先进的涡流无损检测自动化系统

Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396) Pub Date : 2000-02-22 DOI:10.1109/NRSC.2000.838977

M. Fahmy, E. Hashish, I. Elshafiey, I. Jannound

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引用次数: 9

摘要

各种无损检测技术广泛应用于亚表面缺陷的检测。本文介绍了通过开发基于计算机的集成系统来提高涡流无损检测性能的研究成果。该系统的优点是提高了测试速度，同时避免了人为因素造成的错误。该系统可用于优化影响亚表面裂纹检测性能的各种参数，包括探头配置和工作频率范围。通过对原始涡流信号进行高级处理，增强了可检测性。将二维小波变换应用于涡流c扫描图像，提取表征材料缺陷的特征向量。然后利用人工神经网络技术自动检测和分类亚表面缺陷。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Advanced system for automating eddy-current nondestructive evaluation

Various nondestructive evaluation (NDE) techniques are widely used in the inspection of sub-surface flaws. This paper introduces the results of a research conducted to enhance the performance of eddy-current nondestructive evaluation (ECNDE) by developing an integrated computer based system. Advantages of this system include increasing test speed, while avoiding errors due to human factors. The system can be used to optimize various parameters affecting the performance of inspecting sub-surface cracks including probe configuration and operating frequency range. Inspectability is enhanced by advanced processing of raw eddy current signal. The two-dimensional wavelet transform is applied to eddy current c-scan images to extract feature vectors representing the material flaws. Artificial neural network techniques are then invoked to automate the detection and classification of sub-surface flaws.

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Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)

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