Discovery of knowledge from diagnostic databases
Research output: Contribution to journal › Conference article › Contributed › peer-review
Contributors
Abstract
The paper deals with acquisition of diagnostic knowledge that is relevant for detection and isolation of a special class of malfunctions of rotating machinery called "shaft misalignment". To detect a misalignment of the given shaft supported by multiple journal bearings, decision trees have been applied. These trees have been discovered in a database collected in a numerical experiment performed by the well-verified simulation system. A novel approach to definition of classes of misalignment has been introduced. Several new methods of selection of attributes and evaluation of classifier's performance have been suggested and verified. Finally a new method of diagnosing misalignment of rotating machinery has been formulated. This method may be efficiently implemented for real-existing rotating machinery.
Details
Original language | English |
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Pages (from-to) | 126-137 |
Number of pages | 12 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 4730 |
Publication status | Published - 12 Mar 2002 |
Peer-reviewed | Yes |
Externally published | Yes |
Conference
Title | SPIE AeroSense 2002 |
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Subtitle | Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV |
Duration | 1 - 4 April 2002 |
City | Orlando |
Country | United States of America |
Keywords
ASJC Scopus subject areas
Keywords
- Diagnostic knowledge, Knowledge discovery, Rotating machinery, Shaft misalignment, Static models