Multi-leak diagnosis in pipelines based on Extended Kalman Filter

• A model adaptation strategy is proposed to isolate non-concurrent multiple leaks.
• An approach based on Extended Kalman Filters allows us to isolate leaks as they appear.
• Experimental results with real-data are shown through different configurations.

A model-based approach to detect and isolate non-concurrent multiple leaks in a pipeline is proposed, only using pressure and flow sensors placed at the pipeline ends. The approach relies on a nonlinear modeling derived from Water–Hammer equations, and related Extended Kalman Filters used to estimate leak coefficients. This extends former results developed for the single leak case, but with the difficulty that the model is modified at each new leak occurrence. A model adaptation strategy is thus proposed, allowing us to monitor indeed each new leak, and no matter where it appears. Experimental results illustrate the performance of the proposed algorithm.