期刊论文

Zou, Shu-Liang

英文

Applied Sciences-Basel

2076-3417

2018

8

5

838-

10.3390/app8050838

Acknowledgments: This paper is supported by the Double First–class Project on Nuclear Safety Management Science and Engineering of University of South China and the Major Projects of Science and Technology in Hunan Province (No. 2012FJ1007). The authors would like to thank the University of South China and their colleagues for their support and contributions during the development of this work.

本校为第一且通讯机构

Shearing machines are the key pieces of equipment for spent-fuel reprocessing in commercial reactors. Once a failure happens and is not detected in time, serious consequences will arise. It is very important to monitor the shearing machine and to diagnose the faults immediately for spent-fuel reprocessing. In this study, an intelligent condition monitoring approach for spent nuclear fuel shearing machines based on noise signals was proposed. The approach consists of a feature extraction based on wavelet packet transform (WPT) and a hybrid fault...