CN116593191A - Rail locomotive vehicle performance detection system, detection method, detection equipment and medium - Google Patents
Rail locomotive vehicle performance detection system, detection method, detection equipment and medium Download PDFInfo
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Abstract
The invention discloses a railway locomotive vehicle performance detection system, a detection method, equipment and a medium, wherein the detection system comprises a plurality of shear force sensors, a plurality of fulcrum force measurement sensors, data analysis equipment and a 5G millimeter wave base station; the shear force sensor is used for collecting the shear stress of the steel rail under the wheels and transmitting the shear stress to the fulcrum force measuring sensor; the fulcrum force measuring sensor is used for acquiring vertical force and horizontal force applied to the steel rail fulcrum under the wheels and transmitting the shearing stress, the vertical force and the horizontal force to the 5G millimeter wave base station in a wireless communication mode; the 5G millimeter wave base station is used for transmitting the shearing stress, the vertical force and the horizontal force to the data analysis equipment; the data analysis equipment is used for determining the operation parameters of the rail locomotive, and detecting the operation performance of the rail locomotive according to the operation parameters. The technical scheme of the embodiment of the invention can reduce the layout workload of the signal cables on the track and reduce the running risk of rail locomotives.
Description
Technical Field
The embodiment of the invention relates to the technical field of rail transit, in particular to a rail locomotive vehicle performance detection system, a detection method, equipment and a medium.
Background
The dynamic performance detection is carried out on rail transit rolling stock, and is particularly important for rail transit safety. In the prior art, when the dynamic performance of rail transit rolling stock is detected, a continuous wheel-rail mechanical detection method of shearing force and supporting force is generally adopted, namely, a shearing force sensor node is arranged at the center of a sleeper box, the middle and axle positions of a steel rail, two-dimensional fulcrum force sensor nodes are arranged at all sleeper fulcrum positions, all sensor node signal lines are collected and then connected to a centralized signal acquisition and conditioning device, and then the acquisition and AD conversion of wheel-rail force signals, the calculation of relevant dynamic indexes and the evaluation of vehicle states are completed through a data acquisition and analysis system.
However, in the existing performance detection method, all sensors are connected in a wired mode, and signal cable protection grooves/pipes and the like are required to be distributed on two sides of the steel rail on the track and between the left steel rail and the right steel rail for protecting the sensor signal cables. The cable protection groove/pipe is fixed on the track plate or the sleeper by utilizing a mechanical anchor bolt or a chemical anchor bolt in a post-anchoring mode, and under the effects of long-term wind blowing and sun exposure, wind load of a high-speed train and the like, the risk of falling off caused by corrosion, aging and the like exists, so that the running safety risk is greatly increased.
Disclosure of Invention
The embodiment of the invention provides a rail locomotive 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 a rail locomotive vehicle performance detection result, reduce the layout workload of signal cables on a rail and reduce the running risk of the rail locomotive vehicle.
In a first aspect, an embodiment of the present invention provides a rail locomotive vehicle performance detection system, which is characterized by including a plurality of shear force sensors, a plurality of fulcrum force measurement sensors, a data analysis device, and a 5G millimeter wave base station;
the shear force sensor is used for collecting the shear stress of the steel rail under the action of the wheels and transmitting the shear stress to the fulcrum force measuring sensor;
the fulcrum force measuring sensor is used for acquiring vertical force and horizontal force applied to the steel rail fulcrum under the action of the wheels and transmitting the shearing stress, the vertical force and the horizontal force to the 5G millimeter wave base station in a wireless communication mode;
the 5G millimeter wave base station is used for transmitting the shearing stress, the vertical force and the horizontal force to data analysis equipment; the data analysis equipment is used for determining the operation parameters of the rail locomotive according to the shearing stress, the vertical force and the horizontal force and detecting the operation performance of the rail locomotive according to the operation parameters.
Optionally, the shear force sensor is arranged at the middle and axle positions of the steel rail at the center of the sleeper box; the fulcrum force measuring sensor is deployed at the sleeper fulcrum position.
Optionally, the system further comprises an image recognition device;
the image recognition equipment is used for recognizing the identification information of the rail locomotive and sending the identification information to the data analysis equipment;
the data analysis equipment is also used for establishing a mapping relation between the identification information and the railway locomotive vehicle performance detection result.
Optionally, the fulcrum force measuring sensor comprises a fulcrum force sensing module, a signal conditioning and converting module and a 5G millimeter wave terminal sending module;
the fulcrum force sensing module is used for collecting vertical force and horizontal force applied to the steel rail fulcrum under the action of wheels;
the signal conditioning conversion module is used for processing analog signals corresponding to the vertical force, the horizontal force and the shearing stress and transmitting the processing result to the 5G millimeter wave terminal sending module;
and the 5G millimeter wave terminal sending module is used for sending the processing result to the 5G millimeter wave base station through a wireless communication link.
In a second aspect, an embodiment of the present invention further provides a method for detecting a performance of a rail locomotive, where the method is applied to the data analysis device provided in any embodiment, and includes:
receiving shearing stress of a steel rail under the action of wheels and vertical force and horizontal force of a steel rail fulcrum under the action of wheels, which are sent by a 5G millimeter wave base station;
according to a preset parameter calculation analysis model, determining the corresponding operation parameters of the rail locomotive according to the shear stress, the vertical force and the horizontal force;
and detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive through a preset performance detection model.
Optionally, the operation parameters comprise impact force, frequency, wheel speed and wheel weight corresponding to the rail locomotive;
detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps:
and determining at least one tread damage degree index value corresponding to the rail locomotive according to the impact force, the frequency, the wheel speed and the wheel weight corresponding to the rail locomotive by a preset wheel tread damage judging model.
Optionally, the operation parameters comprise corresponding wheeltrack dynamics parameters, hunting destabilization wavelength, speed and gross weight of the rail locomotive;
detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps:
and determining a corresponding hunting state score of the rail locomotive according to the wheel track dynamic parameters, the hunting instability wavelength, the speed and the total weight corresponding to the rail locomotive through a preset hunting instability judging model.
Optionally, the operation parameters comprise the corresponding wheel speed, wheel weight and total weight of the rail locomotive;
detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps:
and determining overload index values and unbalanced load index values corresponding to the rail locomotive according to the wheel speeds, the wheel weights and the total weights corresponding to the rail locomotive through a preset overload and unbalanced load judging model.
In a third aspect, an embodiment of the present invention further provides a data analysis apparatus, including:
one or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the rail vehicle performance detection method provided by any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where a computer program is stored, where the program when executed by a processor implements the method for detecting performance of a rail locomotive according to any embodiment of the present invention.
The technical scheme of the embodiment of the invention provides a rail locomotive vehicle performance detection system, which can realize high-speed acquisition of continuous wheel rail force signals and real-time evaluation of the running performance of the rail locomotive vehicle by arranging a plurality of shear force sensors and fulcrum force measurement sensors on a steel rail, thereby improving the accuracy of the rail locomotive vehicle performance detection result; secondly, through adopting the wireless measurement sensor based on 5G millimeter wave communication to and deploying 5G millimeter wave base station, on the one hand can improve the interference killing feature of signal transmission process, and the reliability of transmission result, on the other hand can also reduce the laying work load of signal cable on the track, reduce the running risk of rail locomotive vehicle, promoted detecting system's security and installation's convenience.
Drawings
FIG. 1 is a schematic diagram of a rail vehicle performance test system according to a first embodiment of the present invention;
FIG. 2a is a schematic diagram of another rail locomotive vehicle performance monitoring system according to a second embodiment of the present invention;
FIG. 2b is a schematic diagram of a sensor for measuring fulcrum force according to a second embodiment of the invention;
FIG. 2c is a schematic diagram of another embodiment of the present invention;
FIG. 3 is a flow chart of a rail locomotive vehicle performance detection method in accordance with a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a data analysis device in a fourth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a schematic structural diagram of a rail locomotive vehicle performance detection system according to an embodiment of the present invention, where the rail locomotive vehicle performance detection system includes a plurality of shear force sensors 101, a plurality of fulcrum force measurement sensors 102, a data analysis device, and a 5G millimeter wave base station.
As shown in fig. 1, in the present embodiment, a plurality of shear force sensors 101 and fulcrum force measurement sensors 102 may be disposed on both sides of the rail. The fulcrum force measurement sensor 102 may be a two-dimensional fulcrum force measurement wireless digital sensor. By installing a shear force sensor and a fulcrum force measuring sensor on the steel rail, the continuous wheel rail force detection technology of shearing force and supporting force can be adopted, and continuous measurement of vertical force and horizontal force of the wheel rail can be realized.
In a specific embodiment, the shear force sensor 101 may be connected to the fulcrum force measurement sensor 102 by a signal transduction cable. The shear force sensor 101 is used for collecting the shear stress of the steel rail under the action of the wheels and transmitting the shear stress to the fulcrum force measuring sensor 102.
The fulcrum force measuring sensor 102 is configured to obtain a vertical force and a horizontal force applied to the steel rail fulcrum under the action of the wheel, and send the shearing stress, the vertical force and the horizontal force to the 5G millimeter wave base station through wireless communication. The 5G millimeter wave base station is used for transmitting the shearing stress, the vertical force and the horizontal force to data analysis equipment; the data analysis equipment is used for determining the operation parameters of the rail locomotive according to the shearing stress, the vertical force and the horizontal force and detecting the operation performance of the rail locomotive according to the operation parameters.
In this embodiment, a 5G millimeter wave base station may be disposed beside the rail, the distance between the 5G millimeter wave base station and the fulcrum force measurement sensor 102 being no greater than 200m. The 5G millimeter wave base station and the fulcrum force measurement sensor 102 may perform data transmission via a wireless communication link. Specifically, the working bandwidth corresponding to the wireless communication link is 2160MHz, and the working frequency is 59-64 GHz.
In one implementation of this embodiment, after the data analysis device obtains the shear stress, the vertical force and the horizontal force, the continuous wheel-rail vertical force and the horizontal force may be input into a preset parameter analysis model, and then the running parameters of the wheel rail, such as the dynamics parameters, the hunting instability wavelength, the impact force and frequency, the wheel speed, the wheel weight, the total weight, and the like, are determined through the parameter calculation analysis model. After the operation parameters are obtained, a pre-built performance detection model can be adopted, and the operation performance (or the operation quality) of the rail locomotive vehicle can be evaluated according to the operation parameters.
In a specific embodiment, in the continuous detection of the wheeltrack force of the rail vehicle, a plurality of fulcrum force measurement sensors 102 (as shown in fig. 1) may be disposed between two continuous shear force sensors 101, and then the two continuous shear force sensors 101 and the plurality of fulcrum force measurement 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 smaller than the minimum bogie axle distance of the main rail transit rolling stock.
Alternatively, two or more unit detection zones may be deployed on the rail, with two adjacent unit detection zones sharing an end shear force sensor, for detection of the rolling stock full wheel circumference and/or rolling stock hunting wavelength.
In this embodiment, after the plurality of unit areas acquire the vertical force and the horizontal force of the wheel rail of each wheel of the rail locomotive, the vertical force and the horizontal force of the continuous wheel rail of each wheel in the plurality of unit areas can be obtained by combining according to the time sequence of each wheel.
The technical scheme of the embodiment of the invention provides a rail locomotive vehicle performance detection system, which can realize high-speed acquisition of continuous wheel rail force signals and real-time evaluation of the running performance of the rail locomotive vehicle by arranging a plurality of shear force sensors and fulcrum force measurement sensors on a steel rail, thereby improving the accuracy of the rail locomotive vehicle performance detection result; secondly, through adopting the wireless measurement sensor based on 5G millimeter wave communication to and deploying 5G millimeter wave base station, on the one hand can improve the interference killing feature of signal transmission process, and the reliability of transmission result, on the other hand can also reduce the laying work load of signal cable on the track, reduce the running risk of rail locomotive vehicle, promoted detecting system's security and installation's convenience.
Example two
Fig. 2a is a schematic structural diagram of a rail locomotive vehicle performance detecting system according to a second embodiment of the present invention, which is refined based on the above-mentioned embodiment. In the embodiment, the shear force sensor is arranged at the middle and axle positions of the steel rail at the center of the sleeper box; the fulcrum force measuring sensor is deployed at the sleeper fulcrum position.
As shown in fig. 2a, the system further comprises an image recognition device; the image recognition equipment is used for recognizing the identification information of the rail locomotive and sending the identification information to the data analysis equipment; the data analysis equipment is also used for establishing a mapping relation between the identification information and the railway locomotive vehicle performance detection result.
In a specific embodiment, the image recognition device may be used to recognize an electronic tag of a rail locomotive, so as to obtain identification information corresponding to the rail locomotive. Alternatively, the identification information may be the number information of the rail vehicle.
The advantage of this is that by arranging the image recognition device in the rail locomotive vehicle performance detection system, the rail locomotive vehicle can be conveniently tracked, and the comprehensive evaluation of multi-frequency detection and the like can be facilitated.
In one implementation of this embodiment, the fulcrum force measurement sensor 102 may include a fulcrum force sensing module, a signal conditioning conversion module, and a 5G millimeter wave terminal transmitting module.
The fulcrum force sensing module is used for collecting vertical force and horizontal force applied to the steel rail fulcrum under the action of wheels. The signal conditioning conversion module is used for processing (such as amplification, filtering, AD conversion and the like) the analog signals corresponding to the vertical force, the horizontal force and the shearing stress, and transmitting the processing result to the 5G millimeter wave terminal sending module. And the 5G millimeter wave terminal sending module is used for sending the processing result to the 5G millimeter wave base station through a wireless communication link.
In a specific embodiment, the fulcrum force measurement sensor 102 may also include a shear force sensor access terminal and a battery powered module. The shear force sensor access terminal is used for receiving the shear stress transmitted by the shear force sensor. The battery power supply module is used for supplying power to the fulcrum force sensing module, the signal conditioning conversion module, the 5G millimeter wave terminal sending module and the like.
In one implementation of the present embodiment, fig. 2b is a schematic structural diagram of the fulcrum force measurement sensor 102 of the present embodiment. As shown in fig. 2b, the fulcrum force sensing module in the fulcrum force measuring sensor 102, the signal conditioning and converting module, the 5G millimeter wave terminal transmitting module and the battery power supply module may be integrally designed. The fulcrum force sensing module, the signal conditioning and converting module, the 5G millimeter wave terminal sending module and the battery power supply module may be integrated in a unified device to form the fulcrum force measuring sensor 102.
In another implementation of the present embodiment, fig. 2c is another schematic structural diagram of the fulcrum force measurement sensor 102 in the present embodiment. As shown in fig. 2c, the fulcrum force sensing module in the fulcrum force measuring sensor 102, the signal conditioning and converting module, the 5G millimeter wave terminal transmitting module and the battery power supply module may be designed separately. The signal conditioning conversion module, the 5G millimeter wave terminal transmitting module and the battery power supply module may be integrated in one device, and the fulcrum force sensing module may be separately integrated in another device, where the two devices form the fulcrum force measuring sensor 102.
According to the technical scheme, the image recognition equipment is deployed in the railway rolling stock performance detection system, so that effective tracking, multi-frequency detection comprehensive evaluation and the like of the railway rolling stock can be realized; secondly, through the fulcrum force sensing module, the signal conditioning conversion module and the 5G millimeter wave terminal sending module which are arranged in the fulcrum force measuring sensor, the anti-interference capability of the signal transmission process and the reliability of the transmission result can be improved, the layout workload of signal cables on a track is reduced, the running risk of rail locomotives is reduced, and the safety of a detection system and the convenience of installation are improved.
Example III
Fig. 3 is a flowchart of a method for detecting performance of a rail vehicle according to a third embodiment of the present invention, where the method may be performed by a data analysis device in a rail vehicle performance detection system, and the method specifically includes the following steps:
step 310, receiving shearing stress of the steel rail under the action of the wheels and vertical force and horizontal force of the steel rail pivot under the action of the wheels, which are sent by the 5G millimeter wave base station.
And 320, calculating an analysis model according to preset parameters, and determining the operation parameters corresponding to the rail locomotive according to the shear stress, the vertical force and the horizontal force.
In this embodiment, the operating parameters may include dynamic parameters corresponding to rail locomotives, hunting wavelengths, impact forces and frequencies, wheel speeds, wheel weights, gross weights, and the like.
And 330, detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive through a preset performance detection model.
In this embodiment, after the above operation parameters are obtained, a performance detection model constructed in advance may be used to evaluate the operation performance (or operation quality) of the rail locomotive according to the operation parameters.
According to the technical scheme, the data analysis equipment is used for receiving the shearing stress of the steel rail under the action of the wheels and the vertical force and the horizontal force of the steel rail fulcrum under the action of the wheels, which are sent by the 5G millimeter wave base station, and according to the preset parameter calculation analysis model, the operation parameters corresponding to the rail locomotive are determined according to the shearing stress, the vertical force and the horizontal force, and the operation performance of the rail locomotive is detected according to the operation parameters corresponding to the rail locomotive through the preset performance detection model, so that the operation performance of the rail locomotive can be evaluated in real time, and the accuracy of the performance detection result of the rail locomotive is improved.
On the basis of the embodiment, the operation parameters comprise impact force, frequency, wheel speed and wheel weight corresponding to the rail locomotive; detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps: and determining at least one tread damage degree index value corresponding to the rail locomotive according to the impact force, the frequency, the wheel speed and the wheel weight corresponding to the rail locomotive by a preset wheel tread damage judging model.
The running parameters comprise wheel track dynamic parameters, hunting destabilization wavelength, speed and total weight corresponding to the rail locomotive; detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps: and determining a corresponding hunting state score of the rail locomotive according to the wheel track dynamic parameters, the hunting instability wavelength, the speed and the total weight corresponding to the rail locomotive through a preset hunting instability judging model.
The operation parameters comprise the corresponding wheel speed, wheel weight and total weight of the rail locomotive; detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps: and determining overload index values and unbalanced load index values corresponding to the rail locomotive according to the wheel speeds, the wheel weights and the total weights corresponding to the rail locomotive through a preset overload and unbalanced load judging model.
Example IV
Fig. 4 shows a schematic diagram of the structure of a data analysis device 10 that may be used to implement an embodiment of the present invention. The data analysis device is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The data analysis device may also represent various forms of mobile apparatus, such as personal digital processing, cellular telephones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the data analysis device 10 includes at least one processor 11, and a memory such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the data analysis device 10 can also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
A plurality of components in the data analysis device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the data analysis device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having 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 specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as a rail locomotive vehicle performance detection method.
In some embodiments, the rail vehicle performance detection method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the data analysis device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the rail vehicle performance detection method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the rail locomotive vehicle performance detection method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may 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. The computer readable storage medium may 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, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, 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.
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 a user; and a keyboard and pointing device (e.g., a mouse or a trackball) through which a user can provide input to the data analysis device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background 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 background, 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: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically 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 called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The rail locomotive vehicle performance detection system is characterized by comprising a plurality of shear force sensors, a plurality of fulcrum force measurement sensors, data analysis equipment and a 5G millimeter wave base station;
the shear force sensor is used for collecting the shear stress of the steel rail under the action of the wheels and transmitting the shear stress to the fulcrum force measuring sensor;
the fulcrum force measuring sensor is used for acquiring vertical force and horizontal force applied to the steel rail fulcrum under the action of the wheels and transmitting the shearing stress, the vertical force and the horizontal force to the 5G millimeter wave base station in a wireless communication mode;
the 5G millimeter wave base station is used for transmitting the shearing stress, the vertical force and the horizontal force to data analysis equipment; the data analysis equipment is used for determining the operation parameters of the rail locomotive according to the shearing stress, the vertical force and the horizontal force and detecting the operation performance of the rail locomotive according to the operation parameters.
2. The railroad car performance detection system of claim 1, wherein the shear force sensor is disposed in a rail center and axle location at a sleeper box center; the fulcrum force measuring sensor is deployed at the sleeper fulcrum position.
3. The railroad rolling stock performance detection system of claim 1, wherein the system further comprises an image recognition device;
the image recognition equipment is used for recognizing the identification information of the rail locomotive and sending the identification information to the data analysis equipment;
the data analysis equipment is also used for establishing a mapping relation between the identification information and the railway locomotive vehicle performance detection result.
4. The rail locomotive vehicle performance detection system of claim 1, wherein the fulcrum force measurement sensor comprises a fulcrum force sensing module, a signal conditioning conversion module, and a 5G millimeter wave terminal transmission module;
the fulcrum force sensing module is used for collecting vertical force and horizontal force applied to the steel rail fulcrum under the action of wheels;
the signal conditioning conversion module is used for processing analog signals corresponding to the vertical force, the horizontal force and the shearing stress and transmitting the processing result to the 5G millimeter wave terminal sending module;
and the 5G millimeter wave terminal sending module is used for sending the processing result to the 5G millimeter wave base station through a wireless communication link.
5. A method for detecting the performance of a rail vehicle, applied to the data analysis apparatus according to any one of claims 1 to 4, comprising:
receiving shearing stress of a steel rail under the action of wheels and vertical force and horizontal force of a steel rail fulcrum under the action of wheels, which are sent by a 5G millimeter wave base station;
according to a preset parameter calculation analysis model, determining the corresponding operation parameters of the rail locomotive according to the shear stress, the vertical force and the horizontal force;
and detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive through a preset performance detection model.
6. The method of claim 5, wherein the operating parameters include impact force, frequency, wheel speed, and wheel weight for a rail locomotive vehicle;
detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps:
and determining at least one tread damage degree index value corresponding to the rail locomotive according to the impact force, the frequency, the wheel speed and the wheel weight corresponding to the rail locomotive by a preset wheel tread damage judging model.
7. The method of claim 5, wherein the operating parameters include a corresponding wheeltrack dynamics parameter, a hunting destabilization wavelength, speed, and gross weight of the rail locomotive;
detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps:
and determining a corresponding hunting state score of the rail locomotive according to the wheel track dynamic parameters, the hunting instability wavelength, the speed and the total weight corresponding to the rail locomotive through a preset hunting instability judging model.
8. The method of claim 5, wherein the operating parameters include a wheel speed, a wheel weight, and a gross weight for the rail locomotive vehicle;
detecting the running performance of the rail locomotive according to the running parameters corresponding to the rail locomotive by a preset performance detection model, wherein the method comprises the following steps:
and determining overload index values and unbalanced load index values corresponding to the rail locomotive according to the wheel speeds, the wheel weights and the total weights corresponding to the rail locomotive through a preset overload and unbalanced load judging model.
9. A data analysis device, comprising:
one or more processors;
a storage means for storing one or more programs;
the rail vehicle performance detection method of any one of claims 5-8 when the one or more programs are executed by the one or more processors, such that the one or more processors execute the programs.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements a rail vehicle performance detection method according to any one of claims 5-8.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310822235.8A CN116593191A (en) | 2023-07-05 | 2023-07-05 | Rail locomotive vehicle performance detection system, detection method, detection equipment and medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310822235.8A CN116593191A (en) | 2023-07-05 | 2023-07-05 | Rail locomotive vehicle performance detection system, detection method, detection equipment and medium |
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| CN202310822235.8A Pending CN116593191A (en) | 2023-07-05 | 2023-07-05 | Rail locomotive vehicle performance detection system, detection method, detection equipment and medium |
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