Research on pressure propagation in long-distance water pipelines for fault conditions by VMD and wavelet transform

Abstract

Long-distance water pipelines in complex geographical environments face potential risks such as leaks. This study uses variational mode decomposition (VMD) and continuous wavelet transform (WT) to analyze pressure fluctuation signals in pipelines for detecting and locating leaks and other anomalies. CFD simulations are conducted to obtain pressure fluctuation data under various fault conditions. The pressure signals are then decomposed into multiple Intrinsic Mode Functions (IMFs) using VMD, and WT is applied to analyze their time–frequency characteristics. The results show significant differences in amplitude and frequency of IMF components between fault and normal conditions, with reduced amplitude and altered frequency under fault conditions, providing a basis for fault detection. Additionally, the IMF characteristics differ at different fault locations, aiding in fault localization. This research offers an effective method for leak detection and localization in long-distance pipelines, crucial for enhancing safety and stability.