A Fault Diagnosis Method for Complex System Based on Hierarchical Bayesian Network

摘要

With basic requirements for fault diagnosis of health management technology-detect and diagnosis fault precisely, decrease CFAR efficiently, make a research from three respects: uncertainty of data, uncertainty of diagnosis result and uncertainty of feature parameter selection. Based on advantages for uncertainty problem of Bayesian network, Hierarchical Bayesian for fault diagnosis is proposed. The existing algorithms are not capable of selecting variables systematically so that they generally use the full model, which may contain unnecessary variables as well as necessary variables. Ignoring this model uncertainty often gives rise to, so called, the smearing effect in solutions. Complexity and difficulty of modeling is increased. The simulation results show this method can get better fault feature, improve fault discernment, and validate the model efficiency.