An image recognition-based intelligent detection system for defects in automobile valve body machining

The intelligent detection system for automotive valve body machining defects based on image recognition utilizes curvature changes and texture features to filter detection areas, distinguishing between attached burrs and free foreign matter. This solves the problem of poor detection accuracy of valve body bore inner walls, improving detection efficiency and safety.

CN122435342APending Publication Date: 2026-07-21TIANJIN JUNLEI PRECISION MACHINERY TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
TIANJIN JUNLEI PRECISION MACHINERY TECHNOLOGY CO LTD
Filing Date
2026-04-30
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing technologies fail to effectively consider the impact of sudden changes in local curvature of the inner wall of automotive valve body bores on defect detection, resulting in poor detection accuracy and potentially causing safety accidents.

Method used

An intelligent detection system for automotive valve body machining defects based on image recognition is adopted. The detection area is screened by curvature change characterization value. Combining gray-scale statistical features and contour geometric deviation features, a dual classification decision mechanism is constructed using texture fracture index and shadow offset characterization value to distinguish between attached burrs and free foreign objects.

Benefits of technology

It improves the accuracy and efficiency of valve body machining defect detection, effectively identifies defects on complex curved surfaces, reduces light and shadow interference, and ensures the reliability and safety of judgment.

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Abstract

The present application relates to the technical field of image recognition, in particular to a kind of intelligent detection system of automobile valve body machining defect based on image recognition, comprising: image acquisition module for obtaining hole wall image;Characteristic calculation module;With the region screening module for detecting area screening according to curvature variation characteristic value;With the control module for determining whether ordinary area exists machining defect according to the surface anomaly characteristic value of the ordinary area and for determining whether risk area exists machining defect according to the contour deviation characteristic value of risk area;With the defect determination module for determining the machining defect cause category of the risk area according to the texture fracture index of the risk area and for determining the machining defect cause category of the risk area according to the shadow offset characteristic value of the risk area secondary, so as to improve the detection accuracy of automobile valve body machining defect.
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