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Prognostics and health management (PHM) methods aim at detecting the degradation, diagnosing the faults and predicting the time at which a system or a component will no longer perform its desired function. PHM is based on access to a model of a system or a component using one or combination of physical or data-driven models. In physical-based models, one has to gather a lot of knowledge about the desired system and then build an analytical model of the system function of the degradation mechanism that is used as a reference during system operation. On the other hand, data-driven models are based on the exploitation of symptoms or indicators of degradations using statistical or artificial intelligence methods on the monitored system once it is operational and learn the normal behaviour. Trend extraction is one of the methods used to extract important information contained in the sensory signals …