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Tytuł artykułu
Autorzy
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Warianty tytułu
Konferencja
19th IMEKO TC-10 International Conference on Technical Diagnostics. Integration in Technical Diagnostics (22-24.09.1999 ; Wrocław)
Języki publikacji
Abstrakty
It was shown in this paper that classical approach to systems condition evolution assessment can be much improved by special processing of observed symptoms of condition. When we have a large symptom data base, we can apply singular value decomposition (SVD), as the newest data mining procedure to obtain a symptom and condition evolution model. By using SVD it is possible to have two additional independent fault discriminants: named CD and SG, with high dynamics of evolution. Moreover we can an additional column of system life count, as the first approximation of a logistic vector describing the unit life history. It is also possible to use the value of a pseudo - determinant of a symptom observation matrix, and correlation between this new discriminant and the symptom observation matrix to minimize the redundancy measuring space, and chose the best symptom for condition observation.
Rocznik
Tom
Strony
33--46
Opis fizyczny
Bibliogr. 15 poz., rys. 4
Twórcy
autor
- Poznań University of Technology, ul. Piotrowo 3 PL-60965 Poznań, Poland, cempel@put.poznan.pl
Bibliografia
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPW2-0003-0062