Incipient fault diagnosis and amplitude estimation based on K-L divergence with a Gaussian mixture model

doi:10.1063/5.0003535

	Incipient fault diagnosis and amplitude estimation based on K-L divergence with a Gaussian mixture model
	Jiang, Dongnian 1,3; Li, Wei 2,3; Shen, Fuyuan 2,3
刊名	Review of Scientific Instruments
	2020-05-01
卷号	91 期号:5
关键词	Failure analysis Fault detection Fault tolerance
ISSN号	00346748
DOI	10.1063/5.0003535
英文摘要	In this paper, a method of incipient fault diagnosis and amplitude estimation based on Kullback-Leibler (K-L) divergence is proposed. An incipient fault is usually regarded as the precursor of a significant system fault, but due to a low amplitude and non-obvious characteristics, it is easy for such a fault to be hidden by disturbance and noise. Based on this and considering the sensitivity of the K-L divergence method in data feature extraction, a method of diagnosing incipient faults is designed. In order to consider the safety performance and lay a foundation for the fault tolerance of the system, an amplitude estimation method for incipient faults is also proposed. By mapping the characteristic change in the residual data to the numerical change in the K-L divergence, the amplitude of the incipient fault can be measured with high sensitivity. Considering the generality of the method, a Gaussian mixture model is used to model the residual data in order to increase the accuracy of fault amplitude estimation. Finally, the effectiveness of the proposed method for incipient fault diagnosis and amplitude estimation is verified by experiment. © 2020 Author(s).
WOS研究方向	Instruments & Instrumentation ; Physics
语种	英语
出版者	American Institute of Physics Inc.
WOS记录号	WOS:000533972000001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/151214]
专题	电气工程与信息工程学院
作者单位	1.State Grid Gansu Electric Power Research Institute, State Grid Gansu Power Company, Lanzhou; 730050, China; 2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou; 730050, China 3.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China;
推荐引用方式 GB/T 7714	Jiang, Dongnian,Li, Wei,Shen, Fuyuan. Incipient fault diagnosis and amplitude estimation based on K-L divergence with a Gaussian mixture model[J]. Review of Scientific Instruments,2020,91(5).
APA	Jiang, Dongnian,Li, Wei,&Shen, Fuyuan.(2020).Incipient fault diagnosis and amplitude estimation based on K-L divergence with a Gaussian mixture model.Review of Scientific Instruments,91(5).
MLA	Jiang, Dongnian,et al."Incipient fault diagnosis and amplitude estimation based on K-L divergence with a Gaussian mixture model".Review of Scientific Instruments 91.5(2020).