A rail vehicle performance detection system, a detection method, equipment and a medium

Abstract

The application discloses a kind of rail vehicle performance detection system, detection method, equipment and medium, including multiple shear force sensors, multiple fulcrum force measuring sensors, data analysis equipment and 5G millimeter wave base station;Shear force sensor is used to collect the shear stress that rail is subjected to under wheel, and shear stress is transmitted to fulcrum force measuring sensor;Fulcrum force measuring sensor is used to obtain the vertical force and horizontal force that rail fulcrum is subjected to under wheel, and shear stress, vertical force and horizontal force are sent to 5G millimeter wave base station by wireless communication mode;5G millimeter wave base station is used to send shear stress, vertical force and horizontal force to data analysis equipment;Data analysis equipment is used to determine the operating parameter of rail vehicle, and the operating performance of rail vehicle is detected according to operating parameter.The technical scheme of the embodiment of the application can reduce the laying workload of signal cable on the track, and reduce the operation risk of rail vehicle.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the field of rail transit technology, and in particular to a rail vehicle performance detection system, a detection method, equipment and a medium. BACKGROUND

[0002] The dynamic performance detection of the rail transit vehicle is particularly important for the safety of rail transit transportation. In the prior art, the dynamic performance detection of the rail transit vehicle is usually performed by using a continuous wheel-rail force detection method of "shear force + support force", that is, shear force sensor nodes are installed at the center of the sleeper box, the middle of the rail and the axle position, two-dimensional support point force sensor nodes are installed at all sleeper support point positions, all sensor node signal lines are collected, and then connected to a centralized signal collection and conditioning device, and then the wheel-rail force signal is collected, AD conversion is performed, and the calculation of related dynamic indexes, the evaluation of the vehicle state are completed by using a data acquisition and analysis system.

[0003] However, in the existing performance detection method, all sensors are connected in a wired manner, and signal cable protection grooves / pipes need to be arranged on both sides of the rail and between the left and right rails for protection of the sensor signal cables, which greatly increases the workload of equipment installation and construction, and more importantly, greatly increases the safety risk of train operation, especially for high-speed rail operation. The cable protection grooves / pipes are fixed on the track plate or the sleeper by using mechanical or chemical anchors through post-anchoring, and under the action of long-term wind and sun, high-speed train wind load and the like, there is a risk of falling due to rusting and aging, which greatly increases the risk of train operation safety. SUMMARY

[0004] The embodiment of the present application provides a rail vehicle performance detection system, a detection method, equipment and a medium, which can realize high-speed acquisition of continuous wheel-rail force signals, improve the accuracy of the performance detection results of the rail vehicle, reduce the workload of signal cable arrangement on the track, and reduce the operation risk of the rail vehicle.

[0005] In a first aspect, the embodiment of the present application provides a rail vehicle performance detection system, characterized in that the system comprises a plurality of shear force sensors, a plurality of support point force measurement sensors, a data analysis device and a 5G millimeter wave base station.

[0006] The shear force sensor is configured to collect the shear stress of the rail under the action of the wheel and transmit the shear stress to the support point force measurement sensor.

[0007] The support point force measurement sensor is configured to obtain the vertical force and the horizontal force of the rail support point under the action of the wheel, and transmit the shear stress, the vertical force and the horizontal force to the 5G millimeter wave base station through a wireless communication mode.

[0008] The 5G millimeter wave base station is configured to send the shear stress, vertical force and horizontal force to a data analysis device.

[0009] Optionally, the shear force sensor is arranged in the rail at the center of the sleeper box and the axle position, and the fulcrum force measuring sensor is arranged at the fulcrum position of the sleeper.

[0010] Optionally, the system further comprises an image recognition device.

[0011] The image recognition device is configured to identify identification information of the rail locomotive vehicle and send the identification information to the data analysis device.

[0012] The data analysis device is further configured to establish a mapping relationship between the identification information and the performance detection result of the rail locomotive vehicle.

[0013] Optionally, the fulcrum force measuring sensor comprises a fulcrum force sensing module, a signal conditioning conversion module and a 5G millimeter wave terminal sending module.

[0014] The fulcrum force sensing module is configured to collect the vertical force and horizontal force of the rail fulcrum under the action of the wheel.

[0015] The signal conditioning conversion module is configured to process analog signals corresponding to the vertical force, horizontal force and shear stress, and transmit the processing result to the 5G millimeter wave terminal sending module.

[0016] The 5G millimeter wave terminal sending module is configured to send the processing result to the 5G millimeter wave base station through a wireless communication link.

[0017] In a second aspect, the embodiments of the present application also provide a rail locomotive vehicle performance detection method, which is applied to the data analysis device provided by any embodiment and comprises the following steps:

[0018] Receiving the shear stress of the rail under the action of the wheel and the vertical force and horizontal force of the rail fulcrum under the action of the wheel sent by the 5G millimeter wave base station.

[0019] According to a preset parameter calculation model, determining the corresponding running parameters of the rail locomotive vehicle according to the shear stress, vertical force and horizontal force.

[0020] According to a preset performance detection model, detecting the running performance of the rail locomotive vehicle according to the corresponding running parameters of the rail locomotive vehicle.

[0021] Optionally, the operation parameters include impact force, frequency, wheel speed and wheel load corresponding to the track locomotive vehicle.

[0022] The operation performance of the track locomotive vehicle is detected according to the operation parameters corresponding to the track locomotive vehicle through a preset performance detection model, including:

[0023] At least one tread damage degree index value corresponding to the track locomotive vehicle is determined according to the impact force, frequency, wheel speed and wheel load corresponding to the track locomotive vehicle through a preset wheel tread damage evaluation model.

[0024] Optionally, the operation parameters include wheel-rail dynamics parameters, hunting instability wavelength, speed and total weight corresponding to the track locomotive vehicle.

[0025] The operation performance of the track locomotive vehicle is detected according to the operation parameters corresponding to the track locomotive vehicle through a preset performance detection model, including:

[0026] A hunting state score corresponding to the track locomotive vehicle is determined according to the wheel-rail dynamics parameters, hunting instability wavelength, speed and total weight corresponding to the track locomotive vehicle through a preset hunting instability evaluation model.

[0027] Optionally, the operation parameters include wheel speed, wheel load and total weight corresponding to the track locomotive vehicle.

[0028] The operation performance of the track locomotive vehicle is detected according to the operation parameters corresponding to the track locomotive vehicle through a preset performance detection model, including:

[0029] An overload index value and a bias load index value corresponding to the track locomotive vehicle are determined according to the wheel speed, wheel load and total weight corresponding to the track locomotive vehicle through a preset super-bias load evaluation model.

[0030] In a third aspect, an embodiment of the present application further provides a data analysis device, which comprises:

[0031] One or more processors;

[0032] A storage device for storing one or more programs;

[0033] When the one or more programs are executed by the one or more processors, the one or more processors perform the track locomotive vehicle performance detection method provided by any embodiment of the present application.

[0034] In a fourth aspect, the embodiments of the present application further provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the track vehicle performance detection method provided by any of the embodiments of the present application.

[0035] The technical scheme of the embodiments of the present application provides a track vehicle performance detection system, by deploying a plurality of shear force sensors and fulcrum force measuring sensors on the steel rail, continuous wheel-rail force signal high-speed acquisition can be realized, and real-time evaluation of the track vehicle performance can be realized, thereby improving the accuracy of the track vehicle performance detection result; secondly, by using a wireless measuring sensor based on 5G millimeter wave communication and deploying a 5G millimeter wave base station, on the one hand, the anti-interference ability of the signal transmission process and the reliability of the transmission result can be improved, and on the other hand, the workload of the signal cable layout on the track can be reduced, the operation risk of the track vehicle can be reduced, and the safety and the installation convenience of the detection system are improved. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 is a structural schematic diagram of a track vehicle performance detection system in the first embodiment of the present application;

[0037] Figure 2a is a structural schematic diagram of another track vehicle performance detection system in the second embodiment of the present application;

[0038] Figure 2b is a structural schematic diagram of a fulcrum force measuring sensor in the second embodiment of the present application;

[0039] Figure 2c is a structural schematic diagram of another fulcrum force measuring sensor in the second embodiment of the present application;

[0040] Figure 3 is a flowchart of a track vehicle performance detection method in the third embodiment of the present application;

[0041] Figure 4 is a structural schematic diagram of a data analysis device in the fourth embodiment of the present application. DETAILED DESCRIPTION

[0042] The present application will be further described below in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application. In addition, it should be noted that, for the convenience of description, only the parts related to the present application are shown in the drawings, but not all the structures.

[0043] Embodiment one

[0044] Figure 1A structural schematic diagram of a rail vehicle performance detection system provided for an embodiment of the present application, the rail vehicle performance detection system comprising a plurality of shear force sensors 101, a plurality of fulcrum force measuring sensors 102, a data analysis device, and a 5G millimeter wave base station.

[0045] As shown in the embodiment, the plurality of shear force sensors 101 and the fulcrum force measuring sensors 102 can be deployed on both sides of the steel rail. The fulcrum force measuring sensors 102 can be two-dimensional fulcrum force measuring wireless digital sensors. By installing shear force sensors and fulcrum force measuring sensors on the steel rail, the "shear force + support force" continuous wheel-rail force detection technology can be used to realize continuous measurement of the vertical force and horizontal force of the wheel-rail. Figure 1 In a specific embodiment, the shear force sensor 101 can be connected to the fulcrum force measuring sensor 102 through a signal conversion connecting cable. The shear force sensor 101 is used to collect the shear stress of the steel rail under the action of the wheel and transmit the shear stress to the fulcrum force measuring sensor 102.

[0046] The fulcrum force measuring sensor 102 is used to obtain the vertical force and horizontal force of the steel rail fulcrum under the action of the wheel, and transmit the shear stress, vertical force and horizontal force to the 5G millimeter wave base station by wireless communication. The 5G millimeter wave base station is used to transmit the shear stress, vertical force and horizontal force to the data analysis device. The data analysis device is used to determine the operating parameters of the rail vehicle according to the shear stress, vertical force and horizontal force, and detect the operating performance of the rail vehicle according to the operating parameters.

[0047] In the embodiment, the 5G millimeter wave base station can be deployed beside the steel rail, and the distance between the 5G millimeter wave base station and the fulcrum force measuring sensor 102 is not greater than 200m. The 5G millimeter wave base station and the fulcrum force measuring sensor 102 can transmit data through a wireless communication link. Specifically, the working bandwidth of the wireless communication link is 2160MHz, and the working frequency is 59-64GHz.

[0048] In an embodiment of the present application, after the data analysis device obtains the shear stress, vertical force and horizontal force, the continuous wheel-rail vertical force and horizontal force can be input into a preset parameter analysis model, and then the operating parameters of the wheel-rail, such as the dynamic parameters, the snaking instability wavelength, the impact force and frequency, the wheel speed, the wheel weight and the total weight, etc. are determined through the parameter calculation analysis model. After obtaining the above operating parameters, the performance detection model constructed in advance can be used to evaluate the operating performance (or operating quality) of the rail vehicle according to the operating parameters.

[0049] In an embodiment of the present application, the data analysis device can be a computer or a server.

[0050] In a specific embodiment, when continuously detecting the wheel-rail force of the rail vehicle, a plurality of fulcrum force measuring sensors 102 can be arranged between two continuous shear force sensors 101 (as shown in the figure), and then the two continuous shear force sensors 101 and the plurality of fulcrum force measuring sensors 102 therebetween are taken as a unit detection area. Wherein, the distance between the two shear force sensors 101 corresponding to each unit detection area needs to be less than the minimum bogie wheelbase of the main rail vehicle. Figure 1

[0051] Optionally, in order to detect the full wheel circumference of the rail vehicle and / or the snake wavelength of the rail vehicle, two or more unit detection areas can be arranged on the rail, and two adjacent unit detection areas share an end shear force sensor.

[0052] In the embodiment, after the plurality of unit detection areas obtain the wheel-rail vertical force and horizontal force of each wheel of the rail vehicle, the wheel-rail vertical force and horizontal force of the wheel in the plurality of unit detection areas can be combined according to the time sequence of each wheel.

[0053] The technical scheme of the embodiment of the present application provides a rail vehicle performance detection system, by arranging a plurality of shear force sensors and fulcrum force measuring sensors on the rail, continuous wheel-rail force signals can be collected at high speed, and the running performance of the rail vehicle can be evaluated in real time, thereby improving the accuracy of the performance detection result of the rail vehicle. Secondly, by using a wireless measuring sensor based on 5G millimeter wave communication and deploying a 5G millimeter wave base station, on the one hand, the anti-interference ability of the signal transmission process and the reliability of the transmission result can be improved, and on the other hand, the workload of laying signal cables on the rail can be reduced, the running risk of the rail vehicle can be reduced, and the safety and the convenience of installation of the detection system can be improved.

[0054] Embodiment two

[0055] Figure 2a is a structural schematic diagram of a rail vehicle performance detection system in the embodiment two of the present application, which is refined on the basis of the above-mentioned embodiment. In the embodiment, the shear force sensors are arranged at the center of the sleeper box and the axle position in the rail; and the fulcrum force measuring sensors are arranged at the fulcrum position of the sleeper.

[0056] As shown in the figure, the system further comprises an image recognition device; the image recognition device is used for identifying the identification information of the rail vehicle, and sending the identification information to the data analysis device; and the data analysis device is further used for establishing the mapping relationship between the identification information and the performance detection result of the rail vehicle. Figure 2a

[0057] ​​In a specific embodiment, the image recognition device can be used to recognize the electronic tag of the rail vehicle, and obtain the identification information corresponding to the rail vehicle. Optionally, the identification information can be the number information of the rail vehicle.

[0058] The advantage of this arrangement is that by deploying the image recognition device in the rail vehicle performance detection system, the rail vehicle can be tracked and detected and evaluated comprehensively at multiple frequencies.

[0059] In an embodiment of the present embodiment, the fulcrum force measuring sensor 102 can include a fulcrum force sensing module, a signal conditioning conversion module, and a 5G millimeter wave terminal sending module.

[0060] The fulcrum force sensing module is configured to collect the vertical force and horizontal force received by the rail fulcrum under the action of the wheel. The signal conditioning conversion module is configured to process (e.g., amplify, filter, and AD convert, etc.) the analog signals corresponding to the vertical force, horizontal force, and shear stress, and transmit the processing results to the 5G millimeter wave terminal sending module. The 5G millimeter wave terminal sending module is configured to transmit the processing results to the 5G millimeter wave base station through a wireless communication link.

[0061] In a specific embodiment, the fulcrum force measuring sensor 102 can further include a shear force sensor access terminal and a battery power supply module. The shear force sensor access terminal is configured to receive the shear stress transmitted by the shear force sensor. The battery power supply module is configured to power the fulcrum force sensing module, the signal conditioning conversion module, the 5G millimeter wave terminal sending module, etc.

[0062] In an embodiment of the present embodiment, Figure 2b is a structural schematic diagram of the fulcrum force measuring sensor 102 in the present embodiment. As shown in Figure 2b The fulcrum force sensing module in the fulcrum force measuring sensor 102 can be integrated with the signal conditioning conversion module, the 5G millimeter wave terminal sending module, and the battery power supply module in an integrated design. The fulcrum force sensing module, the signal conditioning conversion module, the 5G millimeter wave terminal sending module, and the battery power supply module can be integrated in a unified device to form the fulcrum force measuring sensor 102.

[0063] In another embodiment of the present embodiment, Figure 2c is another structural schematic diagram of the fulcrum force measuring sensor 102 in the present embodiment. As shown in Figure 2cAs shown, the fulcrum force sensing module in the fulcrum force measuring sensor 102 can be designed separately from the signal conditioning conversion module, the 5G millimeter wave terminal sending module and the battery power supply module. The signal conditioning conversion module, the 5G millimeter wave terminal sending module and the battery power supply module can be integrated in one device, and the fulcrum force sensing module can be integrated separately in another device, and the two devices constitute the fulcrum force measuring sensor 102.

[0064] The technical scheme of the embodiment of the present application can realize effective tracking of the rail locomotive vehicle and multi-frequency detection and comprehensive evaluation by deploying an image recognition device in the rail locomotive vehicle performance detection system. Secondly, by deploying the fulcrum force sensing module, the signal conditioning conversion module and the 5G millimeter wave terminal sending module in the fulcrum force measuring sensor, the anti-interference ability of the signal transmission process can be improved, the reliability of the transmission result can be improved, the workload of laying signal cables on the track can be reduced, the running risk of the rail locomotive vehicle can be reduced, and the safety and convenience of the detection system are improved.

[0065] Embodiment three

[0066] Figure 3 A flowchart of a rail locomotive vehicle performance detection method provided by the third embodiment of the present application, the present embodiment can be applied to the case of detecting the running performance of the rail locomotive vehicle, and the method can be executed by a data analysis device in a rail locomotive vehicle performance detection system. The rail locomotive vehicle performance detection method specifically includes the following steps:

[0067] Step 310, receiving the shear stress of the rail under the action of the wheel and the vertical force and the horizontal force of the rail fulcrum under the action of the wheel sent by the 5G millimeter wave base station.

[0068] Step 320, calculating and analyzing the model according to the preset parameters, determining the corresponding running parameters of the rail locomotive vehicle according to the shear stress, vertical force and horizontal force.

[0069] In the present embodiment, the running parameters can include the corresponding dynamic parameters of the rail locomotive vehicle, the wavelength of the hunting instability, the impact force and frequency, the wheel speed, the wheel weight and the total weight, etc.

[0070] Step 330, detecting the running performance of the rail locomotive vehicle according to the corresponding running parameters of the rail locomotive vehicle by the preset performance detection model.

[0071] In the present embodiment, after obtaining the above running parameters, a pre-constructed performance detection model can be used to evaluate the running performance (or running quality) of the rail locomotive vehicle according to the running parameters.

[0072] The technical scheme of the embodiment of the present application receives the shear stress of the rail under the action of the wheel and the vertical force and the horizontal force of the rail fulcrum under the action of the wheel sent by the 5G millimeter wave base station, calculates and analyzes the model according to the preset parameters, determines the corresponding running parameters of the rail vehicle according to the shear stress, the vertical force and the horizontal force, and detects the running performance of the rail vehicle according to the corresponding running parameters of the rail vehicle through the preset performance detection model. The technical means can evaluate the running performance of the rail vehicle in real time, and improve the accuracy of the performance detection result of the rail vehicle.

[0073] On the basis of the above-mentioned embodiment, the running parameters include the impact force, the frequency, the wheel speed and the wheel weight corresponding to the rail vehicle; the running performance of the rail vehicle is detected according to the running parameters corresponding to the rail vehicle through the preset performance detection model, including: at least one tread damage degree index value corresponding to the rail vehicle is determined according to the impact force, the frequency, the wheel speed and the wheel weight corresponding to the rail vehicle through the preset wheel tread damage judgment model.

[0074] The running parameters include the wheel-rail dynamics parameters, the snake instability wavelength, the speed and the total weight corresponding to the rail vehicle; the running performance of the rail vehicle is detected according to the running parameters corresponding to the rail vehicle through the preset performance detection model, including: the snake state score corresponding to the rail vehicle is determined according to the wheel-rail dynamics parameters, the snake instability wavelength, the speed and the total weight corresponding to the rail vehicle through the preset snake instability judgment model.

[0075] The running parameters include the wheel speed, the wheel weight and the total weight corresponding to the rail vehicle; the running performance of the rail vehicle is detected according to the running parameters corresponding to the rail vehicle through the preset performance detection model, including: the overload index value and the unbalanced load index value corresponding to the rail vehicle are determined according to the wheel speed, the wheel weight and the total weight corresponding to the rail vehicle through the preset overload judgment model.

[0076] Embodiment four

[0077] Figure 4A schematic diagram of a data analysis device 10, which can be used to implement embodiments of the present invention, is shown. The data analysis device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The data analysis device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0078] like Figure 4 As shown, the data analysis device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the data analysis device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0079] Multiple components in the data analysis device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, optical disk, etc.; and a communication unit 19, such as a network card, modem, wireless transceiver, etc. The communication unit 19 allows the data analysis device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0080] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a rail vehicle performance testing method.

[0081] In some embodiments, the rail vehicle performance detection method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded and / or installed onto data analysis device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the above-described rail vehicle performance detection method can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the rail vehicle performance detection method by other any suitable means, e.g., with the aid of firmware.

[0082] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0083] Computer programs used to implement the methods of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0084] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0085] To provide for interaction with a user, the systems and techniques described here can be implemented on a data analysis device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the data analysis device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0086] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0087] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0088] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0089] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A rail vehicle performance detection system, characterized by, The system comprises a plurality of shear force sensors, a plurality of fulcrum force measuring sensors, a data analysis device and a 5G millimeter wave base station. The shear force sensors are arranged in the rail at the center of the sleeper box and the axle position to collect the shear stress of the rail under the action of the wheel and transmit the shear stress to the fulcrum force measuring sensor. The fulcrum force measuring sensor is arranged at the fulcrum position of the rail to obtain the vertical force and horizontal force of the rail at the fulcrum under the action of the wheel, and transmit the shear stress, vertical force and horizontal force to the 5G millimeter wave base station through wireless communication. The 5G millimeter wave base station is arranged beside the rail, and the distance between the 5G millimeter wave base station and the fulcrum force measuring sensor is not more than 200m. The 5G millimeter wave base station is used to transmit the shear stress, vertical force and horizontal force to the data analysis device. The data analysis device is used to determine the running parameters of the rail vehicle according to the shear stress, vertical force and horizontal force, and detect the running performance of the rail vehicle according to the running parameters. The fulcrum force measuring sensor comprises a fulcrum force sensing module, a signal conditioning conversion module and a 5G millimeter wave terminal sending module. The fulcrum force sensing module is used to collect the vertical force and horizontal force of the rail at the fulcrum under the action of the wheel.

2. The rail vehicle performance detection system of claim 1, wherein, The signal conditioning conversion module is used to process the analog signals corresponding to the vertical force, horizontal force and shear stress, and transmit the processing results to the 5G millimeter wave terminal sending module. The 5G millimeter wave terminal sending module is used to transmit the processing results to the 5G millimeter wave base station through the wireless communication link. The system further comprises an image recognition device.

3. A method of detecting performance of a railway rolling stock, characterized by, The image recognition device is used to identify the identification information of the rail vehicle and transmit the identification information to the data analysis device. The data analysis device is further used to establish the mapping relationship between the identification information and the performance detection result of the rail vehicle. The data analysis device applied to the rail vehicle performance detection system of any one of claims 1-2, the method comprises: receiving the shear stress of the rail under the action of the wheel and the vertical force and horizontal force of the rail at the fulcrum under the action of the wheel sent by the 5G millimeter wave base station; 4. The method of claim 3, wherein, determining the corresponding running parameters of the rail vehicle according to the shear stress, vertical force and horizontal force according to the preset parameter calculation analysis model; detecting the running performance of the rail vehicle according to the corresponding running parameters of the rail vehicle through the preset performance detection model. The running parameters comprise the impact force, frequency, wheel speed and wheel weight corresponding to the rail vehicle. The detection of the running performance of the rail vehicle according to the corresponding running parameters of the rail vehicle through the preset performance detection model comprises: The preset wheel tread damage evaluation model is used to determine at least one tread damage degree index value of the track vehicle according to the impact force, frequency, wheel speed and wheel load corresponding to the track vehicle.

5. The method of claim 3, wherein, The operation parameters include wheel-rail dynamics parameters, hunting instability wavelength, speed and total weight corresponding to the track vehicle. The preset performance detection model is used to detect the operation performance of the track vehicle according to the operation parameters corresponding to the track vehicle, including: The preset hunting instability evaluation model is used to determine a hunting state score of the track vehicle according to the wheel-rail dynamics parameters, hunting instability wavelength, speed and total weight corresponding to the track vehicle.

6. The method of claim 3, wherein, The operation parameters include wheel speed, wheel load and total weight corresponding to the track vehicle. The preset performance detection model is used to detect the operation performance of the track vehicle according to the operation parameters corresponding to the track vehicle, including: The preset overloading evaluation model is used to determine an overloading index value and an unbalanced loading index value of the track vehicle according to the wheel speed, wheel load and total weight corresponding to the track vehicle.

7. A data analysis device comprising: one or more processors; storage for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors perform the track vehicle performance detection method according to any one of claims 3-6.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the track vehicle performance detection method according to any one of claims 3-6. The program is executed by the processor to implement the track vehicle performance detection method according to any one of claims 3-6.

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