Pipeline leakage localization method based on transient signal detection and data fusion from multi-sensor

Pipeline leaks pose significant risks to industries, the environment, and individuals, so localizing pipeline leaks is crucial for enhancing pipeline safety during operation. This paper applies a method for localizing pipeline leakages, integrating transient signal detection with multi-sensor data fusion. Addressing the challenges in detecting small leaks amidst strong noise and uncertainty, the method employs the Dempster-Shafer evidence framework for data fusion and an algorithm to analyze transient pressure waves. Comparing it with three spectrum-based methods, the performance of the fusion method is discussed in the single-leakage and multi-leakage cases. In the single-leakage case, even with high levels of noise, the fusion algorithm delivers precise localization estimates. The fusion method excels over the other three methods in the multi-leakage case. The approach significantly enhances the accuracy of leak localization in water pipelines. Extensive simulations demonstrate the method's effectiveness, particularly in noisy environments, offering a promising solution for maintaining pipeline integrity and reducing resource wastage.