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Structural health monitoring system based on multi-agent coordination and fusion for large structure
Affiliation:1. Department of Aeronautics, Xiamen University, South Siming Road 422#, Xiamen 361005, People’s Republic of China;2. The State Key Lab of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Yu Dao Street 29#, Nanjing 210016, People’s Republic of China;1. Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China;2. Shenzhen Key Laboratory of Urban Planning and Decision-Making Simulation, Shenzhen, China;1. School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China;2. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Abstract:In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.
Keywords:Structural health monitoring  Damage identification  Multi-agent  Fusion  Coordination  Strain distribution  Joint failure  Large structure
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