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文章中把LMS时延估计算法用于地下管网的泄漏检测和漏点定位,避免了经典时延估计算法-广义互相关法(GCC方法)需要知道信号和噪声统计特性等先验知识的不足,但是泄漏检测应用中,管道外在环境造成的突发性强干扰,导致了传感器接收到的信号是非平稳的,而非平稳信号对LMS的时延估计性能有不利影响,文章中分析了这种由突发性强干扰导致的非平稳信号对LMS时延估计收敛性、收敛速度和时延估计值的影响,提出了消除突发干扰的方法。实验表明,在地下管网泄漏检测应用中,该方法能够有效地消除强突发干扰噪声,使得估计性能得到显著的改善。
In this paper, LMS time delay estimation algorithm is applied to leak detection and leak location in underground pipelines, which avoids the shortage of prior knowledge such as generalized cross-correlation method (GCC method) that needs to know the statistical properties of signal and noise However, in the leak detection application, the sudden strong interference caused by the external environment of the pipeline leads to the non-stationary signal received by the sensor, and the non-stationary signal has an adverse effect on the LMS time delay estimation performance. The article analyzes the The effects of nonstationary signals caused by sudden strong interference on the convergence, convergence rate and delay estimation of LMS delay estimation are analyzed. A method to eliminate the burst interference is proposed. Experiments show that this method can effectively eliminate the strong burst noise and improve the estimation performance significantly in the underground pipe network leak detection.