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Wavelet Energy Entropy Based Multi-Sensor Data Fusion for Residual Stress Measurement Using Innovative Intense Magnetic Memory Method

机译:创新的强磁存储方法基于小波能量熵的多传感器数据融合残余应力测量

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In this paper, a novel and effective NDT method named Intense Magnetic Memory (IMM) was introduced to inspect transmission pipeline, which can provide early indications of residual stress status and eventual failure in pipeline. An experimental system was set up and the abnormal signals obtained from pipeline specimens were decomposed by wavelet transform (WT). Wavelet energy entropy was used to extract characteristic from abnormal signals. Multisensor data fusion algorithm was applied to get the whole stress concentration distribution. Initial experimental result shows that it is promising for IMM technology being applied to pipeline inspection.
机译:本文介绍了一种新颖有效的无损检测方法-强磁记忆(IMM)来检查传输管道,该方法可以提供残余应力状态和管道最终故障的早期指示。建立了一个实验系统,并通过小波变换(WT)分解了从管道样本中获得的异常信号。小波能量熵被用来从异常信号中提取特征。应用多传感器数据融合算法获得整个应力集中分布。初步的实验结果表明,将IMM技术应用于管道检测是有希望的。

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