NDLI: Application of data mining in fault diagnosis of induction motor

Content Provider	IEEE Xplore Digital Library
Author	Panigrahy, Parth Sarathi Konar, Pratyay Chattopadhyay, Paramita
Copyright Year	2016
Description	Author affiliation: Department of Electrical Engineering, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India (Panigrahy, Parth Sarathi; Konar, Pratyay; Chattopadhyay, Paramita)
Abstract	Data driven approaches are gaining popularity in the field of condition monitoring due to their knowledge based fault identification capability for wide range of motor operation. Particularly the method, based on mining the data can encompass the wide behavioral operation of induction motor drive system in industries. Therefore, appropriate low cost instrumentation embedding an efficient algorithm becomes the industrial demand for fault diagnosis of induction motor drive. A hardware friendly algorithm for multi-class fault diagnosis by applying data mining technique is proposed in this paper. Most frequently associated faults like bearing fault, stator inter-turn fault, broken rotor bar fault are investigated for a drive fed induction motor. Discrete wavelet transform-Inverse discrete wavelet transform (DWT-IDWT) algorithm is used to obtain the unique characteristics from each synthesized sub-band and these filtered signals are exploited for feature extraction. A feature selection technique based on Genetic Algorithm (GA) is utilized to identify the potential features for reducing the dimensionality of the feature space. The use of smallest length filter of 2 coefficients (db1) for DWT-IDWT algorithm and 6 relevant features has made the proposed algorithm computationally efficient. The classification accuracy for the investigated multiple faults are found to be quite appreciable. Further, a comparative study is also done using different classifiers: k-NN, MLP and RBF.
Starting Page	274
Ending Page	278
File Size	373718
Page Count	5
File Format	PDF
e-ISBN	9781479917693
DOI	10.1109/CMI.2016.7413754
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	DWT Induction motors Bearing fault Stator inter-turn fault Filter banks Filtering algorithms Feature extraction GA Discrete wavelet transforms Induction motor drive Data mining Genetic algorithms
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

Discrete wavelet transform for stator fault detection in induction motors

Induction motor stator inter-turn fault detection using wavelet transform technique

A novel method for induction motors stator inter-turn short circuit fault diagnosis based on wavelet energy and neural network

Stator inter turns fault detection using discrete wavelet transform

DFA and DWT based severity detection and discrimination of induction motor stator winding short circuit fault from incipient insulation failure

Analysis of inter-turn short circuit fault in 2.5HP 3-phase induction motor

Wavelet aided SVM classifier for stator inter-turn fault monitoring in induction motors

Application of discrete wavelet transform for identification of induction motor stator inter-turn short circuit

DWT-based fault diagnosis in induction motors by using CVA

Application of data mining in fault diagnosis of induction motor

Similar Documents

Discrete wavelet transform for stator fault detection in induction motors

Induction motor stator inter-turn fault detection using wavelet transform technique

A novel method for induction motors stator inter-turn short circuit fault diagnosis based on wavelet energy and neural network

Stator inter turns fault detection using discrete wavelet transform

DFA and DWT based severity detection and discrimination of induction motor stator winding short circuit fault from incipient insulation failure

Analysis of inter-turn short circuit fault in 2.5HP 3-phase induction motor

Wavelet aided SVM classifier for stator inter-turn fault monitoring in induction motors

Application of discrete wavelet transform for identification of induction motor stator inter-turn short circuit

DWT-based fault diagnosis in induction motors by using CVA

Application of data mining in fault diagnosis of induction motor