Nondestructive testing optimization method based on safety status assessment accuracy feedback of explosion-proof equipment

By monitoring the beam steering angle and local temperature gradient of explosion-proof equipment in real time, combining high-precision sensors and data analysis, the beam steering angle and scanning density are automatically adjusted, which solves the problem of traditional non-destructive testing methods detecting blind spots in complex equipment, and achieves efficient and accurate equipment monitoring and fault identification.

CN120195273BActive Publication Date: 2025-08-15SHENZHEN ZHONGZHIAN QUALITY SAFETY TECH ASSESSMENT CENT CO LTD
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Patent Information

Application Number
CN202510669420.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-23
Publication Date
2025-08-15
Estimated Expiration
2045-05-23

AI Technical Summary

Technical Problem

Traditional non-destructive testing methods are difficult to fully cover key areas of complex equipment, especially in deep holes, narrow channels or uneven thickness parts, resulting in blind spots in detection and signal interference, affecting the accuracy of defect identification.

Method used

By monitoring the beam steering angle and local temperature gradient of explosion-proof equipment in real time, using high-precision sensor network and data analysis technology, the beam steering angle anomaly and local temperature gradient eigenvalues are calculated, the characteristic vector is constructed, and the support vector machine model is input, and the beam steering angle and scanning density are automatically adjusted to cover the abnormal area.

Benefits of technology

It significantly improves the detection sensitivity and accuracy of potential faults, promptly identify subtle changes, improves equipment safety and operational reliability, optimizes maintenance strategies, and reduces operating costs.

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Abstract

The present invention relates to the technical field of industrial safety and non-destructive testing, and specifically discloses a non-destructive testing optimization method based on accuracy feedback of explosion-proof equipment safety status assessment. By real-time monitoring of the beam steering angle and local temperature gradient of the explosion-proof equipment, key data is obtained using a high-precision sensor network, and advanced data analysis technologies such as clustering algorithms and fast Fourier transforms are applied to calculate abnormal eigenvalues of the beam steering angle and local temperature gradient eigenvalues to evaluate the stability of ultrasonic propagation and the consistency of the internal structure of the equipment. These eigenvalues are combined to construct a eigenvector, which is input into a support vector machine model and outputs a safety status score of the equipment. This score is used to determine whether the current detection process is in an unstable state. Once the system is determined to be unstable, the beam steering angle will be automatically adjusted to cover the abnormal area, and the scanning density of the abnormal area displayed by the local temperature gradient will be increased to ensure more detailed detection of potential problems.
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