Truck bearing damage detection method

A damage detection and bearing technology, applied in neural learning methods, image data processing, biological neural network models, etc., can solve problems such as low accuracy, low efficiency, and long time, and achieve improved efficiency, high flexibility, and improved operation. quality effect

Active Publication Date: 2020-04-28
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problems of long time-consuming and low efficiency in manual detection of truck bearing damage, and the problem of low accuracy in image-based detection of truck bearing damage

Method used

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  • Truck bearing damage detection method
  • Truck bearing damage detection method
  • Truck bearing damage detection method

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specific Embodiment approach 1

[0038] The implementation of a method for detecting damage to a truck bearing described in this embodiment is divided into two stages: a training stage and an inference stage.

[0039] 1. Training phase, such as figure 1 Shown:

[0040] 1.1. Image collection

[0041] Use a line-scan camera, that is, a line-scan camera, to collect images, calculate the shooting frequency of the line-scan camera based on the moving speed of the measured object, and take multiple consecutive pictures, and combine the multiple "strip" images taken In this way, seamless splicing can be realized to generate a two-dimensional image with a large field of view and high precision.

[0042] 1.2. Coarse positioning of the target area

[0043] According to the prior information such as the wheelbase of the truck and the location of the bearing area of ​​the truck, the bearing area of ​​the truck is determined from the two-dimensional image and the image of the bearing area of ​​the truck is extracted, s...

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Abstract

A truck bearing damage detection method belongs to the technical field of freight train detection. The objective of the invention is to solve the problems of long consumed time and low efficiency of manual truck bearing damage detection and the problem of low accuracy of truck bearing damage detection based on images. The method comprises the following steps: acquiring an image and extracting an image corresponding to a truck bearing area as a truck bearing area image to be identified; inputting a to-be-identified truck bearing area image into the trained Mask-RCNN network for speculation, andobtaining a prediction result of each image, the prediction result comprising categories of a plurality of ROIs, frame coordinates, segmentation coordinates and confidence scores; and combining faultposition prior information and bearing auxiliary category information to further detect truck bearing damage according to the confidence coefficient score of the fault. The method is mainly used fortruck bearing damage detection.

Description

technical field [0001] The invention relates to a method for detecting damage to a truck bearing. The invention belongs to the technical field of freight train detection. Background technique [0002] Railway wagons have always played an important role in transportation, and the railway department needs to conduct safety inspections on railway wagons frequently to ensure the safe and stable operation of railway wagons. In the detection of railway freight cars, in order not to affect the normal running and scheduling of railway freight cars, and in order to improve the detection efficiency, most of them currently rely on manual inspection of images for detection, which will consume a lot of labor costs and time costs. Moreover, this detection technology completely relies on the sense of responsibility and energy of the inspectors. Once too many images are viewed, the detection error rate and missed detection rate will increase significantly. [0003] In the routine inspecti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/32G06K9/54G06K9/62G06N3/04G06N3/08
CPCG06T7/0008G06N3/08G06T2207/10004G06T2207/20081G06T2207/20084G06T2207/20104G06V10/25G06V10/20G06N3/045G06F18/241G06F18/214
Inventor 庞博
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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