System for detecting state of electric service equipment component of motor train unit and detection method

Abstract

The invention discloses a system and method for detecting the component state of electric service equipment of a motor train unit, and the system comprises rail side data collection equipment and rail side information processing cabinet equipment which are connected through a data Ethernet equipment power supply control line. The rail side information processing cabinet equipment is connected with a database, the database is connected with a system application server, the system application server is connected with a local area network switch, the local area network switch is connected with a cloud data transmission platform and a management terminal, the cloud data transmission platform is used for uploading data to a cloud server, and the management terminal is connected with the cloud server. And the management terminal is used for integrating information and managing and monitoring the motor train unit. Through the bottom in-cabinet detection module, the bottom out-rail detection module, the TCR antenna detection module, the side detection module, the train number image recognition module and the train roof detection module, all-directional image acquisition of the appearance of the bullet train can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of electric train electrical equipment detection, and in particular to a system and a detection method for detecting the status of components of electric train electrical equipment. Background Art

[0002] In the rail transit sector, the operating status of EMU electrical equipment is directly related to train safety and operational efficiency. Traditional electrical equipment inspection methods rely primarily on manual inspections or single-dimensional sensor monitoring. This approach is relatively inefficient, leading to the emergence of new inspection systems and methods on the market.

[0003] For example, the invention patent application with publication number CN110562305B discloses an intelligent detection system for EMU electrical onboard equipment, including multiple detection base stations, a data processing center and multiple detection subsystems. Each detection base station completes the detection and information collection of the corresponding electrical onboard equipment, such as the functional test, performance indicators and appearance of the electrical onboard equipment, and transmits the collected detection information to the data processing center. The data processing center is responsible for centralized processing and storage of the data sent back by each detection base station, and provides detection information to each detection subsystem for special analysis and comprehensive analysis. Each detection subsystem performs special analysis on the detection data, alarms in the event of equipment performance degradation or functional abnormality, and generates a detection report to remind electrical maintenance personnel to handle it, so as to ensure the reliable use of electrical onboard equipment, ensure driving safety and achieve the purpose of improving quality and efficiency.

[0004] The intelligent detection system provided by the aforementioned patent primarily collects information about EMUs through multiple detection base stations, a data processing center, and multiple detection subsystems. However, existing intelligent detection systems fail to fully cover the EMU's exterior, resulting in incomplete data collection and low accuracy, making it impossible to accurately determine the EMU's status. Summary of the Invention

[0005] The purpose of the present invention is to provide a system and detection method for detecting the status of electrical equipment components of EMUs, aiming to improve the problem that the existing intelligent detection system cannot achieve comprehensive coverage of the EMU appearance, resulting in incomplete EMU data collection and low accuracy of the collected data, which in turn makes it impossible to accurately judge the EMU status.

[0006] The present invention is achieved in that: In order to achieve the above-mentioned purpose, according to one aspect of the present invention, the present invention provides a system for detecting the status of electrical equipment components of EMUs, including a trackside data acquisition device and a trackside information processing cabinet device, the trackside data acquisition device and the trackside information processing cabinet device are connected via a data Ethernet device power supply control line; the trackside information processing cabinet device is connected to a database, the database is connected to a system application server, the system application server is connected to a local area network switch, the local area network switch is connected to a cloud data transmission platform and a management terminal, the cloud data transmission platform is used to upload data to a cloud server, and the management terminal is used to manage and monitor the entire information and the EMU.

[0007] Preferably, the trackside data acquisition equipment includes a train receiving module, an image acquisition module and a vehicle number recognition module; the train receiving module is responsible for detecting the signal of the arrival of the train to ensure that the equipment starts synchronously, the image acquisition module is used to collect picture data of the appearance of the EMU, and the vehicle number recognition module is used to collect the vehicle number information of the EMU, and the vehicle number recognition module is set as a vehicle number image recognition module; the trackside data acquisition equipment also includes a video monitoring module and a vehicle speed measurement module, the video monitoring module is used to use a camera to perform video monitoring of the EMU, and the vehicle speed measurement module is used to measure the speed of the EMU, and the vehicle speed measurement module uses a laser speed meter.

[0008] Preferably, the image acquisition module wraps three bottom in-rail detection modules, two bottom out-rail detection modules, two TCR antenna detection modules, two side detection modules and one roof detection module; the three bottom in-rail detection modules are buried at the bottom inner side of the rail, a bottom out-rail detection module and a TCR antenna detection module are buried on both sides of the rail, and TCR antennas used in conjunction with the TCR antenna detection modules are provided on both sides of the bottom of the EMU; the two side detection modules are respectively arranged on both sides of the EMU, and the information acquisition ends of the side detection modules are aligned with the EMU; the roof detection module is installed directly above the EMU through a gantry.

[0009] Preferably, the bottom rail inner detection module and the bottom rail outer detection module both use 2D area array imaging components, the TCR antenna detection module uses a 3D imaging component, the side detection module uses a 2K linear array imaging component, and the roof detection module uses a 4K linear array imaging component.

[0010] Preferably, the trackside information processing cabinet equipment includes a system control cabinet, an image acquisition machine, a system lightning protection device, a system power-off protection device, a data wireless transmission device and a remote maintenance device; the system control cabinet is used to control the operation of the entire system, the image acquisition machine is used to acquire images taken by the trackside data acquisition equipment, the system lightning protection device is used to protect the entire system from lightning to prevent lightning from affecting the normal operation of the system, the system power-off protection device is used to power off the system when overcurrent or short circuit problems occur in the system, the data wireless transmission device is used to connect to the management terminal to facilitate wireless transmission of data to the management terminal, and the remote maintenance device is used to use network technology to break through spatial limitations to achieve remote operation, can remotely manage and configure equipment and real-time monitoring and early warning, and can also establish maintenance channels for diagnosis and debugging. It is widely used in many fields, greatly improving operation and maintenance efficiency and reducing costs.

[0011] Preferably, it further includes two concrete foundations, which are connected by a cable box, and side boxes are provided on the concrete foundations, and the vehicle number image recognition module is arranged on the top of one of the side boxes; a caisson is provided in the middle of the cable box, and auxiliary boxes are provided on both sides of the caisson; the three bottom rail in-rail detection modules are arranged side by side on the inside of the caisson, and a bottom rail out-of-rail detection module and a TCR antenna detection module are arranged side by side inside the two auxiliary boxes; the two side detection modules are respectively arranged inside the two side boxes.

[0012] Preferably, the concrete foundation is respectively provided with a high platform and a bottom platform, the high platform is arranged to protrude from the bottom surface, and the bottom platform is buried below the ground, a steel plate is provided on the bottom platform, screws are provided at the corners of the upper surface of the steel plate, and supporting caps are provided on the screws; connecting plates are provided at both ends of the bottom of the cable box, through-holes are provided at the corners of the connecting plates, the through-holes are sleeved on the screws, and pressure caps are provided above the screws, and the pressure caps are pressed tightly on the upper surface of the connecting plates; wire tubes are provided at both ends of the cable box; a handle is provided at the front door of the side box, and a threaded hole is provided at the top of the side box, and heat dissipation holes are symmetrically provided on both sides of the bottom of the side box, a fixing plate is provided at the bottom end of the side box, a plurality of fixing holes are provided on the fixing plate, and a reinforcing plate is provided between the fixing plate and the side box; the side box is fixed to the high platform by bolts passing through the fixing holes.

[0013] Preferably, a shield is provided on the top of the vehicle number image recognition module, a wiring tube is provided at the bottom of the vehicle number image recognition module, a threaded tube is provided at the bottom of the wiring tube, and the threaded tube is connected to the threaded hole; a bayonet is provided on the bottom surface of the caisson, and the caisson and the cable box are connected by bolts, bent pipes are provided on both sides of the bottom side of the caisson, a wire entry hole is provided on the bent pipe, and the wire entry hole is communicated with the caisson; a corner plate is provided at the bottom of the auxiliary box, and the auxiliary box is fixed to the cable box by bolts passing through the corner plate.

[0014] According to a second aspect of the present invention, the present invention provides a detection method for detecting the status of electrical equipment components of an EMU. The specific steps of the detection method are as follows: S100: When the speed measurement module detects that the train enters the detection area at a speed of ≤40 km / h, the trackside data acquisition device is triggered to synchronously capture images using the bottom rail detection module, bottom rail detection module, side detection module, TCR antenna detection module, roof detection module, and vehicle number image recognition module. S200: The image acquisition machine in the trackside information processing cabinet performs noise reduction, geometric correction, and brightness equalization on the acquired original image; S300, the system application server analyzes the pre-processed image using a deep learning algorithm to extract component geometry, appearance defects, and installation status features; S400: Compare the extracted features with a preset standard library to automatically identify and classify structural faults, functional faults, and installation faults; S500: Generate a visual inspection report, mark the fault location and severity level, and issue a fault notification through the management terminal.

[0015] Preferably, in step S500, three levels of warning are divided according to the severity of the fault. The first level warning is an emergency fault, and the maintenance center is immediately notified via text message and sound and light alarm; the second level warning is a major fault, and a maintenance work order is issued within 2 hours; the third level warning is a general fault, which is included in the regular maintenance plan.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention can realize all-round image acquisition of the appearance of the EMU through the bottom cabinet detection module, the bottom rail detection module, the TCR antenna detection module, the side detection module, the vehicle number image recognition module and the roof detection module. By processing the collected images, the status of the EMU can be accurately determined, and the collected data and the determination results can be uploaded to the management terminal and the cloud. This can ensure that the management terminal understands the status of each EMU in real time, and the data can be viewed at any time through the cloud.

[0017] 2. The present invention can stably support various components of the entire monitoring system through the concrete foundation, ensuring the stable operation of various devices and avoiding the equipment tilting due to lack of stable support, which affects the detection accuracy.

[0018] 3. The present invention can guide and protect the cables connecting various devices by setting up a cable box, avoiding the problem that the cables are easily damaged when buried under the rails; it also avoids the problem that the cables are messy and inconvenient to repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a structural block diagram of the detection system of the present invention; Figure 2 It is a block diagram of the layout of the trackside data acquisition equipment of the present invention; Figure 3 This is a structural block diagram of the trackside information processing cabinet equipment and the trackside data acquisition equipment of the present invention; Figure 4 This is a schematic diagram of the installation structure of the trackside data acquisition device of the present invention; Figure 5 It is a schematic diagram of the concrete foundation structure of the present invention; Figure 6 It is a schematic diagram of the three-dimensional structure of the side box of the present invention; Figure 7 It is a structural diagram of the vehicle number image recognition module of the present invention; Figure 8 It is a structural schematic diagram of the cable box of the present invention; Figure 9 It is a structural schematic diagram of the caisson of the present invention; Figure 10 It is a structural schematic diagram of the auxiliary box of the present invention; Figure 11 It is a flowchart of the detection method of the present invention.

[0020] In the figure: 1. Concrete foundation; 11. Platform; 12. Base; 13. Steel plate; 14. Screw; 15. Support cap; 16. Pressure cap; 2. Side box; 21. Handle; 22. Threaded hole; 23. Heat dissipation hole; 24. Fixing plate; 25. Fixing hole; 26. Reinforcement plate; 3. Vehicle number image recognition module; 31. Shield; 32. Wiring pipe; 33. Threaded pipe; 4. Cable box; 41. Connecting plate; 42. Perforation; 43. Threading pipe; 5. Caisson; 51. Bayonet; 52. Bend pipe; 53. Wire entry hole; 6. Auxiliary box; 61. Angle plate. DETAILED DESCRIPTION

[0021] In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connect," "fixed," etc. should be understood broadly. For example, they may refer to fixed connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0022] The following is a further description with reference to the accompanying drawings and specific embodiments: Example 1 like Figure 1The system shown in the figure is used to monitor the status of electrical equipment components on a train. The system includes a trackside data acquisition device and a trackside information processing cabinet. The trackside data acquisition device is used to collect image data from the train. The trackside data acquisition device and the trackside information processing cabinet are connected via a data Ethernet power supply control line, facilitating control of the trackside data acquisition device by the trackside information processing cabinet and data transmission between the trackside data acquisition device and the trackside information processing cabinet. The trackside information processing cabinet is connected to a database that stores various data related to monitoring. The database is connected to a system application server, which uses collected images to determine whether the train is faulty. The system application server is connected to a local area network switch, which is connected to a cloud data transmission platform and a management terminal. The cloud data transmission platform uploads data to a cloud server, and the management terminal manages and monitors the entire information system and the train.

[0023] like Figure 3 As shown, the trackside data acquisition equipment includes a train reception module, an image acquisition module, and a vehicle number recognition module. The train reception module is responsible for detecting train arrival signals and ensuring synchronous equipment startup. The image acquisition module is used to capture image data of the EMU's exterior. The vehicle number recognition module is used to collect vehicle number information of the EMU. The vehicle number recognition module is configured as vehicle number image recognition module 3. The trackside data acquisition equipment also includes a video monitoring module and a speed measurement module. The video monitoring module is used to monitor the EMU using a camera. The speed measurement module is used to measure the EMU's speed. The speed measurement module uses a laser speedometer. Vehicle number image recognition module 3 is installed on the side box 2 and includes a camera with a resolution of 40W, a lens with a focal length of 5mm, an IR805 light source, an object distance of 1000mm, supports a maximum frequency of 312fps, adapts to a speed of 40km / h, and has an IP67 protection level. The imaging quality of vehicle number image recognition module 3 is evaluated using the following formula: in, is the modulation transfer function, is the contrast of the camera output image, is the contrast of the object being measured.

[0024] like Figure 2As shown, the image acquisition module encompasses three bottom in-rail detection modules, two bottom out-rail detection modules, two TCR antenna detection modules, two side detection modules, and one roof detection module. The three bottom in-rail detection modules are embedded in the inner bottom of the rails. A bottom out-rail detection module and a TCR antenna detection module are embedded on either side of the rails. TCR antennas are installed on both sides of the EMU's bottom for use with the TCR antenna detection modules. Two side detection modules are located on either side of the EMU, with their information acquisition terminals aligned with the EMU. The roof detection module is mounted directly above the EMU via a gantry. The bottom in-rail and bottom out-rail detection modules both utilize 2D area array imaging components, while the TCR antenna detection module utilizes a 3D imaging component. The side detection module utilizes a 2K linear array imaging component, and the roof detection module utilizes a 4K linear array imaging component.

[0025] The 2D area array imaging component has a resolution of 500W, a lens focal length of 12mm, uses an LED white light source, an object distance of 1000mm, a working distance of 850-1250mm, a detection accuracy of 0.24-0.36mm, supports a maximum frequency of 24.2fps, adapts to a vehicle speed of 40km / h, and has an IP67 protection level. Detection accuracy is calculated using the following formula: in, is the detection accuracy of the bottom detection unit, is the physical size of a single pixel on the camera sensor, is the object distance, is the focal length of the lens.

[0026] The 2K linear array imaging component has a resolution of 2K, a lens focal length of 16mm, an 808nm light source, an object distance of 1100mm, a working distance of 1000-1200mm, a detection accuracy of 0.43-0.52mm, supports a maximum frequency of 48K, adapts to a vehicle speed of 40km / h, and has an IP67 protection level. The detection accuracy is calculated using the following formula: in, is the detection accuracy of the side detection unit, is the width of a single pixel of the line scan camera sensor, is the object distance, is the focal length of the lens.

[0027] The 3D imaging component includes a camera with a resolution of 40W, a lens focal length of 8mm, a 915nm light source, an object distance of 400mm, a working distance of 300-500mm, a 3D detection accuracy of 1mm, supports a maximum frequency of 312fps, adapts to a vehicle speed of 40KM / H, and has an IP67 protection level; The 3D detection accuracy is calculated using the following formula: in, For 3D detection accuracy, is the pixel size, is the object distance, is the focal length of the lens, is the laser line width, is the magnification.

[0028] The 4K linear array imaging component has a lens focal length of 20mm, uses an 808nm light source, has an object distance of 2300mm, a working distance of 2000-2800mm, a detection accuracy of 0.69-0.97mm, supports a maximum frequency of 24K, adapts to a vehicle speed of 40km / h, and has an IP67 protection level. Detection accuracy is calculated using the following formula: in, is the detection accuracy of the top detection unit, is the width of a single pixel of the line scan camera sensor, is the object distance, is the focal length of the lens.

[0029] like Figure 3 As shown, the trackside information processing cabinet equipment includes a system control cabinet, an image acquisition machine, a system lightning protection device, a system power-off protection device, a data wireless transmission device and a remote maintenance device; the system control cabinet is used to control the operation of the entire system, the image acquisition machine is used to acquire images taken by the trackside data acquisition equipment, the system lightning protection device is used to protect the entire system from lightning to prevent lightning from affecting the normal operation of the system, the system power-off protection device is used to power off the system when overcurrent or short circuit problems occur in the system, the data wireless transmission device is used to connect to the management terminal to facilitate wireless transmission of data to the management terminal, and the remote maintenance device is used to use network technology to break through space limitations to achieve remote operation, remote management and configuration of equipment and real-time monitoring and early warning, and to establish maintenance channels for diagnosis and debugging. It is widely used in many fields, greatly improving operation and maintenance efficiency and reducing costs.

[0030] Example 2 like Figure 1The system shown in the figure is used to monitor the status of electrical equipment components on a train. The system includes a trackside data acquisition device and a trackside information processing cabinet. The trackside data acquisition device is used to collect image data from the train. The trackside data acquisition device and the trackside information processing cabinet are connected via a data Ethernet power supply control line, facilitating control of the trackside data acquisition device by the trackside information processing cabinet and data transmission between the trackside data acquisition device and the trackside information processing cabinet. The trackside information processing cabinet is connected to a database that stores various data related to monitoring. The database is connected to a system application server, which uses collected images to determine whether the train is faulty. The system application server is connected to a local area network switch, which is connected to a cloud data transmission platform and a management terminal. The cloud data transmission platform uploads data to a cloud server, and the management terminal manages and monitors the entire information system and the train.

[0031] like Figure 3 As shown, the trackside data acquisition equipment includes a train reception module, an image acquisition module, and a vehicle number recognition module. The train reception module is responsible for detecting train arrival signals and ensuring synchronous equipment startup. The image acquisition module is used to capture image data of the EMU's exterior. The vehicle number recognition module is used to collect vehicle number information of the EMU. The vehicle number recognition module is configured as vehicle number image recognition module 3. The trackside data acquisition equipment also includes a video monitoring module and a speed measurement module. The video monitoring module is used to monitor the EMU using a camera. The speed measurement module is used to measure the EMU's speed. The speed measurement module uses a laser speedometer. Vehicle number image recognition module 3 is installed on the side box 2 and includes a camera with a resolution of 40W, a lens with a focal length of 5mm, an IR805 light source, an object distance of 1000mm, supports a maximum frequency of 312fps, adapts to a speed of 40km / h, and has an IP67 protection level. The imaging quality of vehicle number image recognition module 3 is evaluated using the following formula: in, is the modulation transfer function, is the contrast of the camera output image, is the contrast of the object being measured.

[0032] like Figure 2As shown, the image acquisition module encompasses three bottom in-rail detection modules, two bottom out-rail detection modules, two TCR antenna detection modules, two side detection modules, and one roof detection module. The three bottom in-rail detection modules are embedded in the inner bottom of the rails. A bottom out-rail detection module and a TCR antenna detection module are embedded on either side of the rails. TCR antennas are installed on both sides of the EMU's bottom for use with the TCR antenna detection modules. Two side detection modules are located on either side of the EMU, with their information acquisition terminals aligned with the EMU. The roof detection module is mounted directly above the EMU via a gantry. The bottom in-rail and bottom out-rail detection modules both utilize 2D area array imaging components, while the TCR antenna detection module utilizes a 3D imaging component. The side detection module utilizes a 2K linear array imaging component, and the roof detection module utilizes a 4K linear array imaging component.

[0033] The 2D area array imaging component has a resolution of 500W, a lens focal length of 12mm, uses an LED white light source, an object distance of 1000mm, a working distance of 850-1250mm, a detection accuracy of 0.24-0.36mm, supports a maximum frequency of 24.2fps, adapts to a vehicle speed of 40km / h, and has an IP67 protection level. Detection accuracy is calculated using the following formula: in, is the detection accuracy of the bottom detection unit, is the physical size of a single pixel on the camera sensor, is the object distance, is the focal length of the lens.

[0034] The 2K linear array imaging component has a resolution of 2K, a lens focal length of 16mm, an 808nm light source, an object distance of 1100mm, a working distance of 1000-1200mm, a detection accuracy of 0.43-0.52mm, supports a maximum frequency of 48K, adapts to a vehicle speed of 40km / h, and has an IP67 protection level. The detection accuracy is calculated using the following formula: in, is the detection accuracy of the side detection unit, is the width of a single pixel of the line scan camera sensor, is the object distance, is the focal length of the lens.

[0035] The 3D imaging component includes a camera with a resolution of 40W, a lens focal length of 8mm, a 915nm light source, an object distance of 400mm, a working distance of 300-500mm, a 3D detection accuracy of 1mm, supports a maximum frequency of 312fps, adapts to a vehicle speed of 40KM / H, and has an IP67 protection level; The 3D detection accuracy is calculated using the following formula: in, For 3D detection accuracy, is the pixel size, is the object distance, is the focal length of the lens, is the laser line width, is the magnification.

[0036] The 4K linear array imaging component has a lens focal length of 20mm, uses an 808nm light source, has an object distance of 2300mm, a working distance of 2000-2800mm, a detection accuracy of 0.69-0.97mm, supports a maximum frequency of 24K, adapts to a vehicle speed of 40km / h, and has an IP67 protection level. Detection accuracy is calculated using the following formula: in, is the detection accuracy of the top detection unit, is the width of a single pixel of the line scan camera sensor, is the object distance, is the focal length of the lens.

[0037] like Figure 3 As shown, the trackside information processing cabinet equipment includes a system control cabinet, an image acquisition machine, a system lightning protection device, a system power-off protection device, a data wireless transmission device and a remote maintenance device; the system control cabinet is used to control the operation of the entire system, the image acquisition machine is used to acquire images taken by the trackside data acquisition equipment, the system lightning protection device is used to protect the entire system from lightning to prevent lightning from affecting the normal operation of the system, the system power-off protection device is used to power off the system when overcurrent or short circuit problems occur in the system, the data wireless transmission device is used to connect to the management terminal to facilitate wireless transmission of data to the management terminal, and the remote maintenance device is used to use network technology to break through space limitations to achieve remote operation, remote management and configuration of equipment and real-time monitoring and early warning, and to establish maintenance channels for diagnosis and debugging. It is widely used in many fields, greatly improving operation and maintenance efficiency and reducing costs.

[0038] like Figure 2 and Figure 4As shown, it also includes two concrete foundations 1, which are connected by a cable box 44. The concrete foundation 1 is convenient for supporting various components and ensuring the stable use of each component. A side box 2 is provided on the concrete foundation 1, and the side box 2 is convenient for installing the side detection module. And the vehicle number image recognition module 3 is set on the top of one of the side boxes 2 for detecting the vehicle number. A caisson 5 is provided in the middle of the cable box 44, and auxiliary boxes 6 are provided on both sides of the caisson 5; three bottom rail detection modules are arranged side by side on the inside of the caisson 5, and a bottom rail detection module and a TCR antenna detection module are arranged side by side inside the two auxiliary boxes 6; the two side detection modules are respectively arranged inside the two side boxes 2. This structure can effectively protect each detection module and ensure the stable use of the detection module.

[0039] like Figure 5 、 Figure 6 and Figure 8 As shown, a high platform 11 and a base 12 are provided on the concrete foundation 1. The high platform 11 is protruding from the bottom surface, while the base 12 is buried below the ground. The high platform 11 is used to support the side box 2, while the base 12 is used to support the cable box 44. A steel plate 13 is provided on the base 12, and screws 14 are provided at the corners of the upper surface of the steel plate 13. The screws 14 are provided with supporting caps 15. Connecting plates 41 are provided at both ends of the bottom of the cable box 44. The connecting plates 41 are provided with through holes 42 at the corners. The through holes 42 are sleeved on the screws 14, and a pressure cap 16 is provided above the screws 14. The pressure cap 16 is pressed tightly against the upper surface of the connecting plates 41. This structure facilitates the stable installation of the cable box 44 on the base 12, thereby ensuring the stable use of the cable box 44. A wire threading tube 43 is provided at both ends of the cable box 44. The wire threading tube 43 facilitates the insertion of cables into the interior of the cable box 44. The front door of the side box 2 is equipped with a handle 21 for convenient gripping and opening and closing. The top of the side box 2 is provided with a threaded hole 22 for installing the vehicle license plate image recognition module 3. Symmetrical cooling holes 23 are located on both sides of the bottom of the side box 2 to dissipate heat. A fixing plate 24 is located at the bottom of the side box 2, with multiple fixing holes 25 defined in it. A reinforcement plate 26 is provided between the fixing plate 24 and the side box 2. The side box 2 is secured to the platform 11 with bolts passing through the fixing holes 25, ensuring a stable installation on the platform 11.

[0040] like Figure 7 、 Figure 9 and Figure 10As shown, the top of the vehicle number image recognition module 3 is provided with a shield 31, the bottom of the vehicle number image recognition module 3 is provided with a wiring tube 32, the bottom of the wiring tube 32 is provided with a threaded tube 33, and the threaded tube 33 is connected to the threaded hole 22; this structure facilitates the stable installation of the vehicle number image recognition module 3 on the platform 11, and facilitates the stable use of the vehicle number image recognition module 3. A bayonet 51 is provided on the bottom surface of the caisson 5, and the caisson 5 and the cable box 44 are connected by bolts, which facilitates the stable installation of the caisson 5. Bend pipes 52 are provided on both sides of the bottom side of the caisson 5, and a wire entry hole 53 is provided on the bend pipe 52, which is in communication with the caisson 5; it is convenient to pass external cables into the interior of the caisson 5. A corner plate 61 is provided at the bottom of the auxiliary box 6, and the auxiliary box 6 is fixed to the cable box 44 by bolts passing through the corner plate 61.

[0041] Example 3 like Figure 11 As shown, a detection method for detecting the status of electrical equipment components of an EMU is provided. The specific steps of the detection method are as follows: S100. When the speed measurement module detects that a train enters the detection area at a speed of ≤40 km / h, the trackside data acquisition device is triggered to synchronously capture images using the bottom rail detection module, bottom rail detection module, side detection module, TCR antenna detection module, roof detection module, and vehicle number image recognition module 3. During the image acquisition process, the exposure time of the camera of each imaging component is calculated using the following formula: in, is the exposure time, is the object's speed, To allow motion blur, is the pixel size.

[0042] S200, the image acquisition machine in the trackside information processing cabinet, performs noise reduction, geometric correction, and brightness equalization on the captured raw images. This processing eliminates time deviations from multi-camera acquisitions using a spatiotemporal synchronization algorithm, uses median filtering and histogram equalization to address image noise and brightness unevenness, and performs geometric correction using camera calibration parameters to restore the true dimensions of the components. The spatiotemporal synchronization algorithm is implemented using the following formula: in, is the time synchronization value, is the base time, is the device distance, is the speed of light, The device clock offset.

[0043] S300. The system application server analyzes the preprocessed image using a deep learning algorithm to extract component geometry, appearance defects, and installation status features. The deep learning algorithm includes a convolutional neural network for extracting component geometry, appearance defects, and installation status features. The feature extraction process of the convolutional neural network is expressed by the following formula: in, For the The feature map of the layer, is the activation function, For the The convolution kernel weight of the layer, * represents the convolution operation, For the The feature map of the layer, is the bias term.

[0044] S400: Compare the extracted features with a preset standard library to achieve automatic identification and classification of structural faults, functional faults, and installation faults; the preset standard library includes standard values ​​of component geometric dimensions, appearance defect judgment thresholds, and installation status specification parameters; the confidence level of fault identification is calculated using the following formula: in, is the confidence level of fault identification, is the feature matching degree, is the characteristic deviation.

[0045] S500 generates a visual inspection report, marking the fault location and severity level, and issues a fault notification through the management terminal. Three levels of warning are divided according to the severity of the fault. Level 1 warning is an emergency fault, which is immediately notified to the maintenance center via SMS and audible and visual alarms. Level 2 warning is a major fault, and a maintenance work order is issued within 2 hours. Level 3 warning is a general fault, which is included in the regular maintenance plan. The severity of the fault is evaluated using the following formula: in, is the severity of the fault, 、 、 is the weight coefficient, and , is the fault impact, is the failure rate, The difficulty of troubleshooting.

[0046] Working Principle: During installation, two concrete foundations 1 are first cast at the pre-set locations. Once the concrete foundations 1 have fully solidified, three bottom rail detection modules are placed side by side inside the caisson 5. A bottom rail detection module and a TCR antenna detection module are placed side by side inside each of the two auxiliary boxes 6. Two side detection modules are then installed inside the two side boxes 2. The side boxes 2 are then mounted on the top surface of the concrete foundation 1. A cable box 44 is erected between the two bases 12. The cables are passed through the cable box 44 and the corresponding wire ends are led out from the cable box 44. The caisson 5 and auxiliary boxes 6 are then mounted on the cable box 44 and wired. The roof detection module is then installed via the gantry, and the vehicle number image recognition module 3 is mounted on top of one of the side boxes 2. The trackside information processing cabinet, database, system application server, and LAN switch are then installed. The LAN switch is then used to wirelessly connect to the cloud data transmission platform and management terminal. The entire system is then debugged to ensure proper operation. During inspection, when a speed measurement module (such as a laser speedometer) detects a train entering the inspection area at a speed of 40 km / h or less, the bottom rail detection module, bottom rail detection module, side detection module, TCR antenna detection module, roof detection module, and vehicle number image recognition module simultaneously capture images. The bottom detection unit uses five 2D area array imaging modules to acquire high-definition color images. The side detection unit uses 2K linear array imaging modules to capture side images. The TCR antenna detection unit uses 3D imaging modules to measure antenna installation height. The top detection unit uses 4K linear array imaging modules to capture images of the roof and pantograph. The vehicle number recognition unit simultaneously captures vehicle number information. After all image data is transmitted to the trackside information processing cabinet, the image information acquisition equipment performs pre-processing such as noise reduction, geometric correction, and brightness equalization. The system application server then uses deep learning algorithms (such as convolutional neural networks) to extract component geometric dimensions, appearance defects, and installation status. These features are then compared with a pre-set standard library to automatically identify and classify structural, functional, and installation faults. Ultimately, the system generates a visual report based on the severity of the fault, issues an alert through the management terminal, and connects to the maintenance system. Historical data is also stored in a database for trend analysis. The entire process relies on a spatiotemporal synchronization algorithm to ensure the consistency of multi-camera data. Precise optical design and calculations (such as the detection accuracy calculation formula) guarantee detection accuracy, forming a closed-loop management system of "detection-diagnosis-warning-maintenance."

[0047] To sum up, compared with the existing technology, the present application can realize all-round image acquisition of the appearance of the EMU through the bottom cabinet detection module, the bottom rail detection module, the TCR antenna detection module, the side detection module, the vehicle number image recognition module 3 and the roof detection module, and by processing the collected images, the status of the EMU can be accurately determined, and the collected data and the judgment results can be uploaded to the management terminal and the cloud, so as to ensure that the management terminal understands the status of each EMU in real time, and the data can be viewed at any time through the cloud.

[0048] The above is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A system for detecting the status of components of electric equipment of a train, characterized in that: It includes trackside data acquisition equipment and trackside information processing cabinet equipment, which are connected via a data Ethernet equipment power supply control line; the trackside information processing cabinet equipment is connected to a database, the database is connected to a system application server, the system application server is connected to a local area network switch, the local area network switch is connected to a cloud data transmission platform and a management terminal, the cloud data transmission platform is used to upload data to the cloud server, and the management terminal is used to integrate information and manage and monitor the EMU.

2. A system for detecting the status of components of electric equipment of a train set according to claim 1, characterized in that: The trackside data acquisition equipment includes a train receiving module, an image acquisition module and a vehicle number recognition module; the train receiving module is responsible for detecting the signal of the train arrival and ensuring the synchronous start of the equipment, the image acquisition module is used to collect image data of the appearance of the EMU, and the vehicle number recognition module is used to collect the vehicle number information of the EMU, and the vehicle number recognition module is set as a vehicle number image recognition module (3); the trackside data acquisition equipment also includes a video monitoring module and a vehicle speed measurement module, the video monitoring module is used to use a camera to perform video monitoring of the EMU, and the vehicle speed measurement module is used to measure the speed of the EMU, and the vehicle speed measurement module uses a laser speed meter.

3. A system for detecting the status of components of electric equipment of a train set according to claim 2, characterized in that: The image acquisition module wraps three bottom in-rail detection modules, two bottom out-rail detection modules, two TCR antenna detection modules, two side detection modules and one roof detection module. The three bottom in-rail detection modules are buried at the bottom inner side of the rail, and a bottom out-rail detection module and a TCR antenna detection module are buried on both sides of the rail respectively. TCR antennas used in conjunction with the TCR antenna detection modules are provided on both sides of the bottom of the EMU; the two side detection modules are respectively arranged on both sides of the EMU, and the information acquisition ends of the side detection modules are aligned with the EMU; the roof detection module is installed directly above the EMU through a gantry.

4. A system for detecting the status of components of electric equipment of a train set according to claim 3, characterized in that: The bottom rail in-detection module and the bottom rail out-detection module both use 2D area array imaging components, the TCR antenna detection module uses a 3D imaging component, the side detection module uses a 2K linear array imaging component, and the roof detection module uses a 4K linear array imaging component.

5. The system for detecting the status of components of electric equipment of a train set according to claim 1, characterized in that: The trackside information processing cabinet equipment includes a system control cabinet, an image acquisition machine, a system lightning protection device, a system power-off protection device, a data wireless transmission device and a remote maintenance device; the system control cabinet is used to control the operation of the entire system, the image acquisition machine is used to acquire images taken by the trackside data acquisition equipment, the system lightning protection device is used to protect the entire system from lightning to prevent lightning from affecting the normal operation of the system, the system power-off protection device is used to power off the system when overcurrent or short circuit problems occur in the system, the data wireless transmission device is used to connect to the management terminal to facilitate wireless transmission of data to the management terminal, and the remote maintenance device is used to use network technology to break through spatial limitations to achieve remote operation, can remotely manage and configure equipment and real-time monitoring and early warning, and can also establish maintenance channels for diagnosis and debugging. It is widely used in many fields, greatly improving operation and maintenance efficiency and reducing costs.

6. The system for detecting the status of components of electric equipment of a train set according to claim 3, characterized in that: The vehicle further comprises two concrete foundations (1), the two concrete foundations (1) being connected via a cable box (4), a side box (2) being provided on the concrete foundation (1), and the vehicle number image recognition module (3) being arranged on the top of one of the side boxes (2); a caisson (5) being provided in the middle of the cable box (4), and auxiliary boxes (6) being provided on both sides of the caisson (5); three bottom rail in-line detection modules being arranged side by side inside the caisson (5), and a bottom rail out-line detection module and a TCR antenna detection module being arranged side by side inside each of the two auxiliary boxes (6); and two side detection modules being arranged inside the two side boxes (2), respectively.

7. A system for detecting the status of components of electric equipment of a train set according to claim 6, characterized in that: The concrete foundation (1) is provided with a high platform (11) and a bottom platform (12), the high platform (11) is provided protruding from the bottom surface, and the bottom platform (12) is buried below the ground. A steel plate (13) is provided on the bottom platform (12), and screws (14) are provided at the corners of the upper surface of the steel plate (13), and supporting caps (15) are provided on the screws (14); both ends of the bottom of the cable box (4) are provided with connecting plates (41), and the corners of the connecting plates (41) are provided with through holes (42), and the through holes (42) are sleeved on the screws (14), and a pressure cap (16) is provided above the screws (14). The pressing cap (16) is pressed tightly against the upper surface of the connecting plate (41); both ends of the cable box (4) are provided with a threading tube (43); a handle (21) is provided at the front door of the side box (2), and a threaded hole (22) is provided at the top of the side box (2); heat dissipation holes (23) are symmetrically provided on both sides of the bottom of the side box (2); a fixing plate (24) is provided at the bottom end of the side box (2), and a plurality of fixing holes (25) are provided on the fixing plate (24); a reinforcing plate (26) is provided between the fixing plate (24) and the side box (2); the side box (2) is fixed to the platform (11) by bolts passing through the fixing holes (25).

8. A system for detecting the status of components of electric equipment of a train set according to claim 7, characterized in that: The top of the vehicle number image recognition module (3) is provided with a shield (31), the bottom of the vehicle number image recognition module (3) is provided with a wiring tube (32), the bottom of the wiring tube (32) is provided with a threaded tube (33), and the threaded tube (33) is connected to the threaded hole (22); the bottom surface of the caisson (5) is provided with a bayonet (51), and the caisson (5) and the cable box (4) are connected by bolts, and the bottom sides of the caisson (5) are provided with bent pipes (52), and the bent pipes (52) are provided with wire inlet holes (53), and the wire inlet holes (53) are communicated with the caisson (5); the bottom of the auxiliary box (6) is provided with an angle plate (61), and the auxiliary box (6) is fixed to the cable box (4) by bolts passing through the angle plate (61).

9. A method for detecting the status of components of electrical equipment on a train, using the system for detecting the status of components of electrical equipment on a train according to claim 3, characterized in that: The specific steps of this detection method are as follows: S100, when the speed measurement module detects that the train enters the detection area at a speed of ≤40km / h, the bottom rail detection module, bottom rail detection module, side detection module, TCR antenna detection module, roof detection module and vehicle number image recognition module (3) of the trackside data acquisition equipment are triggered to synchronously collect images; S200: The image acquisition machine in the trackside information processing cabinet performs noise reduction, geometric correction, and brightness equalization on the acquired original image; S300, the system application server analyzes the pre-processed image using a deep learning algorithm to extract component geometry, appearance defects, and installation status features; S400: Compare the extracted features with a preset standard library to automatically identify and classify structural faults, functional faults, and installation faults; S500: Generate a visual inspection report, mark the fault location and severity level, and issue a fault notification through the management terminal.

10. A system and method for detecting the status of components of electric equipment of a train set according to claim 9, characterized in that: In step S500, three levels of warning are divided according to the severity of the fault. The first level warning is an emergency fault, and the maintenance center is immediately notified via SMS and sound and light alarms; the second level warning is a major fault, and a maintenance work order is issued within 2 hours; The third-level warning is a general fault and is included in the regular maintenance plan.

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