Online eddy current detection for micro-defects based a multi-step joint noise reduction and defect signal location

Aiming at the problems of large background noise interference and low detection rate of micro-defects in online eddy current testing (ECT) of stainless steel welded pipes, an optimized online eddy current detection method for micro-defects is proposed. The noise reduction method combining Empirical mode Decomposition (EMD) and wavelet threshold (WT) is adopted. First, the ECT signal is decomposed into a finite number of intrinsic mode functions (IMFs) through EMD. By combining the dual-criterion screening strategy of power spectral entropy (PSD) and correlation coefficient analysis, the high-frequency noise with low correlation is removed. Then, for the high-frequency noise patterns with high correlation, the wavelet threshold denoising algorithm is adopted for denoising. The experimental results show that, compared with the separate empirical mode decomposition and wavelet threshold denoising methods, the signal-to-noise ratio of this method is increased by 5.17dB and 3.36dB respectively, and the mean square error is reduced by 120.18 and 61.50 respectively.To improve the detection rate of micro-defects, the article firstly adopts a defect signal location method combining envelope analysis and wavelet energy analysis, and then enhances the defect part of the signal. The results show that the detection rate of micro-defect stainless steel welded pipes reaches 98.5%, and the false alarm rate of defect-free stainless steel welded pipes drops to 1.8%. This method provides an effective reference for the processing of eddy current testing signals and the detection of micro-defects in stainless steel welded pipes.