Abstract
The objective of this work is to apply the sound perception approach to study and diagnose gear defects. Simple and multiple defects of different levels of severity are artificially simulated on the gear teeth. The corresponding sounds are then acquired to perform a sound base representative of the diversity of gear defects. Acoustic sounds are generated using the processing software DynamX V.7. These sounds are analyzed with the paired comparison method to find a correlation between the sound perception and the scalar indicators. The results show that perception tests allow classifying gear defect sounds by order of degradation. The relation between the vibratory indicators and sound perception enabled us to obtain applicable mathematical models for the other sounds not included in the listening tests. These models can be used to monitor the evolution of gear degradation without repeating perceptions tests.
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