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Motor train unit sanding pipe joint disconnection fault detection method based on image processing

A technology for image processing and disconnecting faults, applied in the field of image processing, can solve problems such as missed detection and false detection, and achieve the effects of reducing false positives, enhancing edges, and improving accuracy

Active Publication Date: 2021-03-16
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention aims to solve the problem that the existing method of manually checking the image to check whether the sand sprinkling pipe joint is disconnected may easily cause missing or wrong detection
Now provides a fault detection method based on image processing EMU sand-spraying pipe joint disconnection

Method used

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  • Motor train unit sanding pipe joint disconnection fault detection method based on image processing
  • Motor train unit sanding pipe joint disconnection fault detection method based on image processing
  • Motor train unit sanding pipe joint disconnection fault detection method based on image processing

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specific Embodiment approach 1

[0051] Specific implementation mode one: combine figure 1 Describe this embodiment, the method for detecting disconnection faults of sand-spraying pipe joints of EMUs based on image processing in this embodiment, the method includes:

[0052] Step 1. Collect the image of the sand-spreading pipe part of the EMU, extract the features of the sand-spraying pipe part image as the training feature, use the training feature to train the support vector machine, and obtain a trained classifier, wherein the trained classifier can use The images of the sanding pipe components are divided into two categories, namely, the disconnected image of the sanding pipe joint and the undisconnected image of the sanding pipe joint;

[0053] Step 2. Obtain the two-dimensional image containing the sand-sprinkling pipe of the EMU to be detected;

[0054] Step 3, denoising the two-dimensional image to obtain a noise-free image containing the sand-sprinkling pipe of the EMU;

[0055] Step 4, matching th...

specific Embodiment approach 2

[0059] Specific embodiment two: this embodiment is the fault detection method based on the image processing EMU sanding pipe joint disconnection of specific embodiment one, in step 2, obtain the two-dimensional image containing the EMU sanding pipe to be detected, including :

[0060] Use camera equipment to collect images of the bottom of the EMU;

[0061] A two-dimensional image containing the sanding pipe of the EMU is intercepted from the bottom image of the EMU.

[0062] In this embodiment, the line scanning method may be used to collect the bottom image of the EMU to form a two-dimensional image with a wide field of view and high precision. It can effectively reduce the time required for fault identification and improve the accuracy of identification.

specific Embodiment approach 3

[0063] Specific embodiment three: This embodiment is a method for detecting disconnected faults of sand-spraying pipe joints of EMUs based on image processing in Embodiment 1. In step 3, the two-dimensional image is denoised to obtain sand-spraying pipes containing EMUs. Noise-free images of , including:

[0064] The denoising model is used to denoise the two-dimensional image, and the denoising model is:

[0065]

[0066] In the formula, J(u) is the objective function of denoising processing, minJ(u) represents the minimum value of J(u), is the regular term of the two-dimensional image containing the EMU sand pipe, for fidelity item, is a fractional gradient operator, (x, y) are the coordinates of each pixel in the two-dimensional image containing the EMU sanding pipe, Ω represents the range of (x, y), u(x, y) is the noise-free image containing the EMU sanding pipe, u 0 (x, y) is a two-dimensional image containing the EMU sand pipe, u 0 (x,y)=u(x,y)+n(x,y)n(x,y) ...

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Abstract

The invention relates to the field of image processing, in particular to a motor train unit sanding pipe joint disconnection fault detection method based on image processing, solves the problems of missing detection and wrong detection caused by the fact that whether a sanding pipe joint is disconnected or not is checked in an existing manual image checking mode, and relates to the field of imageprocessing. The method comprises the steps: taking the features of sanding pipe component images as training features, and acquiring a trained classifier; processing the to-be-detected image containing the motor train unit sanding pipe to obtain a noise-free image containing the motor train unit sanding pipe; matching the noiseless image with a sanding pipe template image stored in a template image library, and extracting a sanding pipe joint image from the noiseless image according to the successfully matched sanding pipe template image; extracting features of the sanding pipe joint image asto-be-detected features; inputting the to-be-detected features into the trained classifier, and outputting the category of the sanding pipe joint image. The device is used for identifying whether thesanding pipe joint is disconnected.

Description

technical field [0001] The invention relates to a fault detection method for disconnection of a sand spreading pipe joint. It belongs to the field of image processing. Background technique [0002] The sand spreading system is an important part of the brake system of the EMU, which can effectively improve the working environment of the wheel-rail contact surface, improve the adhesion coefficient, and improve the running quality. Especially in bad weather such as rain, snow and frost, the rails become very slippery, and the vehicle is prone to idling or sliding. The sand spreading system can effectively reduce the occurrence of such problems. The disconnection of the sanding pipe joint leads to the failure of the sanding function of the sanding system of the EMU, which endangers the driving safety. In traditional fault detection methods, fault detection is usually performed by manually inspecting images. Due to the fact that the inspectors are prone to fatigue and omission...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/40G06K9/62G06T7/41B61K9/00
CPCG06T7/0004G06T7/41B61K9/00G06V10/30G06V10/751G06F18/2411G06F18/214
Inventor 刘丹丹
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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