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Time and Frequency Domain Feature Fusion for Defect Classification Based on Pulsed Eddy Current NDT

机译:基于脉冲涡流无损检测的时频域特征融合在缺陷分类中的应用

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Pulsed Eddy current (PEC) is an emerging nondestructive evaluation (NDT) technique excited with a broadband pulse that consists of rich frequency information. This technique generally uses the response peak value and peak arrival time to detect and quantify defects, which is not sufficient to achieve enough information associated with flaw quantification. This article introduces the application of empirical mode decomposition and Hilbert transform in extracting a new frequency domain feature from PEC responses. Time and frequency features are combined to enhance the accuracy of defect classification. The validation and robustness of the new feature and the improved classification by experimental studies are presented.View full textDownload full textKeywordsdefect classification, feature extraction, feature fusion, instantaneous frequency, pulsed eddy currentRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/09349847.2012.660243
机译:脉冲涡流(PEC)是一种新兴的无损评估(NDT)技术,由包含丰富频率信息的宽带脉冲激发。该技术通常使用响应峰值和峰值到达时间来检测和量化缺陷,这不足以实现与缺陷量化相关的足够信息。本文介绍了经验模式分解和希尔伯特变换在从PEC响应中提取新的频域特征中的应用。时间和频率特征相结合以提高缺陷分类的准确性。提出了新功能的有效性和鲁棒性,并通过实验研究对分类进行了改进。查看全文下载全文关键词缺陷分类,特征提取,特征融合,瞬时频率,脉冲涡流services_compact:“ citeulike,netvibes,twitter,technorati,可口,linkedin,facebook,stumbleupon,digg,google,更多”,发布:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/09349847.2012.660243

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