Bayesian Networks Modeling Based on Small Samples for VariationSource Diagnosis

Abstract

Abstract: Based on the small samples collected in the assembly process, a new approach based on Bayesian networks was proposed for the variationsource diagnsosis. The conditional independence testing algorithm was proposed to obtain the structure of Bayesian networks. After the prior conditonal probabilities are calculated based on the mapping of the variation simulation model, posterior conditonal probabilities are updated by incorporating the small sample data. The results of the body side case show the method is effective and acurate for fixture fault diangosis.

Key words: assembly variation, Bayesian networks, fault diagnosis

CLC Number:

TH 161

LIU Yin-Hua, JIN Sun. Bayesian Networks Modeling Based on Small Samples for VariationSource Diagnosis[J]. Journal of Shanghai Jiaotong University, 2012, 46(05): 701-705.

References

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