Sciweavers

Share
IJSNET
2007

Distributed Bayesian fault diagnosis of jump Markov systems in wireless sensor networks

9 years 10 months ago
Distributed Bayesian fault diagnosis of jump Markov systems in wireless sensor networks
: A Bayesian distributed online change detection algorithm is proposed for monitoring a dynamical system by a wireless sensor network. The proposed solution relies on modelling the system dynamics by a jump Markov system with a finite set of states, including the abrupt change behaviour. For each discrete state, an observed system is assumed to evolve according to a state-space model. The collaborative strategy ensures the efficiency and the robustness of the data processing, while limiting the required communications bandwith. An efficient Rao-Blackwellised Collaborative Particle Filter (RB-CPF) is proposed to estimate the a posteriori probability of the discrete states of the observed systems. The Rao-Blackwellisation procedure combines a Sequential Monte-Carlo (SMC) filter with a bank of distributed Kalman filters. In order to prolong the sensor network lifetime, only few active (leader) nodes are selected according to a spatio-temporal selection protocol. This protocol is base...
Hichem Snoussi, Cédric Richard
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where IJSNET
Authors Hichem Snoussi, Cédric Richard
Comments (0)
books