access icon free Sub-optimum fast Bayesian techniques for joint leak detection and localisation

© The Institution of Engineering and Technology
Received 29/10/2012, Accepted 27/03/2013, Revised 26/02/2013, Published

A fast tree-search algorithm for joint leak detection and localisation using surface-borne ultrasonic acoustic signals is developed through a wireless sensor network. Owing to environmental noise and multipath fading of ultrasonic signals, false sensor observations are frequent in the observation data. The problem is modelled as a Bayesian inference model and the maximum a posteriori solution is approximated through a tree-search structure. The algorithm initially divides the area into large cells and approximates the observation likelihood function over these large cells. In a tree structure, a large cell with high likelihood is divided into smaller cells and the tree is expanded until the required estimation precision is obtained. Simulation and experimental results reveal advantages of the proposed technique in terms of estimation error and convergence speed in comparison with other conventional Bayesian techniques such as particle filtering.

Inspec keywords: wireless sensor networks; search problems; particle filtering (numerical methods); acoustic signal processing; Bayes methods; approximation theory

Other keywords: false sensor observations; ultrasonic signals; environmental noise; wireless sensor network; suboptimum fast Bayesian techniques; joint leak detection; Bayesian techniques; surface borne ultrasonic acoustic signals; particle filtering; tree search algorithm; tree-search structure; joint leak localisation; Bayesian inference model; observation data; tree structure; multipath fading

Subjects: Filtering methods in signal processing; Optimisation techniques; Wireless sensor networks; Interpolation and function approximation (numerical analysis); Other topics in statistics

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