NDLI: Similarity based modeling of time synchronous averaged vibration signals for machinery health monitoring

Content Provider	IEEE Xplore Digital Library
Author	Wegerich, S.W.
Copyright Year	2004
Description	Author affiliation: SmartSignal Corp., Lisle, IL, USA (Wegerich, S.W.)
Abstract	Monitoring rotating machinery is often accomplished with the aid of vibration sensors. The vibration sensor signals contain a wealth of complex information that characterizes the dynamic behavior of the machinery. Transforming this information into useful knowledge about the health of the machine can be challenging due to the presence of extraneous noise sources and variations in the vibration signal itself. This is particularly true in situations in which the rotating machinery is monitored under varying loads and/or speeds. In order for any gained knowledge or insight into the health of machinery to be useful, it must be actionable. This is achieved by detecting incipient faults as early as possible. A novel approach to vibration monitoring that employs a multivariate similarity-based modeling (SBM) technique to characterize the expected behavior of time synchronous averaged spectral features is shown to enable the detection in rotating machinery. This in turn facilitates the assessment of machine health and enables fault diagnostics and ultimately prognostics. SBM has been applied successfully to a variety of non-vibration related multi-sensor, health monitoring applications. Our new approach builds off of these experiences and a combination of signal processing algorithms to expand the overall applicability of SBM into single sensor vibration monitoring. We discuss an approach to gearbox fault monitoring using vibration data and SBM. This new approach is described in detail and is applied to actual H-60 gearbox vibration data acquired from seeded fault tests conducted by U.S. Naval Air Systems Command (NAVAIR) at the Helicopter Transmission Test Facility (HTTF) in Patuxent River, MD in 2001 and 2002.
Sponsorship	Aerosp. and Electron. Syst. Soc
Starting Page	3654
Ending Page	3662
File Size	627508
Page Count	9
File Format	PDF
ISBN	0780381556
ISSN	1095323X
DOI	10.1109/AERO.2004.1368182
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-03-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Machinery Condition monitoring Sensor phenomena and characterization Fault detection Milling machines Shafts Diesel engines Temperature sensors Signal processing algorithms Testing
Content Type	Text
Resource Type	Article
Subject	Aerospace Engineering Space and Planetary Science

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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
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