Method and system for visually detecting surface defects of plastic product

By functional identification and partitioning of home appliance housing and defect identification combined with integrated learning model, the problem of insufficient defect detection efficiency and accuracy in the existing technology is solved, and more efficient and accurate detection effects are achieved.

CN120084823AInactive Publication Date: 2025-06-03JIANGSU HUILILONG PLASTIC IND GROUP
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Patent Information

Application Number
CN202510287564.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-12
Publication Date
2025-06-03
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

In the prior art, the surface defect detection efficiency and recognition accuracy of household appliance housings are low, and it is impossible to optimize the characteristics of different functional areas.

Method used

By obtaining the design information of the home appliance shell, functional identification is performed to obtain the shell functional partition. According to the functional characteristics of the functional partition, the defect identification requirements and location distribution are determined, image information is collected and partition defect identification parameters are located. Then, a defect identification module is configured to use an integrated learning model to identify partition defects.

Benefits of technology

The visual detection efficiency and recognition accuracy are improved, and the defect detection parameters are optimized through functional partitioning features, and the problem of insufficient detection efficiency and accuracy in the prior art is solved.

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Abstract

The invention discloses a method and a system for visually detecting surface defects of a plastic product, and relates to the technical field of defect detection. The method comprises the following steps: performing function identification according to design information to obtain a shell function partition; determining defect identification requirements and position distribution according to functional characteristics of the shell function partitions; collecting image information of the plastic shell product; according to the corresponding relation between defect identification requirements and position distribution, partition defect identification parameter positioning is conducted on the image information, partition identification parameters are obtained, and when multiple partition identification parameters exist, an identification parameter weight exists; configuring a defect identification module according to the partition identification parameters; and carrying out partition defect identification on the corresponding image information by utilizing a defect identification module to obtain a defect identification result. The technical problem that in the prior art, surface defect detection efficiency and recognition precision are low is solved, defect detection parameters are optimized through function partition features, and the technical effect of improving detection efficiency and recognition precision is achieved.
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