Methods for prognosing mechanical systems

A method of prognosing a mechanical system comprising:

• receiving measurement data corresponding to the mechanical system;
• extracting one or more features from the received measurement data by decomposing the measurement data into a feature space;
• selecting a prediction model from a plurality of prediction models for one or more features based at least on part on a degradation status of the mechanical system and a reinforcement learning model;
• generating a predicted feature space by applying the selective prediction model to the feature space;
• generating a confidence value by comparing the predicted feature space with a normal baseline distribution, a faulty baseline distribution, or a combination thereof wherein:
• the confidence value is a value between zero and one;
• and
• the confidence value corresponds to an overlap region of the predicted feature space and the normal baseline distribution such that a relatively high confidence value corresponds with a relatively large overlap region and a relatively low confidence value corresponds with a relatively small overlap region;
• and
• providing a status of mechanical system based at least in part on the confidence value.