摘要
利用概率神经网络对发动机故障进行诊断,建立了发动机故障诊断的概率神经网络模型,利用MATLAB对网络进行训练,并运用测试样本对网络性能进行测试.结果表明,该网络学习速度快、诊断准确率高、泛化能力强,可以对系统进行实时监测和诊断.
A probabilistic neural network was used in fault diagnosis of engines. The model of probabilistic neural networks was set up and trained by MATLAB. The sample data were tested in the networks. The results showed that this network was rapid, precise and full of powerful generalization ability and ease for the real time detection and fault diagnosis.
出处
《河南教育学院学报（自然科学版）》
2012年第3期37-40,共4页
Journal of Henan Institute of Education(Natural Science Edition)
基金
河南省教育厅科学技术研究重点项目(12A510009)
关键词
概率神经网络
发动机
故障诊断
probabilistic neural network
engine
fault diagnosis
作者简介
作者简介：肖玉玲（1970-），女，河南郑州人，河南化工职业学院机械电子系高级讲师
