A hybrid neural network and expert system for monitoring fossil fuel power plants

T. Kraft, K. Okagaki, R. Ishii, P. Surko, A. Brandon, A. DeWeese, S. Peterson, R. Bjordal
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引用次数: 6

Abstract

A fully recurrent neural network and a rule-based expert system are combined in a hybrid architecture to provide power plant operators with an intelligent on-line advisory system. Its purpose is to alert the operator to impending or occurring abnormal conditions related to the plant's boiler. The hybrid system is trained to provide a model of the boiler under normal operation, while the rules address a general set of diagnostic events. Deviation from normal conditions trigger rules to suggest corrective action. This system is intended to increase plant availability and efficiency by automatically deducing abnormal boiler conditions before they become critical.<>
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化石燃料电厂监测的混合神经网络与专家系统
将全递归神经网络和基于规则的专家系统结合在一个混合体系结构中,为电厂运营商提供智能在线咨询系统。其目的是提醒操作人员注意即将发生或正在发生的与电厂锅炉有关的异常情况。混合系统被训练为提供锅炉在正常运行下的模型,而规则则处理一组一般的诊断事件。偏离正常状态触发规则建议纠正措施。该系统旨在提高工厂的可用性和效率,通过自动扣除异常锅炉条件,在他们成为关键之前。
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