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投稿时间：2019-12-20
投稿时间：2019-12-20
中文摘要: 燃气轮机控制系统在电厂安全运行中起到重要作用，而传感器作为控制系统中的测量信号装置，其安全性至关重要，因此开展对燃气轮机控制系统传感器的故障诊断研究具有重要意义。在传感器故障诊断中，需要从故障信息中提取出有效的诊断规则。为了解决这一问题，提出了一种改进离散化方法对数据进行预处理，结合粗糙集（RS）和径向基（RBF）神经网络对传感器进行故障诊断研究。实验结果表明，该方法减少了燃气轮机控制系统传感器故障类型的误判率。
Abstract:The gas turbine control system plays an important role in the safe operation of the power plant,and the sensor,as the measuring signal device in the control system,is of vital importance in safety.Therefore,it is of great significance to carry out the fault diagnosis research on the sensor of the gas turbine control system.In sensor fault diagnosis,it is necessary to extract effective diagnosis rules from fault information.In order to solve this problem,an improved discretization method is proposed to preprocess data,and the sensor fault diagnosis is studied by combining RS(rough set)and RBF(radial basis function) neural network.The experimental results show that this method can reduce the misjudgment rate of sensor fault types in gas turbine control system.
keywords: gas turbine control system discretization rough set radial basis function neural network fault diagnosis
文章编号：20211004 中图分类号：TM621.6 文献标志码：
基金项目:国家科技重大专项（2017-V-0011-0063）；上海市"科技创新行动计划"地方院校能力建设专项项目（19020500700）。
引用文本：
云世豪,涂煊,彭道刚,等.基于RS-RBF的燃气轮机控制系统传感器故障诊断研究[J].上海电力大学学报,2021,37(1):17-22.
YUN Shihao,TU Xuan,PENG Daogang,et al.Research on Sensor Fault Diagnosis of Gas Turbine Control System Based on RS-RBF[J].Journal of Shanghai University of Electric Power,2021,37(1):17-22.
云世豪,涂煊,彭道刚,等.基于RS-RBF的燃气轮机控制系统传感器故障诊断研究[J].上海电力大学学报,2021,37(1):17-22.
YUN Shihao,TU Xuan,PENG Daogang,et al.Research on Sensor Fault Diagnosis of Gas Turbine Control System Based on RS-RBF[J].Journal of Shanghai University of Electric Power,2021,37(1):17-22.