NDLI: Condition recognition of induction machine under various loads

Content Provider	IEEE Xplore Digital Library
Author	Rong-Ching Wu Ta-Peng Tsao
Copyright Year	1999
Description	Author affiliation: Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan (Rong-Ching Wu)
Abstract	This paper offers a complete method to deal with the condition recognition for induction machines under different loads. In actual operation, the loads of induction machines vary within a certain range. When the signal is transformed into spectrum, the load variation causes band drifts and amplitude variation. The load factor influences the result of recognition seriously. This paper offers band adjustment and feature extraction to solve the recognition problems caused by loads and faults. Employing band adjustment, the method eliminates the phenomenon of band drift under different operation condition. Employing feature extraction, the method decreases the sensitivity of features to loads. Then, load influences on condition recognition for an induction machine will descend to a minimum. The method afforded in this paper is verified by experiment, and proves its feasibility with high accuracy.
Starting Page	603
Ending Page	608
File Size	653230
Page Count	6
File Format	PDF
ISBN	0780357698
DOI	10.1109/PEDS.1999.792671
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-27
Publisher Place	Hong Kong
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Induction machines Signal analysis Signal detection Load management Feature extraction Frequency Vibration measurement Narrowband Sampling methods Time factors
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

Gearbox Monitoring Using Induction Machine Stator Current Analysis

Vibration and stator current spectral analysis of induction machine operating under dynamic eccentricity

Study on feature extraction of high speed precision electric machine vibration signal

Induction machine condition monitoring with higher order spectra. I. Fundamentals and fixed frequency operation

Time-Frequency Classification Applied to Induction Machine Faults Monitoring

Statistical analysis of symbol sequence distributions for machine condition monitoring

Bearing in Induction Machine

Detection of Emotional Expressions in Speech

A novel high-resolution technique for induction machine broken bar detection

Condition recognition of induction machine under various loads

Similar Documents

Gearbox Monitoring Using Induction Machine Stator Current Analysis

Vibration and stator current spectral analysis of induction machine operating under dynamic eccentricity

Study on feature extraction of high speed precision electric machine vibration signal

Induction machine condition monitoring with higher order spectra. I. Fundamentals and fixed frequency operation

Time-Frequency Classification Applied to Induction Machine Faults Monitoring

Statistical analysis of symbol sequence distributions for machine condition monitoring

Bearing in Induction Machine

Detection of Emotional Expressions in Speech

A novel high-resolution technique for induction machine broken bar detection

Condition recognition of induction machine under various loads