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Author Lopez, J. A. ♦ Sznaier, M. ♦ Camps, O.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Kernel ♦ Feature extraction ♦ Noise measurement ♦ Mathematical model ♦ Method of moments ♦ Fault detection ♦ Estimation
Abstract We present an unsupervised, data driven method for detecting faults in dynamical systems based upon recent results in polynomial optimization. The proposed technique only requires information about the statistical moments of the normal-state distribution of the system. We demonstrate our method by detecting damage in a bearing test rig.
Description Author affiliation: Department of Electrical & Computer Engineering, Northeastern University, MA 02115, USA (Lopez, J. A.; Sznaier, M.; Camps, O.)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-12-15
Publisher Place Japan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781479978861
Size (in Bytes) 760.88 kB
Page Count 6
Starting Page 3798
Ending Page 3803

Source: IEEE Xplore Digital Library