Smart Sensor for Fault Detection in Induction Motors Based on the Combined Analysis of Stray-Flux and Current Signals: A Flexible, Robust Approach

Abstract

[EN] The most recent trend in the electric motor condition monitoring area relies on combining the information obtained from different machine quantities in order to reach a more reliable conclusion about the motor¿s health. This knowledge is of critical importance nowadays, especially in industrial applications in which unexpected outages can lead to severe repercussions. This paper presents a new intelligent sensor that combines, in a single unit, the information obtained from the analysis of stray fluxes (both axial and radial) and currents by means of a feed-forward neural network (FFNN) for classification purposes. Unlike other solutions, the sensor is based on the application of advanced signal processing tools that are adapted to the online analysis of these quantities under transient from a single processing unit (smart sensor). The combination of these new tools with the classical steady-state analysis of such quantities enables to obtain a more reliable conclusion on the motor health. The experiments included in the paper demonstrate the reliability provided by the sensor, which is being prepared to incorporate a third input based on infrared data.