction jamming caused by drastic temperature fluctuations, resulting in abnormal concentration of local contact pressure.

[0061] The anomaly assessment process in step S4 is as follows: If the determination result is that the pantograph attitude is abnormal, the command "Adjust the pantograph attitude of the corresponding vehicle number" will be output. If the determination result is that the distribution of pull-out values ​​is abnormal, the command "Adjust the distribution of pull-out values ​​of positioning points in the corresponding kilometer marker interval" will be output. If the determination result is an environmental correlation anomaly, the command "Adjust the slope of the contact line in the corresponding section and check the blockage status of the busbar" will be output. And based on the change in guide height Δ D x The system will issue graded warnings based on whether the preset safety threshold is exceeded, and automatically match the maintenance and emergency repair path based on the geographic information system in the judgment conclusion.

[0062] In summary, the pantograph carbon contactor abnormal wear analysis method provided by this invention solves the bottleneck problems of data silos, ambiguous cause localization, and low operation and maintenance efficiency in the traditional manual inspection mode by constructing an analysis architecture based on probability statistics and multi-source fusion. Its core advantages are: high-precision identification of anomalies on the vehicle side is achieved through a pantograph attitude probability density model; systemic design defects on the contact wire side are quantified by the cumulative distribution probability of pull-out values; and the source tracing problem of seasonal and dynamic wear is overcome through a temperature-geometric parameter correlation model. The engineering application of this invention can significantly extend the service life of the carbon contactor, reduce the risk of line breakage accidents caused by abnormal wear of the contact wire, and provide solid technical support for intelligent operation and maintenance of urban rail transit.

Claims

1. A method for analyzing abnormal wear of the carbon sliding plate of a pantograph, characterized in that, Includes the following steps: S1: Acquiring Heterogeneous Data: During the vehicle's operation, a hardware acquisition cluster deployed on the vehicle's roof collects real-time vehicle positioning information, pantograph attitude information, overhead contact line geometric parameters, and real-time ambient temperature information; wherein, the pantograph attitude information includes the forward and backward tilt angles output by the pantograph tilt angle measurement component. θ 1 and left and right tilt angles θ 2; The contact wire geometric parameter information includes the contact wire guide height value at the current vehicle position obtained through a non-contact measurement component. d x With pull value l x ; S2: Data preprocessing: Spatiotemporal synchronization, signal cleaning, and statistical feature extraction are performed on the collected heterogeneous data; for pantograph attitude data, the pantograph attitude probability density function is constructed by aggregating observation data from the same geographical location under different running trips; for pull-out value data, a pull-out value distribution function reflecting the symmetry of the force point distribution on the carbon slide plate surface is constructed using physical intervals as statistical units. S3: Data Analysis: Based on the feature parameters obtained from preprocessing, anomaly tracing is carried out from three dimensions: First, perform pantograph attitude anomaly analysis: by checking whether the pantograph attitude values ​​observed in real time fall within the confidence interval based on long-term statistical distribution, determine whether there is an attitude anomaly of the pantograph caused by mechanical structure deviation. Second, conduct anomaly analysis of pull-out value distribution: calculate the ratio of the weight of positive pull-out value distribution to the weight of negative pull-out value distribution within the target interval, and determine whether there is a systematic statistical bias in the catenary layout by the degree of deviation of the ratio from the preset threshold interval; Third, conduct an analysis of abnormal frost heave of the contact wire and its correlation with the environment: calculate the Pearson correlation coefficient between the ambient temperature fluctuation ΔT and the offset of the contact wire geometric parameters, and determine whether there is dynamic geometric drift of the contact wire induced by drastic changes in ambient temperature based on the correlation test results. S4: Anomaly Assessment: Based on the anomaly assessment results obtained from data analysis, match the corresponding physical maintenance items and automatically generate a decision conclusion that includes the specific fault source and maintenance handling suggestions.

2. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 1, characterized in that, The vehicle positioning information mentioned in step S1 is obtained through a combination of a vehicle-mounted high-precision global navigation satellite system and an inertial navigation system. The output parameters include the route number, direction of travel, section identifier, kilometer marker value, and real-time vehicle speed. The pantograph tilt measurement component uses a microelectromechanical system tilt sensor with a sampling frequency set to no less than 50Hz to fully capture the transient pitch and roll characteristics of the pantograph when the vehicle passes through a position where the stiffness of the contact wire changes abruptly. The real-time ambient temperature information is collected by a high-precision platinum resistance temperature sensor equipped with a radiation shield, and the real-time ambient temperature value T is output.

3. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 1, characterized in that, Step S2 involves signal cleaning and spatiotemporal synchronization of the acquired heterogeneous data, including the following processes: A signal smoothing algorithm based on median filtering is used to eliminate pulse-type noise generated by electromagnetic interference from pantograph sparks. Using spatial resampling technology, data collected at different operating speeds are mapped onto a standard kilometer grid based on vehicle positioning information. The resampling step size is set to 0.1 meters. Cubic spline interpolation is used to fill in missing grid data, and weighted average method is used to fuse duplicate data to ensure strong consistency alignment of data from multiple trips in the physical coordinate dimension.

4. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 2, characterized in that, The specific process of constructing the pantograph attitude probability density function is as follows: S21: Position the pantograph. x Forward and backward tilt angles θ 1,x and left and right tilt angle θ 2,x Treating them as random variables, the maximum likelihood estimation method is used to... N Statistical analysis was performed on sample values ​​from each run. S22: Calculate the position of the pantograph carbon slider x The mean of the forward and backward tilt angles at the location and standard deviation : ； ； S23: Calculate the position of the pantograph carbon slider x The mean of the left and right tilt angles at the location and standard deviation : ； ； S24: Establish a pantograph attitude probability density model based on the mean and standard deviation, including: Forward and backward tilt angle probability density model: ； Left and right tilt angle probability density model: ； in, i Indicates the number of train trips; θ 1,x ( i ) represents the train at the i During the trip, the pantograph is in position x The angle of inclination at the front and rear; θ 2,x ( i ) represents the train at the i During the trip, the pantograph is in position x The left and right tilt angles at that location; Indicates the pantograph is in position x The probability distribution of the forward and backward tilt angles at the location; Indicates the pantograph is in position x The probability distribution of the left and right tilt angles at the location; S25: Filtering random orbital impact interference using the pantograph attitude probability density model: Track impact, wind disturbance, and transient vibration are all short-term random noises. N The average was applied in the trip statistics; Probability density model with mean μ Centered, standard deviation σ The fluctuation bandwidth forms the normal attitude distribution range; Transient spikes and pulse offsets during a single run are judged as low-probability events and are directly filtered out. Extracting the mechanical characteristics benchmark of the pantograph itself: by , As the inherent mechanical attitude reference of the pantograph at this position; in terms of standard deviation , As the boundary of normal fluctuations; The final result is a stable benchmark that is unaffected by random disturbances and reflects only the mechanical structural characteristics of the pantograph itself, which is used for subsequent anomaly detection.

5. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 1, characterized in that, The specific determination process for pantograph attitude anomaly analysis in step S3 is as follows: Set a safety factor n To verify the current real-time observation of the pantograph's position. x Forward and backward tilt angles θ 1,x and left and right tilt angle θ 2,x Does it meet the corresponding confidence interval constraints? ； ； If the real-time observation value exceeds the above confidence interval, it is determined that the pantograph has an abnormal attitude at the corresponding position and is associated with the vehicle pantograph bracket mechanical loosening, balancing mechanism failure or geometric deviation fault. Wherein, the safety factor n It features dynamic weight configuration: when a vehicle passes through a curved section, the system automatically adjusts the left and right tilt angles based on the superelevation parameters of the outer rail. θ The judgment threshold correction coefficient of 2 is increased by 20% to compensate for normal attitude deviation caused by the physical tilt of the vehicle body.

6. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 5, characterized in that, The safety factor n It also performs dynamic attenuation correction based on the cumulative operating mileage of the pantograph slider: When the wear of the pantograph slider reaches more than 80% of the warning value, the system automatically reduces the safety factor. n The value is used to improve the detection sensitivity of pantograph attitude instability anomalies; Simultaneously, during the preprocessing stage, the aerodynamic lift compensation coefficient table based on the real-time operating vehicle speed is invoked to calculate the average forward and backward tilt angles. Dynamic corrections are performed to eliminate the impact of differences in aerodynamic forces at different operating speeds on attitude determination results.

7. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 1, characterized in that, The process of analyzing the anomaly distribution of the pulled-out values ​​in step S3 includes: Define the pull-out value distribution function within the specified physical range. L ( x ): ； in, L ( x () represents the distribution function of the output value; l ( x ) represents the probability density function of the pulled value; The cumulative probability distribution of positive values ​​within this interval is calculated using integration: ； The cumulative probability distribution of negative values ​​within this interval is calculated using integration: ； in, l ( x () represents the actual measured value function; L max 、L min Set value constraint limits for the overhead contact line design; Calculate the forward pull-out value distribution weight L + Weight L of the negative pull-out value distribution − The ratio; Determine whether the ratio is within a preset threshold range. r 1, r If the ratio deviates from the range within 2], it is determined that there is a statistical bias in the layout of the contact network in the range, which induces excessive wear on one side of the carbon sliding plate.

8. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 1, characterized in that, The specific process for analyzing abnormal frost heave and environmental correlation of the contact wire in step S3 is as follows: The average ambient temperature at the reference time point is defined as the reference temperature. T m0 Calculate the average ambient temperature collected in real time. T mi Compared with reference temperature T m0 The absolute value of the difference is used to obtain the ambient temperature fluctuation ΔT = | T mi −T m0 |; When ΔT exceeds a preset significance threshold, the geometric parameter offset calculation is triggered to extract the location. x Change in conduction height Δ at point D x Change in pull-out value Δ L x ; The correlation coefficient between guide height offset and temperature fluctuation is calculated using the Pearson correlation coefficient formula. : ； Calculate the correlation coefficient between pull-out value offset and temperature fluctuation. : ； in, n 1 represents the number of consecutive statistical days, ranging from 3 to 7 days.

9. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 8, characterized in that, The number of days in the statistics n The value of 1 is controlled by the temperature gradient monitoring logic: When the system detects that the real-time temperature gradient exceeds the preset rate of change threshold, it automatically records the number of days. n 1. Shorten to the lower limit value to improve the speed of capturing the dynamic response trend of the overhead contact line; When determining the correlation coefficient A correlation coefficient greater than 0.5 and between the pull-out value offset and temperature fluctuation. When the value is greater than 0.5, the system determines that the contact wire has experienced freezing expansion or thermal contraction jamming caused by drastic temperature fluctuations, resulting in abnormal concentration of local contact pressure.

10. The method for analyzing abnormal wear of the pantograph carbon sliding plate according to claim 1, characterized in that, The anomaly assessment process in step S4 is as follows: If the determination result is that the pantograph attitude is abnormal, the command "Adjust the pantograph attitude of the corresponding vehicle number" will be output. If the determination result is that the distribution of pull-out values ​​is abnormal, the command "Adjust the distribution of pull-out values ​​of positioning points in the corresponding kilometer marker interval" will be output. If the judgment result is an environmental correlation anomaly, the command "Adjust the contact line slope of the corresponding section and check the blockage status of the busbar" will be output. And based on the change in guide height Δ D x The system will issue graded warnings based on whether the preset safety threshold is exceeded, and automatically match the maintenance and emergency repair path based on the geographic information system in the judgment conclusion.

Images