NDLI: Intelligent Recognition of Gearbox Status by Wavelet Packet Decomposition

Content Provider	IEEE Xplore Digital Library
Author	Feizi-Derakhshi, M. Derakhshan, M.R.P.
Copyright Year	2010
Abstract	Energy level of signal is one of the characteristics which its ability to recognize condition of equipment, has been verified and proved. Fault in rotating devices affects the energy level of signal and its distribution type. Thus energy is an important feature for condition monitoring of rotating devices. Entropy is a concept to express uncertainly of random variables and Shannon entropy is one of most widely used manner to measure it. Data used in this research is from car gearbox in which many different pieces are involved. Data has also been collected in industrial environment. So the added noise is more than that would be the case if it was collected in laboratory condition with simple equipments containing few pieces. So the energy of these noises can significantly affect the energy level of the main signal and cause difficulty, in recognition. In contrast entropy only depends on the scatter of used data and a little change in level and distribution does not affect entropy. Data in this research has been collected from 20 car gearboxes which have been analyzed by 50 different wavelets to measure their energy and entropy as feature vector along with RBF neural network and support vector machine in recognition of the safe and damaged gearboxes. The mean and best recognition result was 57.8 and 65 percent for energy and RBF network, 59.9 and 70 percent for energy and support vector machine, 65.9 and 85 percent for entropy and RBF network and finally 71.4 and 90 percent for entropy and support vector machine. These results indicate is that entropy outperforms energy and support vector machine outperforms RBF network in condition monitoring of gearboxes.
Starting Page	446
Ending Page	450
File Size	632828
Page Count	5
File Format	PDF
ISBN	9781424475476
e-ISBN	9781424475483
DOI	10.1109/CIT.2010.102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-29
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Condition monitoring Gears entropy Noise Radial basis function networks Feature extraction Entropy Energy of signal
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

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