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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:基于粗糙集理论的刮板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:为了安全生产并避免由于煤矿大型运输设备的机电故障引起的事故,提出了基于粗糙集理论的模糊神经网络故障诊断方案和刮板在线故障监测系统。设计了输送机。介绍了整个系统的监控模型。采用Duffing混沌振荡器检测机械振动的微弱信号。阐述了粗糙集与模糊神经网络相结合的原理,实现了在线故障监测。验证了该方案的可行性和优越性,以实现故障诊断和在线监控。

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