Demodulation Techniques in Gearbox Diagnostics

Abstract: This thesis covers the scope of one out of many ways to diagnose gearboxes, demodulating the excited vibrational signals to enhance fault detection and identification. The topic is not only of academic interest since the achievements that can be made by successful machine condition monitoring in the industry. It has a potential value that is close to be absurd, for example unplanned production stops is commonly known to be one of the worst nightmares for manufacturing companies and if one can detect faults in early stages one can improve the possibilityto plan a production stop and therefore increase the profit. Four demodulation algorithms were developed and implemented in MATLAB on data characterized by close to stationarity and distinctive energy centered around the harmonics of the gearmesh frequency. The resulting algorithms for narrowband phase and amplitude demodulation was shown to outperform Hilbert transform based phase and amplitude demodulation algorithms in gearbox diagnostics. One of the goals with the thesis was therefore reached; demodulation algorithms were developed and implemented on data. A comparison of these algorithms was done and a conclusion of which demodulation technique is superior was done. Experimental work was carried out on a test-rig and both local and distributed faults were introduced to two gearboxes, one kind of fault per gearbox. However, the data acquired from the test-rig showed severe non-stationarity and smeared spectrum properties even when angular resampling was performed and therefore a major drawback of the demodulation techniques was exploited since the methods for demodulation in this thesis are not applicable for signals with smeared spectrums. The other goal was therefore not accomplished; to distinguish a local fault from a distributed fault in data acquired by experimental work by applying the selected demodulation techniques.