Article ID: | iaor19932131 |
Country: | Japan |
Volume: | 37 |
Issue: | 2 |
Start Page Number: | 64 |
End Page Number: | 69 |
Publication Date: | Feb 1992 |
Journal: | Communications of the Operations Research Society of Japan |
Authors: | Hosaka Shigetaka, Takami Isao |
Keywords: | artificial intelligence |
The fault diagnosis method using the fault trees for diagnosis is developed, which describes the relationships among the faults, causes and observations. In this method, the causes and their probabilities are estimated by the fault trees for diagnosis and the data of observations. The probabilities of causes are calculated with the failure rate of them, and with Fussell-Vesely importance which is used in the Fault Tree Analysis. The authors have developed a fault diagnostic method using a series of multi-matrix which have the knowledge of diagnostic objects. In this paper, they propose and evaluate the following items: the calculation method with the certain factors of the causes that uses the expanded Bayesian approach, the handling method of unknown relations of causes and results, the calculation method of certain factors in series of multi-matrix, the order control method of answering the questions. [In Japanese.]