Innovative developments in systems condition monitoring

被引:8
|
作者
Cempel, C [1 ]
机构
[1] Poznan Univ Technol, PL-60965 Poznan, Poland
来源
DAMAS 99: DAMAGE ASSESSMENT OF STRUCTURES | 1999年 / 167-1卷
关键词
systems condition; modelling; holistic models; symptom models; logistic vector; symptom observation matrix; singular value decomposition; symptom discriminant; generalized fault symptom;
D O I
10.4028/www.scientific.net/KEM.167-168.172
中图分类号
TQ174 [陶瓷工业]; TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
It is shown in this paper that classical approach to condition monitoring of critical systems can be supplemented by holistic models, which enable the best symptom of condition to be chosen and the evolution of the sytem condition to be simulated. When this is not possible, and where large symptom data base exist, we can apply singular value decomposition (SVD) as the newest data mining procedure to obtain symptom evolution model. By using SVD it is possible to have two additional independent fault discriminant: SD and SG, with the high dynamics of evolution, Moreover we can add life count as the first approximation of a logistic vector describing the unit life history. It is also possible to use the value of pseudo - determinant of a symptom observation matrix, and to correlate between this new discriminant and the symptom observation matrix to minimise the redundancy of symptom measuring space.
引用
收藏
页码:172 / 188
页数:17
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