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Research on a Novel Method Diagnosis and Maintenance for Key Produce Plant Based on MAS and NN

机译:基于MAS和NN的关键农产品新型诊断与维修方法研究。

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As the development of the electrical power market, the maintenance automation has become an intrinsic need to increase the overall economic efficiency of hydropower plants. A Multi-Agent System (MAS) based model for the predictive maintenance system of hydropower plant within the framework of Intelligent Control-Maintenance-Management System (ICMMS) is proposed. All maintenance activities, form data collection through the recommendation of specific maintenance actions, are integrated into the system. In this model, the predictive maintenance system composed of four layers: Signal Collection, Data Processing, Diagnosis and Prognosis, and Maintenance Decision-Making. Using this model a prototype of predictive maintenance for hydropower plant is established. Artificial Neural-Network (NN) is successfully applied to monitor, identify and diagnosis the dynamic performance of the prototype system online.
机译:随着电力市场的发展,维护自动化已成为提高水力发电厂整体经济效率的内在需求。提出了一种在智能控制-维护-管理系统(ICMMS)框架内的基于多代理系统(MAS)的水电厂预测维护系统模型。通过推荐特定维护措施收集数据的所有维护活动都已集成到系统中。在此模型中,预测性维护系统由四层组成:信号收集,数据处理,诊断和预测以及维护决策。使用该模型,建立了水电厂预测性维护的原型。人工神经网络(NN)已成功应用于在线监测,识别和诊断原型系统的动态性能。

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