Advanced Signal Processing and Condition Monitoring
Résumé
When physical models are of a high complexity, a signal processing approach is helpful for providing accurate information about a system and its failures. Advanced Signal Processing methods in the context of condition monitoring, diagnostic and fault detection tackle with the analysis, modelling and/or detection of nonstationary and/or nonlinear signals in time, frequency, time-frequency and/or time-scale domains using parametric, non-parametric and/or statistical approaches. Tools as optimization techniques can cope with the high non-linearity of the system to solve. The methods proposed are successful in decision-making and bring on a step up in real-life signal processing applications. Signals or considered models come from domains such as acoustics, vibroacoustics, mechanics and electrical engineering. This keynote paper outlines a structured session of the Fourth International Conference on Condition Monitoring, gives some insight in spectral and time-frequency analysis and, in particular, presents a way of modelling highly non-stationary signals having both non-linear amplitude and non-linear frequency modulations.