Abstract
This paper evaluates how wavelet transform can be used to detect and isolate particular
faults. The diagnostic method that is proposed is based on the stationary wavelet transform. The
wavelet coefficients allow analysing the signal changes over different scales. Therefore, fault
detection can be performed. Each scale is related to a particular frequency band. Thus if various
faults are known to affect different frequency bands, the wavelet coefficients can be used to isolate
the faults. Fuzzyfication of the wavelet coefficients is first applied, followed by the fuzzy
aggregation of the fuzzyfied coefficients to make the isolation decision easy to compute and
gradual. Academic examples are discussed to show the efficiency of the isolation method
presented here.
