Baoping Cai

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Keywords: Dynamic Bayesian networks Fault tree Imperfect repair Subsea blowout preventer Reliability Availability a b s t r a c t This paper presents a quantitative reliability and availability evaluation method for subsea blowout pre-venter (BOP) system by translating fault tree (FT) into dynamic Bayesian networks (DBN) directly, taking account of(More)
A multi-source information fusion based fault diagnosis methodology is proposed. The diagnosis model is obtained by combining two proposed Bayesian networks. The proposed model can increase the fault diagnostic accuracy for single fault. The model can correct the wrong results for multiple-simultaneous faults. a b s t r a c t In order to increase the(More)
This paper proposes a fault diagnosis methodology for a gear pump based on the ensemble empirical mode decomposition (EEMD) method and the Bayesian network. Essentially, the presented scheme is a multi-source information fusion based methodology. Compared with the conventional fault diagnosis with only EEMD, the proposed method is able to take advantage of(More)
The work presents a dynamic Bayesian networks (DBN) modeling of series, parallel and 2-out-of-3 (2oo3) voting systems, taking account of common-cause failure, imperfect coverage, imperfect repair and preventive maintenance. Seven basic events of one, two or three component failure are proposed to model the common-cause failure of the(More)
A framework for the reliability evaluation of grid-connected PV (photovoltaic) systems with intermittent faults is proposed using DBNs (dynamic Bayesian networks). A three-state Markov model is constructed to represent the state transition relationship of no faults, intermittent faults, and permanent faults for PV components. The model is subsequently fused(More)
In order to research the influence of hidden layer neurons of artificial neural network(ANN) and switching frequency of power switches on the performance of permanent magnet synchronous motor(PMSM), a algorithm of space vector pulse width modulation based on artificial neural network (ANN-SVPWM) is proposed. The simulation and experiment of closed-loop PMSM(More)
Transient fault (TF) and intermittent fault (IF) of complex electronic systems are difficult to diagnose. As the performance of electronic products degrades over time, the results of fault diagnosis could be different at different times for the given identical fault symptoms. A dynamic Bayesian network (DBN)-based fault diagnosis methodology in the presence(More)