The prediction of failures in rotating machines is an important issue in industries to improve safety, to reduce the cost of maintenance and to prevent accidents. In this paper a predictive maintenance algorithm, based on the analysis of the orbits shape of the rotor shaft is proposed. It is based on an autonomous image pattern recognition algorithm, implemented by using a Convolutional Neural Network (CNN). The CNN has been designed, by using a suitable database, to recognize the orbits shape, allowing both fault detection and classification.
Deep Learning Algorithm for Predictive Maintenance of Rotating Machines Through the Analysis of the Orbits Shape of the Rotor Shaft
Caponetto R.;Xibilia M. G.
2019-01-01
Abstract
The prediction of failures in rotating machines is an important issue in industries to improve safety, to reduce the cost of maintenance and to prevent accidents. In this paper a predictive maintenance algorithm, based on the analysis of the orbits shape of the rotor shaft is proposed. It is based on an autonomous image pattern recognition algorithm, implemented by using a Convolutional Neural Network (CNN). The CNN has been designed, by using a suitable database, to recognize the orbits shape, allowing both fault detection and classification.File in questo prodotto:
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