Abstract
In order to obtain accurate real-time system state recognition under the supervision of the universal mobile internet of things management platform, an intelligent fault diagnosis system is proposed. And the intelligent fault diagnosis system is presentation based on ZigBee technology and particle filter in this paper. Real-time collection of multi-variable data is realized by adopting ZigBee wireless sensor network, and the accurate estimation of the state of monitored objects and intelligent prediction of faults are based on the particle filtering algorithm. The proposed approach is implemented on a circuit fault identification system. The application results show that the proposed approach can achieve the real-time remote monitoring, accurate state estimation and fault diagnosis, meanwhile, effectively enhance applicable scope and diagnostic level of the fault diagnosis system.
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