| dc.contributor.author |
Mesbah, M |
|
| dc.contributor.author |
Boashash, B |
|
| dc.contributor.author |
Mathew, J |
|
| dc.date.accessioned |
2012-03-06T18:55:42Z |
|
| dc.date.available |
2012-03-06T18:55:42Z |
|
| dc.date.issued |
2003 |
|
| dc.identifier.citation |
Time-Frequency Signal Analysis & Processing: A Comprehensive Reference, Elsevier Science, Oxford, 2003, Chapter 15, Article 15.6, pages 671-682 |
en_US |
| dc.identifier.isbn |
0080443354 |
|
| dc.identifier.isbn |
9780080443355 |
|
| dc.identifier.uri |
http://hdl.handle.net/10576/10799 |
|
| dc.description |
This Article shows that time-frequency analysis methods are applicable to the area of machine condition monitoring and diagnosis such as detection, classification, and monitoring the progression of the faults and wear with time for prediction and prevention of failures.
(Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354).
In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). |
en_US |
| dc.description.abstract |
Time-frequency analysis methods are applicable to the area of machine condition
monitoring and diagnosis. They are capable of efficiently and unambiguously char-
acterizing a large number of faults. TFA methods are used for detection, classi-
fication, and monitoring the progression of the faults and wear with time. This
enables prediction and prevention of catastrophic failures. Time-frequency analysis
techniques, in the form of either TFD or WT, are used as both visual indicators
of the presence of faults and as a feature extractor in a fully automated pattern
recognition process.
Articles 11.2 and 15.2 of this book describe two other time-frequency approaches
to machine condition monitoring. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Elsevier |
en_US |
| dc.subject |
time-frequency analysis |
en_US |
| dc.subject |
fault detection |
en_US |
| dc.subject |
time-frequency distributions |
en_US |
| dc.subject |
TFDs |
en_US |
| dc.subject |
Feature extraction |
en_US |
| dc.subject |
Quadratic TFDs |
en_US |
| dc.subject |
Gearbox fault detection |
en_US |
| dc.subject |
WVD |
en_US |
| dc.subject |
Wigner-Ville Distribution |
en_US |
| dc.subject |
Wavelet transform |
en_US |
| dc.subject |
vibration signal |
en_US |
| dc.subject |
rotating machinery |
en_US |
| dc.subject |
Bearing fault transient |
en_US |
| dc.title |
Time-Frequency Based Machine Condition Monitoring and Fault Diagnosis |
en_US |
| dc.type |
Book chapter |
en_US |