Prediction of multiple failures for a mobile robot steering system
Fault diagnosis and failure prognosis are critical techniques to improve the safety and reliability of modern complex electromechanical systems. In this paper, a model-based prognosis method is developed to deal with multiple incipient faults in a mobile robot steering system. This method utilizes t...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/102129 http://hdl.handle.net/10220/16373 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Fault diagnosis and failure prognosis are critical techniques to improve the safety and reliability of modern complex electromechanical systems. In this paper, a model-based prognosis method is developed to deal with multiple incipient faults in a mobile robot steering system. This method utilizes the concept of Augmented Global Analytical Redundancy Relations (AGARRs) to handle failures with both parametric and non-parametric nature. In order to realize multiple failures prediction, a multiple Hybrid Particle Swarm Optimization (HPSO) algorithm is proposed. Simulation results verify the effectiveness of the proposed method in a front steering system of a CyCab mobile robot. |
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