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The positioning accuracy of pipeline leakage mainly depends on denoising effect and time delay estimation performance. In view of the problem of poor positioning accuracy of current pipeline leak, Non-Local Means-Empirical Mode Decomposition(NLM-EMD) autocorrelation method for denoising and Fuzzy C-Means clustering(FCM)-second correlation method for adaptive time delay estimation are proposed. NLM is used for noise reduction pretreatment, and the signal is recombined and de-noised according to autocorrelation criterion of EMD, then FCM is used to adaptively extract the pressure drop signal with higher correlation, and second correlation can estimate the delay of the signal. The results show that NLM-EMD autocorrelation method can effectively reduce noise interference and improve the decomposition quality of EMD, FCM-second correlation method can enhance the correlation of the two leakage signals, and the positioning accuracy is improved by 0.817% compared with the direct second correlation.

Evaluating the filtering process of the digital speckle pattern interferometry (DSPI) of a single image by the traditional methods can result in under- or over-filtering. To solve this problem, this paper proposes an image-filtering evaluation method based on the Sobel operator and image entropy. First, the Sobel operator is introduced to convolute a filtered image to obtain a gradient image of a DSPI. Then, by analyzing the gradient image, image entropy is calculated according to the characteristics of the gradient map. Finally, the proposed method is verified by experiments. The experimental results show that the proposed method can quantitatively evaluate the filtering process of the DSPI. [ABSTRACT FROM AUTHOR]