Sensor placement for fault diagnosis using genetic algorithm

• Main Authors: Chi, Guoyi, Wang, Danwei, Yu, Ming, Alavi, Marjan, Le, Tung, Luo, Ming
• 其他作者: School of Electrical and Electronic Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2013
• 主題: DRNTU::Engineering::Electrical and electronic engineering
• 在線閱讀: https://hdl.handle.net/10356/102788; http://hdl.handle.net/10220/16441

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.