Fault diagnosis of rolling bearing based on S transform and image of invariant moments

doi:10.4028/www.scientific.net/AMR.706-708.798

CORC > 兰州理工大学 > 兰州理工大学

	Fault diagnosis of rolling bearing based on S transform and image of invariant moments
	Guo, Jun Feng; Wang, Bao Zeng; Wei, Peng; Wei, Xing Chun
	2013
会议日期	May 18, 2013 - May 19, 2013
会议地点	XiShuangBanNa, China
关键词	Bearings (machine parts) Failure analysis Image processing Intelligent materials Roller bearings Geometric moment Invariant moment Rolling bearings S-transformation Simulation research Time and frequencies Time-frequency spectrum Two dimensional images
卷号	706-708
DOI	10.4028/www.scientific.net/AMR.706-708.798
页码	798-802
英文摘要	According the characteristics of rolling bearing fault information are nonlinear and non-stationary, the method of time-frequency is often used to make the one dimensional time signal map into two dimensional time and frequency function, and describe the energy density of signal at different times and frequency simultaneously. A method of fault diagnosis based on S transformation and image Hu of invariant moments was put forward in this paper. First of all the measured rolling bearing signals have been S transformed, and time-frequency spectrum which is got is expressed as two dimensional image, then Hu geometric moment invariant of the S transformation spectrum is calculated and the simulation research is carried out using invariant moment principle in image processing. The results show that this method can distinguish the inner ring, outer ring and bearing roller fault intuitively and accurately and measure rolling bearing fault diagnosis efficiently. © (2013) Trans Tech Publications, Switzerland.
会议录	Advanced Materials Research
会议录出版者	Trans Tech Publications Ltd, Kreuzstrasse 10, Zurich-Durnten, CH-8635, Switzerland
语种	英语
ISSN号	10226680
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117578]
专题	兰州理工大学
作者单位	College of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou, China
推荐引用方式 GB/T 7714	Guo, Jun Feng,Wang, Bao Zeng,Wei, Peng,et al. Fault diagnosis of rolling bearing based on S transform and image of invariant moments[C]. 见:. XiShuangBanNa, China. May 18, 2013 - May 19, 2013.