SIA OpenIR  > 工业控制网络与系统研究室
Sensor Drift Detection Based on Discrete Wavelet Transform and Grey Models
Han XJ(韩晓佳)1,2,3; Jiang, Jing4; Xu AD(徐皑冬)1,2; Bari, Ataul4; Pei C(裴超)1,2,3; Sun Y(孙越)1,2,3
Department工业控制网络与系统研究室
Source PublicationIEEE ACCESS
ISSN2169-3536
2020
Volume8Pages:204389-204399
Indexed BySCI
WOS IDWOS:000590420200001
Contribution Rank1
Funding OrganizationResearch and Application of Key Technologies for High-Level Safety Integrity Transmitter [2018YFB2004101] ; UCAS Joint Ph.D. Training Program ; Ontario Research Fund Research Excellence 8
KeywordDiscrete wavelet transform fault detection grey models kernel density estimation sensor drift
Abstract

Drift detection has been a difficult problem in the field of sensor fault diagnosis. In this article, a sensor drift detection method using discrete wavelet transform (DWT) and a grey model GM(1,1) is proposed. DWT is used to separate the noise part from the trend part of the sensor data. Then, the GM(1,1) model is used for time series prediction in the trend part. Finally, residuals generated by predicted and current denoised sensor data are calculated and compared with a pre-selected threshold for drift detection. The residuals may not necessarily be Gaussian distribution. Therefore, the pre-selected threshold is chosen by using the kernel density estimation (KDE) method without Gaussian assumption. The effectiveness of the proposed method has been demonstrated using a simulated temperature sensor output from a sensor model on a continuous stirred-tank reactor (CSTR), as well as measurements from a physical temperature sensor in the nuclear power control test facility (NPCTF).

Language英语
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS KeywordFAULT-DETECTION ; DIAGNOSIS ; STRATEGY
WOS Research AreaComputer Science ; Engineering ; Telecommunications
Funding ProjectResearch and Application of Key Technologies for High-Level Safety Integrity Transmitter[2018YFB2004101] ; UCAS Joint Ph.D. Training Program ; Ontario Research Fund Research Excellence 8
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/27954
Collection工业控制网络与系统研究室
Corresponding AuthorXu AD(徐皑冬)
Affiliation1.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
4.Western University, London, Ontario N6A 5B9, Canada
Recommended Citation
GB/T 7714
Han XJ,Jiang, Jing,Xu AD,et al. Sensor Drift Detection Based on Discrete Wavelet Transform and Grey Models[J]. IEEE ACCESS,2020,8:204389-204399.
APA Han XJ,Jiang, Jing,Xu AD,Bari, Ataul,Pei C,&Sun Y.(2020).Sensor Drift Detection Based on Discrete Wavelet Transform and Grey Models.IEEE ACCESS,8,204389-204399.
MLA Han XJ,et al."Sensor Drift Detection Based on Discrete Wavelet Transform and Grey Models".IEEE ACCESS 8(2020):204389-204399.
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