【摘要】 管道泄漏的定位精度主要取决于信号去噪效果和时延估计性能。针对当前管道泄漏定位精度较差的问题,提出了非局部均值-经验模态分解(NLM-EMD)自相关去噪算法和模糊C均值聚类(FCM)-二次相关自适应时延估计算法。利用NLM进行降噪预处理,根据EMD自相关准则进行重构去噪,然后利用FCM自适应提取相关性较高的压力下降段信号,对其进行二次相关时延估计。结果表明,NLM-EMD自相关法能有效降低噪声干扰,提高EMD分解质量,FCM-二次相关法能增强两泄漏信号的相关性,与直接二次相关相比定位精度提高了0.817%。更多还原

【Abstract】 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 re-duce 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.更多还原