Bayesian detection of leaks in gas distribution networks

A probabilistic method is proposed to detect and localize leaks in low-pressure gas distribution networks. These leakage events are estimated using flow and pressure information obtained from the steady state analysis of gas network. The approach provides an estimation of the leaked pipe section and the amount of gas outflow from the pipe section containing leaks. The reliability of the methodology is shown by analyzing the network in the presence of network modeling errors. These errors account for the variation in demand value of gas at the outlet nodes and the change in pipe roughness due to age. Even in the presence of large noise in the network, this methodology provides an accuracy of more than 80% in the localization of leak. The study aims to develop a real-time online monitoring system for low pressure gas distribution networks. Moreover, this technique is cost effective and can be easily integrated with the existing monitoring system.

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