DocumentCode :
3510016
Title :
Optimization of symptom observation matrix in vibration condition monitoring
Author :
Cempel, Czeslaw
Author_Institution :
Poznan Univ. of Technol., Poznan, Poland
fYear :
2009
fDate :
20-24 July 2009
Firstpage :
944
Lastpage :
950
Abstract :
In diagnostics of complex machines, for their condition assessment we often use many dasiawould bepsila symptoms at the beginning, especially at the diagnostic startup of a new machine. The discrete observation of this dasiawould bepsila symptom vector creates so called symptom observation matrix (SOM). Using next the singular value decomposition (SVD) for the given SOM, one can extract the generalized fault symptoms, describing the fault evolution in a given case, and also diagnostic contribution of measured symptoms. Using the symptom reliability concepts further, and the grey system forecast methodology, it is possible to asses the generalized symptoms limit value. In this way one can establish the needed dimensionality of symptom observation matrix, and moreover assess the residual system life. However, doing this we have to establish new criteria for the dimensionality of SOM, based not on the number of symptoms in use, but the quality of diagnostic decision. This concept was verified in the paper using the data taken from real cases of vibration condition monitoring practice.
Keywords :
condition monitoring; fault diagnosis; grey systems; machinery; optimisation; reliability; singular value decomposition; vibrations; fault diagnosis; grey system forecast methodology; machine condition monitoring; optimization; singular value decomposition; symptom observation matrix; symptom reliability concept; vibration condition monitoring; Condition monitoring; Degradation; Electric breakdown; Matrix decomposition; Multidimensional signal processing; Multidimensional systems; Principal component analysis; Redundancy; Signal processing; Singular value decomposition; diagnosis quality; grey system; machine condition; multidimensional monitoring; rolling forecasting; singular value decomposition (SVD);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reliability, Maintainability and Safety, 2009. ICRMS 2009. 8th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4903-3
Electronic_ISBN :
978-1-4244-4905-7
Type :
conf
DOI :
10.1109/ICRMS.2009.5269973
Filename :
5269973
Link To Document :
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