Abstract
This paper presents a fuzzy knowledge-based system
for turbomachinery diagnosis. Given symptoms associated with a
vibration problem, the system can identify and rank possible causes
by performing incremental forward chaining. The diagnostic system
incorporates an attribute weighting component to reflect the relative
significance of conditional attributes, thereby allowing the system
to produce more accurate diagnoses. The ability of this system to
identify causes of typical vibration problems in rotating machinery
is supported with tests on real cases.
Original language | English |
---|---|
Pages (from-to) | 137-146 |
Number of pages | 10 |
Journal | International Journal of Knowledge-Based and Intelligent Engineering Systems |
Volume | 12 |
Issue number | 2 |
Publication status | Published - 2008 |