中国机械工程Issue(16)：2159-2162,2163,5.DOI:10.3969/j.issn.1004-132X.2014.16.005
量子 BP 神经网络在发动机故障诊断中的应用
Applications of Quantum BP Neural Network in Engine Fault Diagnosis
摘要
Abstract
In order to solve the problem of slow convergence speed and low classification accuracy in common BP neural network (CBPN),a model of quantum BP neural network (QBPN)was pro-posed.Quantum computation was introduced into CBPN.The structure of QBPN contained input lay-er,hidden layer and output layer,where input and transfer function were represented by quantum bit, and the output was real value.Firstly,the real-valued training samples were transformed into quantum training samples,which was as the input.Then,with transfer function,the quantum weights were cal-culated,and the network parameters were updated to achieve the required result.Finally,the trained network was used for fault diagnosis,and the result was output in real value.The proposed method was applied in fault diagnosis of engine.The results indicate that,compared with CBPN,QBPN has great advantages of convergence speed,classification accuracy and executing time.关键词
量子计算/量子神经网络/发动机/故障诊断Key words
quantum computation/quantum neural network/engine/fault diagnosis分类
机械制造引用本文复制引用
李胜,张培林,李兵,李琛..量子 BP 神经网络在发动机故障诊断中的应用[J].中国机械工程,2014,(16):2159-2162,2163,5.基金项目
国家自然科学基金资助项目(E51205405) （E51205405）
