Fault Diagnosis of Complex System Based on Bayesian Networks

The structure and relationship of components are complicated in complex system, and the test-cost of complex system is high. So, the fault diagnosis of complex system is the decision with uncertainty under small sample. A Bayesian networks (BN) model for fault diagnosis of complex system is built up,furthermore, the Leaky Noisy-OR model is used to reduce the requirements for data and computation complexity. The study shows that the method for fault diagnosis of complex system can utilize all kinds of information, represent knowledge definitely, demand small sample and diagnose the faults accurately. The method can guide the decision for fault diagnosis of complex system.