@article{oai:u-fukui.repo.nii.ac.jp:00024899,
 author = {ASAKURA, Toshiyuki and KOBAYASI, Takashi and HAYASHI, Shoji and XU, Baojie},
 issue = {1},
 journal = {福井大学工学部研究報告},
 month = {Mar},
 note = {This paper describes a method on machine fault diagnosis system using neural networks. As fault diagnosing signal, the sound signal of machine can be used, in which the data is obtained as the power spectrum density through FFT analyzer. First. the structure of fault diagnosis system is shown. Next, in the neural networks, both the normal and abnormal conditions of machine can be learned by back-propagation method and the fault diagnosis system of a machine may be constructed. Finally, through simulation experiments, it was verified that the failure of machine was diagnosed based on the spectrum of sound signal including noise. Also, it was certified that, using the real data of sound signal, the fault diagnosis system proposed here can be applied to the practical machine.},
 pages = {1--10},
 title = {Fault Diagnosis System of Machine Using Neural Networks and Its Application},
 volume = {45},
 year = {1997}
}