An industrial assembly line automotive parts vision inspection system

By introducing aperture detection, contour detection, and surface defect detection, a quantified anomaly coefficient is generated, which solves the problem that existing technologies cannot analyze anomaly factors, enables rapid identification of anomaly tendency characteristics, improves detection efficiency and accuracy, and reduces downtime and maintenance costs.

CN122448754APending Publication Date: 2026-07-24广东威亚特汽车零部件有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
广东威亚特汽车零部件有限公司
Filing Date
2026-06-09
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing technologies cannot perform anomaly analysis when continuous anomalies occur in test results, resulting in low efficiency and long downtime in automotive parts testing, and an inability to quickly generate optimized processing decisions for production processes or testing environments.

Method used

Design a visual inspection system for automotive parts in an industrial assembly line, comprising a visual inspection platform, a quality inspection module, a result analysis module, and an anomaly handling module. Through aperture detection, contour detection, and surface defect detection, generate aperture anomaly coefficients, contour anomaly coefficients, and surface anomaly coefficients for quantitative anomaly factor analysis.

Benefits of technology

It enables comprehensive quality assessment of automotive parts, quickly identifies abnormal tendencies, improves the efficiency and accuracy of anomaly handling, and reduces production line downtime and maintenance costs.

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Abstract

The application belongs to the field of automobile accessory quality detection, and relates to visual detection technology, and is used for solving the problem that the prior art cannot analyze abnormal factors when continuous abnormality appears in detection results, in particular to an industrial assembly line automobile part visual detection system, which comprises a visual detection platform, and the visual detection platform is communicatively connected with a quality detection module, a result analysis module, an abnormality processing module and a database; the application can intelligently analyze and classify complex and multi-dimensional abnormal detection results, and improves from pure defect identification to defect reason tendency judgment, which makes managers no longer need to spend a lot of time and energy to check all possible links one by one when facing continuous defects, but can quickly obtain a clear optimization direction; when the abnormality has a tendency, the system can accurately point out the specific process that needs to be optimized, so that the treatment is targeted, and invalid intervention to non-key processes is avoided.
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