Predizione del tempo rimanente di vita di un impianto mediante Hidden Markow Model

In this thesis we investigate the main methods used in the literature for the automation of conditio-base maintenance and then see a pratical application concerning bearing system. In the specifics we first analyze the row signal of vibration decomposing whit a wavelet packet transform then, we select the best level and index in term of characteristics. For create a model of failure we use the method of Hidden Markov Model. At least we compare the model generated with other level and index of decomposition to demonstrate that our choice was the best.