The Fault Prediction of Aerospace Equipment PHM technology and its demonstrated failure prediction module simulation

摘要：

Prognostics and Health Management Technology (PHM) will make up the deficiencies of current device monitoring and fault diagnosis, especially the lack of fault prediction. Its combination with the neural network can provide a universal theory and technology of the intelligence prediction. Though the experiments, we establish the BP neural network, as well as the most suitable prediction model. After testing data verification, neural networks can accurately predict the status of the equipment, and the health trends in the future. With the network we can accurately predict the system state, remaining life for the aerospace equipment, make it possible to provide maintenance in time, reduce failure losses and improve reliability.

关键词： Fault prediction PHM Neural network prediction L-M algorithm BP algorithm

作者: Ni Li Zhenhua Li

作者单位: The School of Computer Science,China University of Geosciences Wuhan,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 247-251

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）