| Co-Investigator(Kenkyū-buntansha) |
ZHA Hong-Bin Kyushu Institute of Technology Faculty of Comp. Sci. Sys. Eng. Research Assistan, 情報工学部, 助手 (80225680)
UCHINO Eiji Kyushu Institute of Technology Faculty of Comp. Sci. Sys. Eng. Associate Profess, 情報工学部, 助教授 (30168710)
INOUE Katsuhiro Kyushu Institute of Technology Faculty of Comp. Sci. Sys. Eng. Associate Profess, 情報工学部, 助教授 (00150516)
WADA Kiyoshi Kyushu University Faculty of Eng. Associate Professor, 工学部, 助教授 (60125127)
SAGARA Setsuo Kyushu University Faculty of Eng. Professor, 工学部, 教授 (60037679)
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| Research Abstract |
In this research project, developments of model-based failure diagnosis methods and their application studies have been carried out for the following 4-types of dynamic systems,
(1) Lumped parameter Linear Systems Described by State-Space Model
(2) Processes with Black-Box Type Representation
(3) Large-Scale Systems like an Electric Power Plant
(4) Distributed Parameter Systems.
Research results of the project obtained for each system are summarized as follows :
(1) A hierarchical diagnosis system which can be performed on line has been developed by using parallel Kalman filter and generalized likelihood ratio (GLR) test. Furthermore, several methods for directly estimating physical parameters of continuous time linear systems have been proposed by a combinational use of the numerical integration or infinite impulse digital filter approach and the recursive identification algorithms. The applicability of the estimator to failure diagnosis problem has also been confirmed through the simulatio
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(2) First, in order to investigate the convergence and the numerical instability in many kinds of existing recursive identification algorithms, which are used for failure diagnosis, a soft-ware package of CAD system has been manufactured on the personal computer. Next, for adaptively controlled systems, a method of on-line diagnosis method has been proposed by using Kullback discrimination information as the detection index. Furthermore a diagnosis method using fuzzy inference to decide whether the detected system parameter changes are due to a failure or not tas also been developed. In particular, the method can be considered as a new one, so called "Knowledge Aided Model-Based Diagnosis", which effectively incorporates available knowledge about the system operating behavior and the failure modes into the model-based diagnosis.
(3) Two diagnosis methods of controlled deaerator system in the thermal power plant has been developed. The one is a method using a linearized perturbation model and GLR test, and the other is a simulator-based method with small parameter adjusting scheme, and their effectiveness has been confirmed for the model of a practical thermal power plant.
(4) Several methods for estimation and identification of state variables, system parameters and unknown boundary conditions have been proposed for parabolic and/or hyperbolic type of distributed parameter systems. On the other hand their applicability to diagnosis problems are on being investigated. Less
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