A Bayesian solution to the multiple composite hypothesis testing for fault diagnosis in dynamic systems |
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Authors: | Davi Antônio dos Santos Takashi Yoneyama[Author vitae] |
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Affiliation: | aInstituto Tecnológico de Aeronáutica, Divisão de Engenharia Mecânica-Aeronáutica, 12228-900 - São José dos Campos, SP, Brazil;bInstituto Tecnológico de Aeronáutica, Divisão de Engenharia Eletrônica, 12228-900 - São José dos Campos, SP, Brazil |
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Abstract: | This paper is concerned with model-based isolation and estimation of additive faults in discrete-time linear Gaussian systems. The isolation problem is stated as a multiple composite hypothesis testing on the innovation sequence of the Kalman filter (KF) that considers the system operating under fault-free conditions. Fault estimation is carried out, after isolating a fault mode, by using the Maximum a Posteriori (MAP) criterion. An explicit solution is presented for both fault isolation and estimation when the parameters of the fault modes are assumed to be realizations of specific random variables (RV). |
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Keywords: | Fault diagnosis Multiple hypothesis testing Estimation theory Detection theory |
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