Fault detection with process-identification methods

Isermann, Rolf

doi:10.1007/3-540-30368-5_9

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…Given Z and an estimated number of clusters K, the Gustafson-Kessel fuzzy clustering algorithm [6] is applied to compute the fuzzy partition matrix U. This provides a description of the system in terms of its local characteristic behavior in regions of the data identified by the clustering algorithm, and each cluster defines a rule.…”

Section: Parameter Estimationmentioning

confidence: 99%

Takagi Sugeno fuzzy expert model based soft fault diagnosis for two tank interacting system

Mani¹

2014

Archives of Control Sciences

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Takagi Sugeno fuzzy expert model based soft fault diagnosis for two tank interacting system PANDIYAN MANIKANDAN, MANI GEETHAThe inherent characteristics of fuzzy logic theory make it suitable for fault detection and diagnosis (FDI). Fault detection can benefit from nonlinear fuzzy modeling and fault diagnosis can profit from a transparent reasoning system, which can embed operator experience, but also learn from experimental and/or simulation data. Thus, fuzzy logic-based diagnostic is advantageous since it allows the incorporation of a-priori knowledge and lets the user understand the inference of the system. In this paper, the successful use of a fuzzy FDI based system, based on dynamic fuzzy models for fault detection and diagnosis of an industrial two tank system is presented. The plant data is used for the design and validation of the fuzzy FDI system. The validation results show the effectiveness of this approach.

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Section: Parameter Estimationmentioning

confidence: 99%

Takagi Sugeno fuzzy expert model based soft fault diagnosis for two tank interacting system

Mani¹

2014

Archives of Control Sciences

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Fault Detection Method Using Context-Based Approach

Kalisch

2015

Advances in Intelligent Systems and Computing

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The paper describes the context based and model-free fault detection method. The main purpose of the research is to present that there is the possibility of development of diagnostic schemes using ensemble learning and context based approach to obtain the high efficiency of the fault detection system. The achieved results confirm the effectiveness of the proposed approach and also show its limitations.

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