Planar laser diffuse reflection detection method applied to rail transit

Abstract

The invention discloses a planar laser diffuse reflection detection method applied to rail transit. The application method comprises the following steps: step 1, acquiring a system image, introducing a module, and selecting a model for a hardware part of an image acquisition module; 2, a camera labeling experiment is completed based on Matlab software, and the conversion relation between pixel points and space points is obtained; 3, obtaining a continuous sliding plate abrasion edge by using a Canny algorithm, and obtaining a crack skeleton; 4, based on the crack skeleton in the step 3, learning and identifying the image features of the crack skeleton based on a support vector machine, and then converting the image features into electric signals; and 5, based on the electric signal in the step 4, converting the electric signal into a digital image signal through A / D (analog-to-digital conversion) conversion, sending the digital image signal to a digital signal processing chip (DSP), processing the image signal, packaging the image signal into a data packet, and directly transmitting the data packet to a judgment processing center, so that a constructed comprehensive monitoring and fault early warning system provides a decision basis for maintenance personnel.

Description

Technical Field

[0001] The present invention relates to the field of reflection detection methods, in particular to a planar laser diffuse reflection detection method for rail transit applications. Background Art

[0002] Based on the "technical regulations" of the train itself, it is interconnected in terms of technical requirements, system composition, communication form, etc., to ensure reliable operation, maximize utilization and guarantee efficiency within a limited service life to achieve maximum safety.

[0003] Based on this innovative project, a new type of anti-interference and anti-electromagnetic composite board is used, the inner layer is a strong electric field composite application board, and the surface is coated with an unsaturated resin composition. The planar laser reflection method, the external material of this method has a good shielding effect on the electromagnetic interference of the bow net offline arc, and the bow net arc radiation that reaches the ground through the reinforced concrete is very small, and has little impact on the ground equipment; for the protection against electromagnetic interference, there are shielding, grounding, filtering and other methods. When it comes to specific problems, there are also different devices for protection, which can effectively prevent electronic interference of on-board equipment and surrounding sensitive electronic components. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the above technical defects.

[0005] In order to solve the above problems, the technical solution of the present invention is: a plane laser diffuse reflection detection method for rail transit application, the use method comprises the following steps:

[0006] Step 1: Collect system images, introduce modules, and select the hardware of image acquisition module;

[0007] Step 2: Complete the camera annotation experiment based on Matlab software to obtain the conversion relationship between pixel points and spatial points, perform image filtering and image enhancement on the skateboard wear graphics and skateboard crack graphics collected by the graphics acquisition module, and obtain a skateboard image with higher quality and stronger edge features;

[0008] Step 3: Using the Canny algorithm, the continuous wear edge of the slide is obtained. When extracting crack features, the crack image is preprocessed to obtain a binary crack image, and then the crack is refined to obtain a crack skeleton.

[0009] Step 4: Based on the crack skeleton in step 3, the image features of the crack skeleton are learned and recognized based on the support vector machine, and the length of the crack of the skateboard is calculated. The surface of the observed object is projected onto the surface of the image sensor after generating an optical image through the lens, and then converted into an electrical signal;

[0010] Step 5: Based on the electrical signal in step 4, it is converted into a digital image signal through A / D (analog-to-digital conversion), and then sent to the digital signal processing chip (DSP) to process the image signal and package it into a data packet and directly transmit it to the judgment processing center. The judgment processing center simply analyzes the image information and distributes it to fault information terminals with different functions. Tasks are assigned at the fault information terminal, and the processed feedback is received.

[0011] The advantages of the present invention compared with the prior art are:

[0012] The detection method of the present invention can not only detect abnormal conditions such as wear, cracks, and deformation of the pantograph slide, but also shield the offline arc electromagnetic interference of the pantograph network to protect ground equipment and surrounding sensitive electronic components. At the same time, the constructed comprehensive monitoring and fault warning system can realize data visualization and provide scientific decision-making basis for maintenance personnel. DETAILED DESCRIPTION

[0013] In order to make the contents of the present invention more clearly understood, the technical solutions in the embodiments of the present invention are described clearly and completely.

[0014] A planar laser diffuse reflection detection method for rail transit application includes a fixed bracket 1, laser scanning heads 2 are provided on both sides of the fixed bracket 1, and the two laser scanning heads 2 are hinged to the fixed bracket 1 so that the angle can be adjusted. A receiver 3 is fixedly connected to the fixed bracket 1, and an image acquisition module is provided in the receiver 3. The image acquisition module includes an image sensor, a judgment processing center and a fault information terminal. The image sensor performs image filtering and image enhancement processing on the collected skateboard wear pattern and skateboard crack pattern to obtain a skateboard image with higher quality and stronger edge features.

[0015] The image sensor uses the Canny algorithm to perform graphic preprocessing on the crack image to obtain a binary crack image, and then refines the crack to obtain a crack skeleton. The judgment processing center converts the image signal into a digital image signal through A / D (analog-to-digital conversion), and then sends it to the digital signal processing chip (DSP) for processing. The image signal is packaged into a data packet and directly transmitted to the judgment processing center. The judgment processing center simply analyzes the image information, and the fault information terminal performs task dispatching and receives the processed feedback.

[0016] In specific use, laser scanning technology is used to produce a surface refraction effect at the same horizontal plane between the pantograph bracket and the carbon slide board, as well as at the same horizontal position between the front position of the wheel tread of the vehicle frame, the side of the track and the bottom of the rail, to judge and detect the surface flatness of the components, thereby efficiently and accurately obtaining the geometric morphological information of the component surface.

[0017] Secondly, pantograph skateboard monitoring methods are involved. Pantograph skateboard monitoring methods are installed at key locations such as high-speed railway stations, EMU entry and exit areas, and station throat areas. These methods can monitor the technical status of the EMU pantograph skateboard in real time, including abnormal conditions such as wear, cracks, and deformation of the skateboard. Through real-time data collection and analysis, potential safety hazards can be discovered in a timely manner, providing a scientific basis for fault elimination.

[0018] Furthermore, with the support of the above new methods, a comprehensive monitoring and fault warning system is used for data visualization. Combining the laser scanning surface flatness detection technology and the pantograph slide monitoring method, a comprehensive monitoring and fault warning system is constructed. The system can realize comprehensive monitoring of the operating status of the contact network and pantograph, timely detect and warn of abnormal conditions, and guide maintenance personnel to respond quickly, accurately locate and handle faults, thereby ensuring the safe and stable operation of high-speed railways.

[0019] In the specific operation, the computer vision algorithm is used to complete the introduction of the image acquisition module of the system according to the site requirements, the hardware part of the image acquisition module is selected, and the camera annotation principle is briefly described. Finally, the camera annotation experiment is completed based on Matlab software to obtain the conversion relationship between pixel points and space points. The skateboard wear graphics and skateboard crack graphics collected by the graphics acquisition module are filtered and enhanced to obtain a skateboard image with higher quality and stronger edge features.

[0020] When extracting the wear health status features of the skateboard, an improved Canny algorithm was proposed to obtain the continuous wear edge of the skateboard. When extracting the crack features, the crack image was firstly preprocessed to obtain the binary crack image, and then the crack was refined to obtain the crack skeleton. Finally, the crack skeleton image features were learned and recognized based on the support vector machine, and the skateboard crack length was calculated.

[0021] The surface of the observed object generates an optical image through the lens and is projected onto the surface of the image sensor. It is then converted into an electrical signal and converted into a digital image signal through A / D (analog-to-digital conversion). The signal is then sent to the digital signal processing chip (DSP) to be processed and packaged into a data packet and directly transmitted to the judgment processing center. The judgment processing center simply analyzes the image information and then distributes it to fault information terminals with different functions. Tasks are assigned at the fault information terminals, and feedback after processing is received.

[0022] The present invention and its implementation methods are described above, and such description is not restrictive, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design structures and embodiments similar to the technical solution without creativity, which should all fall within the protection scope of the present invention.

Claims

1. Planar laser diffuse reflection detection method for rail transit application, characterized by: The method of use comprises the following steps: Step 1: Collect system images, introduce modules, and select the hardware of image acquisition module; Step 2: Complete the camera annotation experiment based on Matlab software to obtain the conversion relationship between pixel points and spatial points, perform image filtering and image enhancement on the skateboard wear graphics and skateboard crack graphics collected by the graphics acquisition module, and obtain a skateboard image with higher quality and stronger edge features; Step 3: Using the Canny algorithm, the continuous wear edge of the slide is obtained. When extracting crack features, the crack image is preprocessed to obtain a binary crack image, and then the crack is refined to obtain a crack skeleton. Step 4: Based on the crack skeleton in step 3, the image features of the crack skeleton are learned and recognized based on the support vector machine, and the length of the crack of the skateboard is calculated. The surface of the observed object is projected onto the surface of the image sensor after generating an optical image through the lens, and then converted into an electrical signal; Step 5: Based on the electrical signal in step 4, it is converted into a digital image signal through A / D (analog-to-digital conversion), and then sent to the digital signal processing chip (DSP) to process the image signal and package it into a data packet and directly transmit it to the judgment processing center. The judgment processing center simply analyzes the image information and distributes it to fault information terminals with different functions. Tasks are assigned at the fault information terminal, and the processed feedback is received.