Fault Diagnosis in Electric Motors through the Analysis of Currents and Stray Fluxes

Electric motors are key assets in most industrial plants, participating in a multitude of processes and driving very diverse loads. The correct maintenance of these machines is of paramount importance, since it can avoid unplanned production stops and reduce repair costs and waiting times. Due to this, in recent years a significant effort has been devoted to the development of new predictive techniques that can improve the performance of the techniques currently used in the industry. This article reviews the most recent trends in terms of new predictive maintenance techniques based on the analysis of electrical magnitudes. More specifically, emphasis is placed on two of the technologies that have attracted most of the attention, due to their non-invasive nature, their simplicity and the valuable information they provide for diagnosis. These are techniques based on the analysis of the current demanded by the motor and the stray flux around the machine. The article reviews the fundamentals of both techniques, ranging from the most traditional variants to the most modern ones based on transient analysis. The latter have proven to be tremendously robust in reaching a fully reliable diagnosis of the failure, avoiding false indications provided by the classical variants. Two separate cases are included regarding the application of both techniques in laboratory and industrial motors. These cases help to illustrate the significant advantages that these techniques can bring. Finally, some modern systems are commented, which have been recently developed and which integrate the application of both technologies in a single device.