Asynchronous Motor Test Bench for the Generation and Current Signal Diagnostics of Accelerated Bearing Damage

Christoph Anger, Christian Preusche, and Uwe Klingauf
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phmc_15_014.pdf759.71 KBAugust 7, 2015 - 6:53am

The data acquisition of run to failure data by means of degrading components is one of the most delicate tasks in evaluating new diagnostic and prognostic approaches, since it is cost-intensive and time-consuming. Therefore, a test rig for a cost-efficient generation of artificial bearing damages is described below. The test rig is thereby based on an ordinary asynchronous motor.
This paper mainly concentrates on the description of the test rig’s setup and first diagnostic findings. One aim of the experiments is the investigation of several variations of the applied loads for the artificially accelerated bearing aging. Thus, radial force and fluting are examined. The latter causes a damage triggered by a current flow through the test bearing. Both load types reduce the overall lifespan of bearings to about few weeks.
The generated faults are a broken cage and chattermarks due to a radial force higher than the design point. The bearings are diagnosed by means of frequency analysis of the phase current signal, which is produced in the stator of the motor. Beside the current signal, also temperature, vibration and revolution of the shaft are measured, whereas the vibration signal is used only for the comparison to the current signal. The comprehensive measurement concept allows a performance evaluation of diagnostic and prognostic algorithms based on different physical indicators.
It can be shown that especially the current frequency spectrum of a faulty bearing differs significantly from a healthy one. In order to face the high amount of measurement data, the Principal Component Analysis is used for data reduction to generate features for the diagnosis and prognosis. Thus, a classification of different fault modes and loading conditions is possible.

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Submission Keywords: 
Motor Current Signature Analysis
test rig
bearing diagnostics
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
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