Crack detection device and method for precise automobile parts

Through ultrasonic multi-dimensional scanning and multi-physics fusion technology, the accuracy and reliability of crack detection of precision automotive parts are solved, and high-precision crack recognition and prediction are achieved, suitable for automotive parts with complex structures and stress distribution.

CN120404946AInactive Publication Date: 2025-08-01ZHAOQING FENGCHI PRECISION METALWORK
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Patent Information

Application Number
CN202510920611.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-04
Publication Date
2025-08-01
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The existing precision automotive parts crack detection methods ignore the multi-physical coupling characteristics and complex structural characteristics, resulting in low accuracy and reliability of the detection results.

Method used

Ultrasonic multi-dimensional pre-scan is used to identify acoustic reflection data, combine stress-acoustic response timing data for three-dimensional stress field reconstruction, dual-frequency stress modulation excitation and multi-physics field synchronization detection, and feature matching and prediction are performed through multi-parameter fusion calculation and multi-scale wavelet decomposition, and crack geometric parameters and acoustic time-frequency characteristics.

Benefits of technology

It realizes high-precision intelligent detection of cracks in precision automotive parts, especially in stress concentration recognition, lossless grasping and synchronous detection of internal and external cracks, which improves detection accuracy and reliability and provides accurate identification of crack types and development trends.

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Abstract

The invention relates to the technical field of nondestructive testing, and discloses a crack detection device and method for precise automobile parts. The method comprises the following steps: carrying out ultrasonic multi-dimensional pre-scanning and acoustic impedance abnormal region identification on a to-be-detected automobile part, carrying out influence range calculation and sensitive threshold classification based on abnormal region distribution data, and obtaining stress-acoustic response time sequence data through partition grabbing force distribution and stress loading; three-dimensional stress field reconstruction and stress concentration area identification are realized; performing dual-frequency stress modulation excitation and multi-physics field synchronous detection on the stress concentration area to obtain a multi-physics field response signal, performing multi-parameter fusion calculation and multi-scale wavelet decomposition of acoustic components on the multi-physics field response signal, and performing feature dimension splicing to obtain crack feature classification data; and calculating and generating a crack detection result based on feature similarity matching and extension prediction. The precision and reliability of crack detection of the automobile parts are remarkably improved, and the damage risk in the detection process is avoided.
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