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Title: Sensor placement for fault diagnosis using genetic algorithm
Authors: Chi, Guoyi
Wang, Danwei
Yu, Ming
Alavi, Marjan
Le, Tung
Luo, Ming
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Chi, G., Wang, D., Yu, M., Alavi, M., Le, T., & Luo, M. (2012). Sensor placement for fault diagnosis using genetic algorithm. 2012 IEEE 17th Conference on Emerging Technologies & Factory Automation (ETFA), pp.1-7.
Abstract: This paper presents a novel methodology for the purpose of fault detection and isolation (FDI) to a two-tank system. This new methodology benefits from the basic facts that faults are embedded in the analytical redundancy relations (ARRs) and that the occurrence of a fault will cause the corresponding ARRs to change. Based on these facts, the minimal isolation set as an important concept is introduced to make each fault in the fault set F detectable and isolable. Then, the sensor placement problem consists in determining an optimal minimal isolation set associated with the least number of sensors. A dedicated genetic algorithm is developed to solve the formulated sensor placement problem. A case study of a two-tank system shows that the proposed methodology performs well.
DOI: 10.1109/ETFA.2012.6489615
Rights: © 2012 IEEE
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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