Advanced analysis of motor currents for the diagnosis of the rotor condition in electric motors operating in mining facilities

[EN] Predictive maintenance of electric motors is a topic of increasing importance in many industrial applications. The mining industry is not an exception; many electric motors operating in mining facilities are critical machines and their unexpected failures may imply significant losses and can be hazardous for the users. Due to these facts, an increasing research effort has been dedicated to investigate on new techniques that are able to provide a reliable diagnostic of the motor condition. Over recent years, monitoring of electrical quantities (e.g. motor currents) has emerged as a very attractive option for determining the health of several motor parts (rotor, eccentricities, bearings) due to its very interesting advantages: possibility of remote motor monitoring, non-invasive nature, simple application, broad fault coverage¿The traditional methods based on analysis of motor currents during steady-state operation (MCSA) are being complemented, when not replaced, by more reliable approaches. This work applies an innovative transient based methodology (ATCSA) to several case studies referred to large motors operating in mining facilities. The results prove how this modern methodology enables to overcome some important drawbacks of the classical MCSA, such as its unsuitability under varying speed conditions, and may provide an earlier indication of rotor electrical asymmetries under such working conditions.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and in part by the FEDER Program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P. (Corresponding author: Jose A. Antonino-Daviu.)Antonino-Daviu, JA.; Quijano-Lopez, A.; Rubbiolo, M.; Climente Alarcon, V. (2018). Advanced analysis of motor currents for the diagnosis of the rotor condition in electric motors operating in mining facilities. IEEE Transactions on Industry Applications. 54(4):3934-3942. https://doi.org/10.1109/TIA.2018.2818671S3934394254