Wireless IoT Approach for Testing in situ Motor's Axis Vibration Monitoring

In this paper, a workbench for remote control of rotating machine is developed to predict the maintenance of a DC motor in an efficient way. To test the reliability of the sensor systems and explore the proposed experimental bench, a large set of measurements of the acceleration signal, derived from a MEMS accelerometer sensor placed on the rod axis of the engine and associated with a wireless RF device, was carried in different environments for multiple rotational speeds. In addition, different types of vibration signal, with different amplitudes and frequencies are injected directly on the engine's axis to also test and prove the reliability of devices. The detection, definition and localisation of vibration signatures are accomplished successfully thanks to Allan's variance technique. In fact, a white/random walk noise is then identified as a slope with gradient -1/2 whereas the bias instability is identified on the plot as a flat region around the minimum in the Allan's variance curve that corresponds to the acceleration signal recorded after a 200 mV/500 Hz sine wave vibration injection.