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Fuzzy neural network fault diagnosis and online vibration monitoring system for the coal scraper conveyor based on rough set theory

机译:基于粗糙集理论的煤刮刀输送机模糊神经网络故障诊断与在线振动监测系统

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In order to produce in safety and avoid the accidents, which is caused by electromechanical failure in the coal large transport equipments, the fuzzy neural network fault diagnosis scheme based on rough set theory is proposed in this paper and the online fault monitoring system for the scraper conveyor is designed. The whole system monitoring model is introduced. The weak signal of mechanical vibration detection by Duffing chaotic oscillator is adopted. And the principle combining rough set and fuzzy neural network is described to realize the on-line fault monitoring. The feasibility and superiority of the scenario are verified so as to achieve a fault diagnosis and on-line monitoring.
机译:为了在安全性并避免由煤大型运输设备中的机电故障引起的事故,本文提出了基于粗糙集理论的模糊神经网络故障诊断方案,以及用于刮刀的在线故障监测系统传送带设计。介绍了整个系统监测模型。采用Duffing混沌振荡器的机械振动检测弱信号。描述了粗糙集和模糊神经网络的原理来实现在线故障监控。验证了场景的可行性和优越性,以实现故障诊断和在线监控。

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