Method and apparatus for generating motor current spectra to enhance motor system fault detection
Abstract
A method and circuitry for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate at which samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed.
 Inventors:

 Knoxville, TN
 Oak Ridge, TN
 Issue Date:
 Research Org.:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 OSTI Identifier:
 870131
 Patent Number(s):
 5461329
 Assignee:
 Martin Marietta Energy Systems, Inc. (Oak Ridge, TN)
 DOE Contract Number:
 AC0584OR21400
 Resource Type:
 Patent
 Country of Publication:
 United States
 Language:
 English
 Subject:
 method; apparatus; generating; motor; current; spectra; enhance; fault; detection; circuitry; sampling; periodic; amplitude; modulations; nonstationary; carrier; wave; determine; frequencies; circuit; described; terms; improved; signature; analysis; insures; sampled; data; set; contains; exact; cycles; defining; rate; samples; collected; containing; stationary; waves; recreated; analog; signal; conditioning; adjust; frequency; variations; transformed; domain; via; discrete; fourier; transform; distribution; components; due; harmonics; minimized; signals; easily; analyzed; carrier wave; frequency domain; fourier transform; motor current; data set; current signal; fault detection; amplitude modulation; sampling rate; signature analysis; current data; current signature; frequency distribution; current spectra; /324/702/
Citation Formats
Linehan, Daniel J, Bunch, Stanley L, and Lyster, Carl T. Method and apparatus for generating motor current spectra to enhance motor system fault detection. United States: N. p., 1995.
Web.
Linehan, Daniel J, Bunch, Stanley L, & Lyster, Carl T. Method and apparatus for generating motor current spectra to enhance motor system fault detection. United States.
Linehan, Daniel J, Bunch, Stanley L, and Lyster, Carl T. Sun .
"Method and apparatus for generating motor current spectra to enhance motor system fault detection". United States. https://www.osti.gov/servlets/purl/870131.
@article{osti_870131,
title = {Method and apparatus for generating motor current spectra to enhance motor system fault detection},
author = {Linehan, Daniel J and Bunch, Stanley L and Lyster, Carl T},
abstractNote = {A method and circuitry for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate at which samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1995},
month = {1}
}