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PREDICTIVE MAINTENANCE OF MINING MACHINERY BASED ON VIBRATIONAL ANALYSIS

Javier Castilla

Abstract

One of the main problems industries in general are facing is the prediction of errors or failures of the most sensitive or critical assets of their equipment. For this reason, techniques based on predictive maintenance are emerging, searching for the early detection of possible cracks, imperfections or defects that are likely to cause an accident or the partial or complete shutdown of a plant. The main objective is to anticipate breakages in order to improve the planning and scheduling of control and maintenance operations. This not only improves safety, but also profitability. We cannot forget the extremely high costs involved in a shutdown for corrective maintenance and the implications for the different equipment, sometimes causing its own deactivation. The bearing is precisely one of the most important elements in production equipment and systems. Its analysis and monitoring are two of the most common tools for predicting problems in different industrial processes. This study deals with the different situations suffered by a machine during 15 years of real operating conditions, analysing its spectral map and typical frequencies seeking for the most relevant and influential variables in the useful life of the assembly. Not only will we try to respond to the most determining elements, but we will also try to establish at which measuring points their disturbances are more evident, to reduce the number of sampling points without losing reliability.

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DOI resolver: doi.org/10.5593/sgem2018/1.3/s03.084

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