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| Received:May 11, 2006Revised:May 13, 2008 |
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| Fault detection and identification based on combining logic and model in a wall-climbing robot |
| Yong JIANG, Hongguang WANG, Lijin FANG, Mingyang ZHAO |
| (State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang Liaoning 110016, China;
Graduate School of the Chinese Academy of Sciences, Beijing 100039, China) |
| Abstract: |
| A combined logic- and model-based approach to fault detection and identification (FDI) in a suction foot control system of a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis. Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the system by evaluating the basic events (elementary causes), which can lead to a root event (a particular fault). Then, a multiple-model adaptive estimation algorithm is used to detect and identify the model-known faults. Finally, based on the system states of the robot and the results of the estimation, the model-unknown faults are also identified using logical reasoning. Experiments show that the proposed approach based on the combination of logical reasoning and model estimating is efficient in the FDI of the robot. |
| Key words: FDI Fault tree Model estimation Logic reasoning Wall-climbing robot |
