Abstract

Vibration and wear debris analyses are the two main conditions monitoring techniques for machinery maintenance and fault diagnosis. These two techniques have their unique advantages and disadvantages associated with the monitoring and fault diagnosis of machinery. When these techniques are conducted independently, only a portion of machine faults are typically diagnosed. However, practical experience has shown that integrating these two techniques in a machine condition monitoring program provides greater and more reliable information, bringing significant cost benefits to industry. The objective of this work is to investigate the correlation between vibration analysis and wear debris analysis. This was achieved by investigating different operating conditions of an experimental rig, consisting of a worm gearbox driven by an electric motor. The worm gearbox was initially run under normal operating conditions as a comparative test. A series of tests were then conducted corresponding to lack of proper lubrication, and with different contaminant particles added to the various lubricants. Oil samples and vibration data were regularly collected. Numerical data produced by wear debris analysis were compared with vibration spectra, in order to quantify the effectiveness of the two condition monitoring techniques. The results from this paper have given more understanding on the dependent and independent roles of vibration and wear debris analyses in predicting and diagnosing machine faults.

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