时变模糊神经网络及其在航空发动机排气温度预测中的应用  

Time-varying fuzzy neural network and its application in prediction of exhaust gas temperature

作　　者：付旭云 陕振勇[2] 李臻 钟诗胜[2] 

机构地区：[1]哈尔滨工业大学(威海)船舶与海洋工程学院,山东威海264209 [2]哈尔滨工业大学机电工程学院,黑龙江哈尔滨150001

出　　处：《计算机集成制造系统》2014年第4期919-925,共7页Computer Integrated Manufacturing Systems

基　　金：国家863计划资助项目(2012AA040911);国家自然科学基金资助项目(51305096);民航局科技计划资助项目(MHRD201122)~~

摘　　要：为了提高气路参数偏差值预测精度,首先建立了时变模糊推理系统;同时,为了解决模糊推理系统因参数众多而难以实际应用的问题,建立了时变模糊神经网络,并给出了该网络的学习算法。采用Mackey-Glass时间序列对时变模糊神经网络的预测精度进行验证,并将其应用到发动机排气温度偏差值预测中。应用实例表明,时变模糊神经网络能更好地预测排气温度偏差值的变化趋势,为发动机预诊断提供支持。To obtain a better accuracy, the time-varying fuzzy inference system theory was established, and a time-va- rying fuzzy neural network was created to solve the problem that the application was hard realized by too much pa- rameters of the fuzzy inference system. The learning algorithm of the network structure was also designed. Mackey- Glass chaotic time series prediction was used to prove the network prediction accuracy, and the time-varying fuzzy inference system theory was used to predict the exhaust gas temperature deviation. The result showed that the bet- ter variation trend was predicted by proposed network, which could provide support for pre-diagnosis of aero-en- gine.

关 键 词：时变模糊推理系统 时变模糊神经网络 航空发动机 排气温度预测 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]