Induction motors are the most widespread rotating electrical machines in industry.Predictive maintenance of the motors is of crucial importance due to the fact that unexpected faults in those machines can lead to huge...Induction motors are the most widespread rotating electrical machines in industry.Predictive maintenance of the motors is of crucial importance due to the fact that unexpected faults in those machines can lead to huge economic losses for the corresponding companies.Over recent years,there is an increasing use of industrial induction motors operated by different types of drives,which have different functionalities.Among them,the use of soft-starters has proliferated due to the inherent benefits provided by these drives:they damp the high starting currents,enabling the soft startup of the motors and avoiding undesirable commutation transients introduced by other starting modalities.In spite of these advantages,they do not avoid the possible occurrence of rotor damages,one of the most common faults in this type of motors.Few works have proposed predictive maintenance techniques that are aimed to diagnose the rotor condition in soft-started machines and even fewer have demonstrated the validity of their methods in real motors.This work presents,for the first time,the massive validation of a rotor fault diagnosis methodology in soft-started induction motors.Industrial and laboratory and induction motors started under different types of soft-starters and with diverse rotor fault conditions are considered in the work.The results prove the potential of the approach for the reliable assessment of the rotor condition in such machines.展开更多
基金Supported by the Spanish‘Ministerio de Economia y Competitividad’(MINECO)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’(ref:DPI2014-52842-P).”。
文摘Induction motors are the most widespread rotating electrical machines in industry.Predictive maintenance of the motors is of crucial importance due to the fact that unexpected faults in those machines can lead to huge economic losses for the corresponding companies.Over recent years,there is an increasing use of industrial induction motors operated by different types of drives,which have different functionalities.Among them,the use of soft-starters has proliferated due to the inherent benefits provided by these drives:they damp the high starting currents,enabling the soft startup of the motors and avoiding undesirable commutation transients introduced by other starting modalities.In spite of these advantages,they do not avoid the possible occurrence of rotor damages,one of the most common faults in this type of motors.Few works have proposed predictive maintenance techniques that are aimed to diagnose the rotor condition in soft-started machines and even fewer have demonstrated the validity of their methods in real motors.This work presents,for the first time,the massive validation of a rotor fault diagnosis methodology in soft-started induction motors.Industrial and laboratory and induction motors started under different types of soft-starters and with diverse rotor fault conditions are considered in the work.The results prove the potential of the approach for the reliable assessment of the rotor condition in such machines.
