Urban rail vehicle traction safety control method and system, electronic equipment and storage medium

Abstract

The invention provides an urban rail vehicle traction safety control method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining vehicle state data and environment data, and inputting the vehicle state data and environment data into a pre-constructed random forest model to obtain influence factors about vehicle driving safety; vehicle operation and maintenance data and passenger flow data are acquired, and a comprehensive loss index of the vehicle is calculated according to the vehicle operation and maintenance data and the passenger flow data; and calculating a running state comprehensive evaluation score of the vehicle according to the influence factor and the comprehensive loss index, performing risk grade division according to the comprehensive evaluation score, and executing a preset safety control strategy based on the risk grade to send a corresponding safety control instruction to the vehicle so as to control the vehicle to execute corresponding control measures. According to the application, the current vehicle fault can be monitored and diagnosed in real time, and the fault possibly occurring in the future can be predicted, so that the safe operation of the vehicle is further guaranteed.

Description

Technical Field

[0001] The present application belongs to the field of rail transit technology, and in particular, relates to a method, system, electronic device and storage medium for traction safety control of urban rail vehicles. Background Art

[0002] Urban rail vehicles, or urban rail transit vehicles, refer to rail transit vehicles in urban rail transit systems used for public transportation between urban areas and within urban areas. With the acceleration of urbanization, urban rail transit has been widely developed and applied as an important means to alleviate urban traffic pressure. Urban rail vehicles are the core components of the urban rail transit system, and their operating safety and reliability are directly related to the safety of passengers' lives and property and the normal operation of the city.

[0003] Although existing fault detection algorithms and sensor unit technologies can identify vehicle faults to a certain extent, false alarms and missed alarms still exist. Especially in complex and changeable operating environments, the accuracy of fault detection is more easily affected, resulting in poor fault detection accuracy and the inability to accurately predict faults. Summary of the invention

[0004] In view of this, the present application aims to propose a method, system, electronic device and storage medium for urban rail vehicle traction safety control to solve the problems of false alarm and missed alarm of vehicle faults, single adaptability, poor fault detection accuracy and unpredictable faults.

[0005] To achieve the above purpose, the technical solution of this application is implemented as follows:

[0006] In a first aspect, the present application provides a method for controlling traction safety of a city rail vehicle, comprising:

[0007] Acquire vehicle status data and environmental data, and input the vehicle status data and the environmental data into a pre-constructed random forest model to obtain influencing factors on vehicle driving safety, wherein the random forest model is trained and constructed by the vehicle status data and the environmental data;

[0008] Acquiring vehicle operation and maintenance data and passenger flow data, and calculating a comprehensive loss index of the vehicle based on the vehicle operation and maintenance data and the passenger flow data;

[0009] A comprehensive evaluation score of the vehicle's operating status is calculated based on the influencing factors and the comprehensive loss index, and risk levels are divided based on the comprehensive evaluation score. A preset safety control strategy is executed based on the risk level to send corresponding safety control instructions to the vehicle, thereby controlling the vehicle to execute corresponding control measures.

[0010] In the second aspect, based on the same inventive concept, the present application also provides a traction safety control system for urban rail vehicles, including a data acquisition module, a data processing module, a safety control module and a monitoring display module;

[0011] The data acquisition module is used to collect vehicle status data, environmental data, vehicle operation and maintenance data, and passenger flow data during operation;

[0012] The data processing module is used to receive the raw data from the data acquisition module, perform data processing on the raw data, and comprehensively evaluate the current running state of the vehicle based on the processed data results;

[0013] The safety control module is used to classify safety risks into different levels according to the evaluation results, and generate corresponding safety control instructions to control the vehicle to execute corresponding safety measures;

[0014] The monitoring and display module is used to display the current vehicle operation information, vehicle status information and the execution status of safety control instructions, and supports remote access and monitoring functions.

[0015] In a third aspect, based on the same inventive concept, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first aspect is implemented.

[0016] In a fourth aspect, based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0017] Compared with the prior art, the urban rail vehicle traction safety control method, system, electronic device and storage medium described in this application have the following beneficial effects:

[0018] The urban rail vehicle traction safety control method, system, electronic device and storage medium described in the present application can monitor and diagnose current vehicle faults in real time, and can also predict possible faults in the future, further ensuring the safe operation of the vehicle. At the same time, it can display the vehicle operation status, fault information and the execution of safety control instructions in real time, so that the operator can quickly understand the overall condition of the vehicle. Through real-time monitoring, data analysis and prediction, intelligent control and remote monitoring, the safety of vehicle operation and the efficiency of troubleshooting are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0020] Figure 1 This is a flow chart of a method for controlling traction safety of urban rail vehicles according to an embodiment of the present application;

[0021] Figure 2 This is a schematic diagram of the structure of a traction safety control system for urban rail vehicles according to an embodiment of the present application;

[0022] Figure 3 This is a schematic diagram of the hardware structure of the electronic device described in the embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0024] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0026] See also Figure 1 As shown, this embodiment provides a method for controlling traction safety of urban rail vehicles, which specifically includes the following steps:

[0027] Step S101, obtaining vehicle status data and environmental data, and inputting the vehicle status data and environmental data into a pre-constructed random forest model to obtain factors affecting vehicle driving safety, wherein the random forest model is constructed by training the vehicle status data and environmental data.

[0028] Specifically, in this embodiment, multiple sensor arrays installed on the vehicle are used to monitor the vehicle's own operating status and operating environment data. As the "sensing organs" of the system, they are widely distributed in key parts of the vehicle. These high-precision sensor units can collect real-time information on the vehicle's vibration, temperature, pressure, speed, acceleration, current, voltage and other physical quantities, providing a comprehensive and accurate data basis for the system's safety assessment.

[0029] Among them, vehicle running status data: vehicle speed is obtained in real time through the speed sensor unit installed on the vehicle to accurately measure the current driving speed information and position information of the vehicle, and the specific position of the vehicle on the track is determined in real time using positioning technology;

[0030] Traction brake system data: The motor’s current, voltage, power and temperature reflect the motor’s operating status and performance. The stability of the inverter’s output voltage, current and frequency directly affects the motor’s operating effect. Braking pressure and temperature are used to evaluate the performance and health of the braking system and prevent safety issues caused by brake failure or overheating.

[0031] Vehicle bogie data: wheelset temperature and vibration. Monitoring of these parameters helps to promptly detect wheelset failures or abnormal wear problems. Bearing vibration and temperature. The vibration and temperature data are important for assessing the health of bearings and predicting potential failures. Suspension stiffness and damping help optimize the performance of the suspension system and improve the vehicle's ride quality.

[0032] Environmental data: Temperature data, humidity data and wind data are all important factors that affect the safe operation of vehicles. Too high temperature will cause overheating of vehicle components during operation, while too low temperature will affect battery performance or cause lubricating oil to solidify. Too high humidity will increase the risk of failure of electrical components, and excessive wind will generate greater lateral force on the body of the urban rail vehicle, affecting the vehicle's driving.

[0033] The above data are preprocessed respectively. This embodiment uses the vehicle running status data as an example to illustrate:

[0034] For vehicle operation status data processing, the collected urban rail vehicle operation status data includes normal operation data and abnormal operation data. The data is not limited to various parameters under normal operation, including speed, acceleration, temperature, pressure, etc., but also covers key information recorded under abnormal operation conditions, forming a database as a basis for reference and comparison;

[0035] In order to reduce the interference of noise on data analysis, smoothing technology, filtering method and data transformation method are used to reduce the interference of noise on data analysis. Smoothing technology is used to smooth the data curve to eliminate the noise caused by random fluctuations. The filtering method selectively retains or removes signals with specific frequency components according to the spectral characteristics of the signal to reduce the interference of noise on the data. The data transformation method is used to improve the distribution characteristics of the data to make it more suitable for subsequent analysis algorithms. It should be noted that smoothing technology, filtering method and data transformation method are all existing technologies in this field and will not be elaborated here.

[0036] At the same time, verify whether there are missing values ​​in the received real-time data. Missing values ​​are caused by sensor failure, communication interruption, etc. If there are missing values, the entire data group with missing values ​​will be deleted, and feedback information will be sent to the sensor array module to obtain new real-time data to replace it. If there are no missing values, outlier detection will be performed to ensure the integrity and continuity of the data.

[0037] In order to accurately identify outliers, the real-time data is compared with the information in the database to determine whether the data is an outlier. Outliers refer to values ​​that obviously deviate from the normal data range. They are caused by measurement errors, equipment failures or extreme operating conditions. If the data is not included in the database, 5 new groups of data are obtained for the data group with the anomaly and repeated comparisons are performed to verify the accuracy of the anomaly, reduce errors, and improve the accuracy of outlier detection. If the new data also has anomalies, it is determined to be an outlier and similar outliers are marked. If the new data does not have anomalies, the original data group with anomalies will be deleted as a whole; if the data is included in the database, no processing is done.

[0038] The method for calculating the influencing factors based on the data processing method in the above steps is:

[0039] The vehicle speed, vehicle position, vehicle motor current, voltage, power, temperature, inverter output voltage, current, frequency, brake pressure, temperature, wheelset temperature, vibration, bearing vibration and temperature, suspension stiffness, damping, temperature, humidity, wind data information in the database are used as feature data;

[0040] Based on dividing the data after data processing into training set and test set, when dividing the data set, it should be ensured that the training set and the test set are consistent in data distribution to avoid overfitting or underfitting problems, and set the parameters of random forest, including the number of trees, maximum depth, and minimum number of samples.

[0041] Decision trees are constructed based on feature data. During the construction process, a portion of feature data and sample data are randomly selected for training. This process is parallel, that is, multiple decision trees are constructed at the same time. Each decision tree will independently select features and samples during construction, and will be trained based on different random samples and feature subsets. In this way, each tree will learn different aspects of the data, thereby improving the generalization ability of the entire forest, and ultimately the decision trees are trained based on different random samples and feature subsets.

[0042] All decision trees are integrated to construct a random forest. The prediction results of each tree are combined into the final result through classification problems. A voting mechanism is usually used to combine the prediction results of each tree. Specifically, the predictions of each tree on the sample category are counted, and finally the category with the most votes is used as the prediction result of the random forest.

[0043] Use the training set data to train the random forest, use the test set data to evaluate the model performance, calculate the accuracy, and use the trained random forest model to detect anomalies on new data samples. The model will analyze the feature data of the new samples and compare them with the normal pattern, identify anomalies that deviate significantly from the normal pattern as factors that affect the safety of urban rail vehicles, and participate in subsequent comprehensive evaluations.

[0044] The random forest model output based on the above construction obtains influencing factors, including operating status factors, traction braking system factors, vehicle bogie factors and environmental factors. The operating status factors directly reflect the current operating status of the vehicle, including but not limited to vehicle speed, acceleration, deceleration, position stability, etc. These factors are obtained through the real-time monitoring system to evaluate whether the vehicle is within the normal operating range; the traction braking system factors involve abnormal conditions of the vehicle motor, inverter and their related electrical parameters. The random forest model can identify abnormal patterns in these parameters, thereby determining whether the traction braking system has potential faults or performance degradation; vehicle bogie factors include the temperature and vibration of the wheelset, and the temperature and vibration of the bearings. These factors reflect the health of the bogie, and abnormal values ​​indicate problems such as wheelset wear, bearing failure, and suspension system failure; and environmental factors involve extreme weather conditions that lead to vehicle performance degradation or increased failures. Analysis of environmental factors helps to understand the performance of the vehicle in different environments.

[0045] Step S102: Acquire vehicle operation and maintenance data and passenger flow data, and calculate the comprehensive loss index of the vehicle based on the vehicle operation and maintenance data and the passenger flow data.

[0046] Specifically, in this embodiment, the total number of years since the urban rail vehicle was put into operation is collected, passenger flow information data is collected according to the sensor array module, and vehicle mechanical wear information, electrical system aging information, interior appearance loss information, and maintenance and servicing information are collected;

[0047] Based on the collected information data, a loss assessment model is established, and a comprehensive loss index is calculated by combining the operating years, passenger flow, loss coefficient and maintenance records;

[0048] Among them, the calculation formula of comprehensive loss index is:

[0049]

[0050] Where CLI represents the comprehensive loss index, w i represents the weight of component i, d i represents the loss coefficient and maintenance record of component i, u i represents the usage frequency of component i based on passenger flow, y i Indicates the impact factor of operating years.

[0051] This embodiment uses the comprehensive loss index as one of the influencing factors to participate in the subsequent comprehensive evaluation.

[0052] Step S103, calculate the comprehensive evaluation score of the vehicle's operating status based on the influencing factors and the comprehensive loss index, divide the risk level according to the comprehensive evaluation score, and execute the preset safety control strategy based on the risk level to send corresponding safety control instructions to the vehicle, thereby controlling the vehicle to execute corresponding control measures.

[0053] Specifically, in this embodiment, according to the results of random forest calculation and the comprehensive loss index, the influencing factors are divided into operating state factors, traction braking system factors, vehicle bogie factors, environmental factors and comprehensive loss factors;

[0054] Calculate the comprehensive evaluation score of the vehicle's operating status based on operating status factors, traction brake system factors, vehicle bogie factors, environmental factors and comprehensive loss factors;

[0055] The calculation formula for the comprehensive evaluation score is:

[0056]

[0057] Where S represents the comprehensive evaluation score, S1-S5 represent the operating status factor, traction braking system factor, vehicle bogie factor, environmental factor and comprehensive loss factor, respectively, and R1-R5 represent the weights of the operating status factor, traction braking system factor, vehicle bogie factor, environmental factor and comprehensive loss factor, respectively.

[0058] The risk levels are divided according to the comprehensive assessment points. The risk levels after division are as follows:

[0059] No risk, the comprehensive assessment score is greater than or equal to 90 points, and the vehicle continues to be maintained in good condition by carrying out regular maintenance and servicing plans;

[0060] Low risk, with a comprehensive assessment score of 80-89 points. Monitoring needs to be strengthened, with special attention paid to indicators that are close to or outside the normal range, and preventive maintenance should be performed when necessary.

[0061] Medium risk, with a comprehensive assessment score of 70-79 points, requires the immediate formulation and implementation of targeted risk control measures, a thorough inspection and repair of indicators that exceed the standard, and strengthening of daily inspections and monitoring;

[0062] High risk, with a comprehensive assessment score of less than 70 points, the vehicle must be stopped immediately for a comprehensive inspection and repair until all problems are completely resolved. The vehicle must not be put into use again before it resumes normal operation.

[0063] Preferably, the preset safety control strategies include: emergency braking, traction blocking, speed limit, fault diagnosis and isolation, sound and light alarm, data recording and reporting, and remote intervention;

[0064] Specifically, for risk-free, there is no need to regulate the vehicle, and the vehicle can just maintain normal operation;

[0065] For low risks, the train is allowed to complete the full-day operation route specified in the timetable and then return to the base, and the fault content is recorded directly.

[0066] For medium risk, the train is allowed to maintain the route specified in the operation diagram and then return to the base. The fault content will be displayed on the driver's display screen with the fault button flashing, and the fault button needs to be clicked to view.

[0067] For high-risk vehicles, the vehicle speed is controlled and it stops at the nearest station for maintenance or emergency braking, passengers are evacuated, and the empty vehicle returns to the base. The fault content is displayed in a pop-up window on the driver's display screen, accompanied by an audible and visual alarm. At the same time, the vehicle fault is diagnosed and isolated, and data of the risk is recorded and reported. In special circumstances, remote control intervention can be used to quickly resolve the fault.

[0068] Furthermore, in order to ensure the safe operation of urban rail vehicles and effectively respond to potential risks, safety control instructions are designed to be integrated and executed in real time. When the system detects a high-risk situation, it will immediately trigger an emergency braking instruction to stop the vehicle as quickly as possible to prevent the situation from further deteriorating. At the same time, the traction blocking instruction will be activated to block the vehicle's traction system to ensure that the vehicle will not accelerate accidentally due to misoperation or system failure. In order to ensure the safety of passengers and vehicles, the speed limit instruction will dynamically adjust the vehicle's maximum operating speed according to actual conditions to ensure that it travels at a safe speed in specific sections or conditions. The fault diagnosis and isolation instructions are responsible for quickly locating the source of the fault and preventing it through isolation measures. Fault diffusion facilitates subsequent maintenance work. The sound and light alarm command will be activated in an emergency, issuing warnings through sound and light signals to remind operators to pay attention and take corresponding measures. The data recording and reporting command is responsible for collecting and recording key data before and after the fault occurs, providing a basis for accident analysis and improvement. These data will be analyzed in detail and a report will be generated so that management and maintenance personnel can understand the cause of the fault and optimize system performance. If the remote monitoring center determines that the on-site situation requires more direct intervention, the remote intervention command will be sent to the vehicle, allowing professionals to directly operate the vehicle through the remote control system to quickly restore the normal operation of the vehicle or ensure the safe evacuation of passengers;

[0069] The algorithm is used to build a dynamic programming model to fine-tune the safety control strategy, consider the costs and benefits of different state transitions, and calculate the optimal safety control strategy sequence. The calculation method for calculating the optimal safety control strategy sequence is:

[0070]

[0071] In the formula, arg min represents the parameter value of the function to achieve the minimum value in its domain, γ represents the discount factor, π represents the strategy, s represents the state, t represents the time step, E represents the total number of time steps, c represents the cost, and C(s t ,π(s t )) means in state s t The execution strategy π(s t )’s immediate cost, V(s t+1 ) represents the future state s t+1 The value function of s t represents the state s at the t-th time step, π(s t ) represents the policy for state s at the tth time step.

[0072] Preferably, when a driving safety hazard is monitored or predicted, the problem is presented in the form of graphics and text, and is specific to a certain location in the vehicle, to help operators take correct countermeasures. Once an abnormality is detected or a potential risk is predicted, the monitoring display module will immediately pop up a striking alarm window, using eye-catching colors and flashing effects to attract the operator's attention. The alarm information should be concise and clear, directly pointing out the "driving safety hazard warning" or the specific type of abnormality. The real-time position map of the vehicle is displayed on the monitoring screen, and the specific location of the problem is highlighted or specially marked on the map.

[0073] In addition, the method also supports remote monitoring and diagnosis functions. By connecting to the remote monitoring center through wireless communication technology, the operator can view the vehicle's various operating parameters and status information in real time and discover abnormal situations in time. Once the system detects potential safety hazards or fault alarms, it will immediately remind the operator through sound, flash, pop-up windows and other methods to achieve remote real-time monitoring and fault diagnosis of the vehicle's operating status.

[0074] The method described in this embodiment can monitor and diagnose current vehicle faults in real time, and can also predict possible faults in the future, further ensuring the safe operation of the vehicle. At the same time, it can display the vehicle's operating status, fault information and the execution of safety control instructions in real time, so that the operator can quickly understand the overall condition of the vehicle. Through real-time monitoring, data analysis and prediction, intelligent control and remote monitoring, the safety of vehicle operation and the efficiency of troubleshooting are significantly improved.

[0075] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0076] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application further provides a traction safety control system for urban rail vehicles.

[0077] like Figure 2 As shown, the urban rail vehicle traction safety control system includes a data acquisition module 11, a data processing module 12, a safety control module 13 and a monitoring display module 14;

[0078] The data acquisition module 11 is used to monitor the vehicle's own operating status and passenger flow during operation. As the "sensing organ" of the system, it is widely distributed in key parts of the vehicle. Each sensor unit monitors the key operating parameters of the urban rail vehicle around the clock and continuously. The sensor unit has high precision and high sensitivity, and can capture small changes in the vehicle operation. The data is transmitted to the data processing module 12 through wireless transmission. The wireless transmission method not only reduces the wiring complexity and maintenance cost, but also improves the flexibility and reliability of data transmission;

[0079] After receiving the raw data from the sensor array module, the data processing module 12 first performs signal conversion, converting the analog signal into a digital signal for computer processing, and preprocessing the data, including steps such as denoising, filtering, and calibration, to improve the accuracy and reliability of the data. On this basis, the processed data is deeply analyzed using advanced algorithms to identify various factors that affect the driving safety of the vehicle. Through a comprehensive evaluation of these factors, the system can accurately determine the current operating status of the vehicle and predict future safety risks;

[0080] After receiving the evaluation results provided by the data processing module 12, the safety control module 13 first performs risk level classification, and classifies the safety risks into different levels according to the evaluation results. For the risks of different levels, the system generates corresponding safety control instructions, aiming to quickly eliminate or reduce the impact of safety risks on vehicle operation, and sends the generated safety control instructions to the vehicle main control system to execute corresponding safety measures;

[0081] The monitoring and display module 14 displays the real-time vehicle operation status and the information fed back by the safety control module 13. If necessary, the vehicle can be manually intervened through the monitoring and display module to prevent the system from being unable to respond in time to emergencies;

[0082] After each manual intervention, the safety control module 13 will automatically record the intervention process and generate a detailed report, including the intervention time, reasons, measures and results, etc. The data processing module 12 optimizes the algorithm based on these reports, adjusts the parameter settings, and improves the analysis model to improve the system's response speed and accuracy when facing similar emergencies in the future.

[0083] For the convenience of description, the above system is described by dividing the functions into various modules. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0084] The system of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0085] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any of the above embodiments is implemented.

[0086] Figure 3 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0087] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0088] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0089] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0090] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0091] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0092] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0093] The electronic device of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0094] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in any of the above embodiments.

[0095] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0096] The computer instructions stored in the storage medium of the above embodiments are used to enable the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0097] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0098] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0099] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0100] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A method for controlling traction safety of urban rail vehicles, characterized in that: include: Acquire vehicle status data and environmental data, and input the vehicle status data and the environmental data into a pre-constructed random forest model to obtain influencing factors on vehicle driving safety, wherein the random forest model is trained and constructed by the vehicle status data and the environmental data; Acquiring vehicle operation and maintenance data and passenger flow data, and calculating a comprehensive loss index of the vehicle based on the vehicle operation and maintenance data and the passenger flow data; A comprehensive evaluation score of the vehicle's operating status is calculated based on the influencing factors and the comprehensive loss index, and risk levels are divided based on the comprehensive evaluation score. A preset safety control strategy is executed based on the risk level to send corresponding safety control instructions to the vehicle, thereby controlling the vehicle to execute corresponding control measures.

2. The method according to claim 1, characterized in that: The random forest model construction method comprises: Performing data preprocessing on the vehicle state data and the environment data, and constructing a data set based on the preprocessed data, randomly dividing the data set into a training set and a test set, and setting random forest parameters, wherein the vehicle state data includes vehicle running state data, traction braking system data, and vehicle bogie data, and the forest parameters include the number of trees, the maximum depth, and the minimum number of samples; The vehicle state data and the environment data in the database are used as feature data, and a decision tree is constructed based on the feature data. During the construction process, a portion of the feature data and sample data are randomly selected for training to construct multiple decision trees, and multiple decision trees are integrated to construct a random forest model; The random forest model is trained by the training set, and the random forest model is tested by the test set.

3. The method according to claim 1, characterized in that The comprehensive loss index formula includes: Where CLI represents the comprehensive loss index, w i represents the weight of component i, d i represents the loss coefficient and maintenance record of component i, u i represents the usage frequency of component i based on passenger flow, y i Indicates the impact factor of operating years.

4. The method according to claim 1, characterized in that The calculating the comprehensive evaluation score of the vehicle's operating status according to the influencing factors and the comprehensive loss index includes: The influencing factors and the comprehensive loss index are divided into operating state factors, traction braking system factors, vehicle bogie factors, environmental factors and comprehensive loss factors; The comprehensive evaluation score of the vehicle's operating status is calculated based on the operating status factor, the traction braking system factor, the vehicle bogie factor, the environmental factor and the comprehensive loss factor, wherein the comprehensive evaluation score calculation formula is: Where S represents the comprehensive evaluation score, S1-S5 represent the operating status factor, traction braking system factor, vehicle bogie factor, environmental factor and comprehensive loss factor, respectively, and R1-R5 represent the weights of the operating status factor, traction braking system factor, vehicle bogie factor, environmental factor and comprehensive loss factor, respectively.

5. The method according to claim 1, characterized in that It also includes fine-tuning the security control strategy to calculate the optimal security control strategy, the calculation formula of which is: In the formula, arg min represents the parameter value of the function to achieve the minimum value in its domain, γ represents the discount factor, π represents the strategy, s represents the state, t represents the time step, E represents the total number of time steps, c represents the cost, and C(s t ,π(s t )) means in state s t The execution strategy π(s t )’s immediate cost, V(s t+1 ) represents the future state s t+1 The value function of s t represents the state s at the t-th time step, π(s t ) represents the policy for state s at the tth time step.

6. A traction safety control system for urban rail vehicles, characterized in that: It includes data acquisition module, data processing module, safety control module and monitoring display module; The data acquisition module is used to collect vehicle status data, environmental data, vehicle operation and maintenance data, and passenger flow data during operation; The data processing module is used to receive the raw data from the data acquisition module, perform data processing on the raw data, and comprehensively evaluate the current running state of the vehicle based on the processed data results; The safety control module is used to classify safety risks into different levels according to the evaluation results, and generate corresponding safety control instructions to control the vehicle to execute corresponding safety measures; The monitoring and display module is used to display the current vehicle operation information, vehicle status information and the execution status of safety control instructions, and supports remote access and monitoring functions.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 5 is implemented.

8. A non-transitory computer-readable storage medium, characterized in that: in, The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 5.

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