An Improved Cross-correlation Algorithm Based on Wavelet Transform and Energy Feature Extraction for Pipeline Leak Detection
Leakage is one of the main problems faced by many pipeline industries,such as water supply and gas transmission systems.For its prominent capability of on-line monitoring the singular signals,acoustic emission (AE) technique has been considered as one of the most potential manners for pipeline leak detection.As a kind of continuous AE signals,leak signals are usually processed with cross-correlation method.However,due to the multi-modes and dispersion nature of AE wave propagating in pipeline,the traditional cross-correlation analysis does not perform well in practice.This paper presents an improved cross-correlation algorithm for high-precision pipeline leak detection based on wavelet transform and energy feature extraction.Both energy and frequency features of AE signals are taken into consideration to determine the time delay for leak location.A series of numerical simulations are conducted and AE signals measured in-situ is analyzed based on the proposed method.The results show that the improved method can achieve higher precision of the identification for signal similarity and time delay,especially when the continuous AE signals are affected by various disturbances and noises.
Pipeline Leak Detection Cross-correlation Analysis Wavelet Transform Energy Feature Extraction
Xinxin Wang Ming Zhao Suzhen Li
Master student; Department of Civil Engineering, Tongji University; No.1239, Siping Road, Shanghai 2 Professor; Department of Civil Engineering, Tongji University; No.1239, Siping Road, Shanghai 200092 Associate Professor; Department of Civil Engineering and the State Key Laboratory of Disaster Resear
国际会议
北京
英文
577-591
2012-10-14（万方平台首次上网日期，不代表论文的发表时间）