NDLI: The normalization PCA model and its application under the periodic non-steady conditions

Content Provider	IEEE Xplore Digital Library
Author	Wang Tian-zhen Xu Man Tang Tian-hao
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Autom., Shanghai Maritime Univ., Shanghai, China (Wang Tian-zhen; Xu Man; Tang Tian-hao)
Abstract	The principal component analysis method is usually used for fault detection under the steady conditions, however, when system works under the non-steady conditions, the false alarm rate and the missing alarm rate, tested by the $T^{2}$ control limit, are so high. The main reason for this situation is that the sampled data is accord with normal distribution under the steady conditions, whereas the data mostly does not satisfy normal distribution under the non-steady conditions, but $T^{2}$ control limit can only detection fault effectively for the data conforming to normal distribution. So this paper firstly analyzes two characteristics of the periodic non-steady conditions and mathematical theory and Q-Q figures have verified the characteristics, then a normalization PCA (NPCA) is proposed. Finally it is applied to the system of the motor cyclical process and alleviating the load, the test result is good and can verify the effectiveness of the model.
Sponsorship	IEEE Control Syst. Soc.
Starting Page	4313
Ending Page	4318
File Size	367158
Page Count	6
File Format	PDF
ISBN	9781467355339
e-ISBN	9781467355346
DOI	10.1109/CCDC.2013.6561710
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	$T^{2}$ Control Limit Q-Q Figures Automation Fault Detection Fault detection NPCA Abstracts Gaussian distribution Educational institutions Electronic mail Principal component analysis PCA
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

The normalization PCA model and its application in fault detection of wind power generation system

Fault detection method based on principal component analysis and kernel density estimation and its application

A fault detection method based on dynamic peakvalley limit under the non-steady conditions

A multi-model anomaly detection method

Multi-space PCA with its application in fault diagnosis

The research of fault diagnosis method based on weighted Q contribution plot and SDG

Multi-level PCA and its application in fault diagnosis

Autoregressive total projection to latent structures for process monitoring

Adaptive PCA based fault diagnosis scheme in imperial smelting process

The normalization PCA model and its application under the periodic non-steady conditions

Similar Documents

The normalization PCA model and its application in fault detection of wind power generation system

Fault detection method based on principal component analysis and kernel density estimation and its application

A fault detection method based on dynamic peakvalley limit under the non-steady conditions

A multi-model anomaly detection method

Multi-space PCA with its application in fault diagnosis

The research of fault diagnosis method based on weighted Q contribution plot and SDG

Multi-level PCA and its application in fault diagnosis

Autoregressive total projection to latent structures for process monitoring

Adaptive PCA based fault diagnosis scheme in imperial smelting process

The normalization PCA model and its application under the periodic non-steady conditions