1992 Fiscal Year Final Research Report Summary
Development of vibrational diagnosis system and creation of fault mode in rotating machinery
Project/Area Number |
03452140
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Research Category |
Grant-in-Aid for General Scientific Research (B)
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Allocation Type | Single-year Grants |
Research Field |
機械力学・制御工学
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Research Institution | Kobe University |
Principal Investigator |
IWATSUBO Takuzo Kobe University, Faculty of Engineering, Professor, 工学部, 教授 (00031097)
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Co-Investigator(Kenkyū-buntansha) |
ADACHI Kazuhiko Kobe University, Faculty of Engineering, Research Associate, 工学部, 助手 (30243322)
KAWAMURA Shozo Kobe University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (00204777)
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Project Period (FY) |
1991 – 1992
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Keywords | Rotating machinery / Failure mode / Diagnosis method / Fuzzy logic / Neural network |
Research Abstract |
It is a most effective way to protect the power plants or chemical plants from the big accidents that we predict the accident theoretically or find the accident at the initial stage of the faults. In order to achieve the above matters, the investigations were performed for the following objects. (1) Establishment of predicting method of fault modes from the viewpoints of function and stracture of rotating machinery. (2) Establishment of precise estimating technique by using the Bay's theory, in which the discrepancy of measurement vibrational data by the difference of measuring points of the rotating machinery are made clear. (3) Development of automatic diagnostic algorithm by using the expart system or neural network theory. As the results, the data base for the cause of the fault are established and the expart diagnostic systems by using the matrix counting method, fuzzy theory, Bay's theory and the neural network system are built up. That is, the analysis of diagnostic process by the specialist and the development of the modeling of the diagnostic process are built up by using the expart system technique. In practical case, main diagnostic computer program are finished, in which subsystem for different types of diagnostic algorithm, these are, the matrix counting method, fuzzy theory, Bay's theory and neural network theory can be added in order to compare with each other. In the diagnostic method, creation of fault modes and its relation to the vibration phenomena are clarified from the engineering point of view. Moreover realizations of Bay's diagnostic technique and the neural network technique to the precise diagnosis are accomplished.
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