Condition Monitoring Using Computational Intelligence Methods
promotes the various approaches gathered under the umbrella of
computational intelligence to show how condition monitoring can be
used to avoid equipment failures and lengthen its useful life,
minimize downtime and reduce maintenance costs. The text introduces
various signal-processing and pre-processing techniques, wavelets
and principal component analysis, for example, together with their
uses in condition monitoring and details the development of
effective feature extraction techniques classified into frequency-,
time-frequency- and time-domain analysis. Data generated by these
techniques can then be used for condition classification employing
tools such as:
fuzzy systems; rough and neuro-rough sets; neural and Bayesian
networks;hidden Markov and Gaussian mixture models; and support
vector machines."
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