Use of the infrared data for heating curve computation in induction motors: Application to fault diagnosis

Abstract

[EN] Infrared thermography is a technique that has been frequently used as a predictive tool for electrical installations maintenance, since many of the failures or installation defects lead to temperature increments in specific points or areas. However, its application to fault detection in electric motors is far less usual. Alternative techniques, based on current or vibration monitoring, are still preferred, despite the analyses of these quantities do not enable the diagnosis of a significant number of failures that occur in these machines. In this regard, infrared data may provide very useful information for the detection of some faults which are not easy to be detected with currents or vibrations. In addition, this can be done in a non-invasive way, i.e., without interfering with the machine operation. The spectacular evolution undergone by the infrared cameras, which even enable the capture of motor thermal transients, represented by sequences of high resolution images as well as the monitoring of the temperature evolution at any point of the surface, is a fact that contributes to the great potential of this technique.

In this work, a new methodology relying on the combination between the heat transfer theory and infrared data is proposed. The main pursued objectives are: (1) to study the thermal behaviour and perform the energy balance by building a thermal model of the induction motor using infrared data and (2) to set the baseline for further complex failure diagnosis in electric motors.

To achieve these goals, a 1.1 kW induction motor is tested; thermography images of the motor frame are captured every second during the whole startup transient, from standstill till steady-state, by using an infrared camera connected to a laptop computer fitted with an acquisition and analysis software. These infrared data are used in a first stage to build the thermal model of the induction motor. Afterwards, in a second stage, the obtained results are compared with those corresponding to faulty machines to study the applicability of thermography data for diagnosis purposes.

The results prove the potential of the approach to become a powerful diagnosis tool, complementing the information provided by techniques relying on other quantities, in cases in which they are not conclusive.