A Method for Distributed Pipeline Burst and Leakage Detection in Wireless Sensor Networks Using Transform Analysis

Abstract

Bursts and leakages have turned out to be one of the most frequent malfunctions in liquid pipeline distribution systems. In recent years, the issue has gained a lot of attention in research community due to associated financial costs, environmental hazards, and safety considerations. Wireless sensor network (WSN) based leakage detection and localization can provide an exceptional level of operational efficiency, safety assurance, and real-time parametric view of the entire pipeline network. In this paper, we propose a transient pressure wave based technique coupled with wavelet analysis to achieve reliable detection and localization of abrupt bursts and leakages. The presented technique uses the information carried in the transient pressure signal. A specific pattern is induced on the pressure traces within the pipeline due to leak; we use wavelet analysis to detect these local singularities. The proposed algorithm is distributed in nature and run on low power sensor nodes. The algorithm is deployed in field on a custom pipeline test bed and performance results are documented for various testing scenarios. A comparison of proposed wavelet technique with other widely used methods has been carried out. The technique provides more than 90% accuracy in a number of deployment scenarios for high noise generating long pipeline networks.