Distributed Bayesian Fault diagnosis in Collaborative Wireless Sensor Networks

Abstract— In this contribution, we propose an efficient collaborative strategy for online change detection, in a distributed sensor network. The collaborative strategy ensures the efficiency and the robustness of the data processing, while limiting the required communication bandwith. The observed systems are assumed to have each a finite set of states, including the abrupt change behavior. For each discrete state, an observed system is assumed to evolve according to a linear state-space model. An efficient Rao-Blackwellized collaborative particle filter (RBCPF) is proposed to estimate the a posteriori probability of the discrete states of the observed systems. The Rao-Blackwellization procedure combines a sequential Monte Carlo filter with a bank of distributed Kalman filters. Only sufficient statistics are communicated between smart nodes. The spatio-temporal selection of the leader node and its collaborators is based on a trade-off between error propagation, communication ...

• Type: Conference
• Year: 2006
• Where: GLOBECOM
• Authors: Hichem Snoussi, Cédric Richard
• Keywords: Collaborative Strategy, Discrete States, GLOBECOM 2006, Observed Systems, Telecommunications