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Bearing roller chamfering surface defect detection method based on machine vision

A bearing roller and machine vision technology, which is applied in the field of machine vision-based bearing roller defect detection, can solve the problems of high experience requirements for inspectors, poor detection efficiency and reliability, missed and false detection of defects, etc., to achieve improved defects The effect of detection, improvement of accuracy, and strong stability

Inactive Publication Date: 2020-03-27
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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Problems solved by technology

The traditional screening method relies on manual inspection, which not only requires complicated work and requires high experience of inspectors, but also is easily affected by the environment and the fatigue state of inspectors. Defects are qualitatively judged but not quantitatively evaluated

Method used

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  • Bearing roller chamfering surface defect detection method based on machine vision
  • Bearing roller chamfering surface defect detection method based on machine vision
  • Bearing roller chamfering surface defect detection method based on machine vision

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Embodiment Construction

[0033] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0034] Such as figure 1 As shown, a machine learning-based detection method for bearing roller chamfer surface defects includes the following steps:

[0035] 1) Establish a machine vision acquisition system to collect a large number of bearing roller image samples containing chamfered surface defects, manually calibrate the defect positions, and establish a chamfered surface defect database;

[0036] 2) Establish a deep learning algorithm target detection model based on a deep convolutional neural network, use the defect samples in the defect database to train and optimize the detection model, and obtain a network model suitable for the detection of defects on the chamfer surface of bearing rollers;

[0037] 3) Use the visual acquisition system to collect the image of the roller to be detected, and use the edge detection algorithm based on th...

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Abstract

The invention discloses a bearing roller chamfered surface defect detection method based on machine vision. Aiming at the chamfering surface defect problem of the bearing roller in the production andtransportation process, a chamfering surface image of the bearing roller is collected, a chamfering surface missing part detection model is established by utilizing a deep learning algorithm based ona deep convolutional neural network, and rapid detection and position positioning of the chamfering surface defect are realized. According to the method, the deep learning model and the machine visionalgorithm are used for detecting the bearing roller chamfer defects in real time, the method has the advantages of being rapid in detection, accurate in positioning and high in recognition accuracy,a traditional manual detection method can be replaced, and the requirement for roller defect detection automation is met.

Description

technical field [0001] The invention relates to the field of image detection, in particular to a method for detecting defects of bearing rollers based on machine vision. Background technique [0002] The bearing roller is the core component of the bearing, and the damage of the roller will cause the accelerated wear and aging of the roller, and even cause the operation failure of the bearing. Therefore, the rollers need to be screened before assembly to remove defective rollers. The traditional screening method relies on manual inspection, which not only requires complicated work and requires high experience of inspectors, but also is easily affected by the environment and the fatigue state of inspectors. Defects are judged qualitatively rather than quantitatively. Therefore, the invention of an automatic bearing roller defect detection method has high application value and meets the actual needs of intelligent roller defect detection, high efficiency, high accuracy and go...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/88G01M13/04G06T7/00G06T7/11G06N3/04G06N3/08
CPCG01N21/8806G01N21/8851G01M13/04G06T7/0004G06T7/11G06N3/08G01N2021/8887G01N2021/8861G06T2207/30164G06N3/045
Inventor 杜劲松白珈郡李兴强李祥杨旭崔维华张清石畅申
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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