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Rubber sealing ring defect detection method based on deep learning

A rubber sealing ring and deep learning technology, applied in image analysis, image enhancement, instruments, etc., can solve the problems of poor stability of visual inspection method, high detection pressure, easy eye fatigue, etc., achieve accurate model recognition, effective regression, and reduce labor The effect of intensity

Pending Publication Date: 2021-06-25
FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST
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Problems solved by technology

[0004] The purpose of the present invention is to address the deficiencies in the prior art, to provide a method for detecting defects of rubber sealing rings based on deep learning, and to solve the problems of high detection pressure, easy fatigue of the eyes and poor stability of the visual inspection method caused by manual detection in the prior art. Low efficiency and other issues

Method used

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  • Rubber sealing ring defect detection method based on deep learning
  • Rubber sealing ring defect detection method based on deep learning
  • Rubber sealing ring defect detection method based on deep learning

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Embodiment 1

[0024] Such as Figure 1 to Figure 2 As shown, a deep learning-based rubber sealing ring defect detection method includes the following steps:

[0025] S1. Collect the image data of the rubber sealing ring after mold opening and perform labeling and defect category definition processing to form a training image database, a verification image database and a test image database.

[0026] Wherein, the specific implementation manner of the above-mentioned step S1 is: use the industrial camera to collect the image data of the rubber sealing ring after mold opening, use the labelImg software to label and process the image data of the rubber sealing ring collected to obtain the xml file, and to The image data xml files after labeling and defect category definition processing are classified to form a training image database, a verification image database and a test image database, and generate images corresponding to the training image database, verification image database and test im...

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Abstract

A rubber sealing ring defect detection method based on deep learning comprises the following steps that image data are collected and marked, defect category definition processing is carried out, and a training image database, a verification image database and a test image database are formed; Establishing a model framework, and training the training image database by using the model framework; S2, performing verification and testing by using the verification image database and the test image database, if the set value is not reached, returning to the step S2 for re-training, If the set value is reached, obtaining a prediction model; S2, testing an output result of the prediction model and feeding back to a rejection mechanism, if the accuracy of the output result is lower than a threshold value, returning to the step S1 to obtain again, If the accuracy of the output result reaches the threshold value, putting into use; According to the invention, the detection work of the rubber sealing ring can be completed in a centralized and high-efficiency manner, the labor intensity is greatly reduced, and the applicability is wide.

Description

technical field [0001] The invention relates to the technical field of automatic visual inspection, in particular to a method for detecting defects of rubber sealing rings based on deep learning. Background technique [0002] As an important industrial product, rubber sealing ring is already a basic component in many industries. Rubber sealing rings have functions such as waterproof, oil-proof, gas-proof, and shock-absorbing, and their quality directly affects the performance and service life of the product, and even threatens personal and property safety. Among all the rubber rings, the O-shaped rubber sealing ring is the most used one, which has simple geometric shape, convenient production and low cost. 1. Uneven cutting, surface damage, grooves, etc. These defects will directly affect the performance of the sealing ring, and will also cause safety problems, causing huge economic losses to the user and the manufacturer. Therefore, before the sealing ring leaves the facto...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06T7/0004G06T2207/20081G06T2207/20084
Inventor 杨海东李泽辉王华龙
Owner FOSHAN NANHAI GUANGDONG TECH UNIV CNC EQUIP COOP INNOVATION INST
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