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With increase in demand for quieter product and reduction in masking noise, axle whine management plays a crucial role in the early product development process. Whine is tonal in nature and humans are more sensitive to tonal memory, hence this makes user to experience a very unpleasant ride which in turn results in bad product credibility. Dynamic mesh force excitation is the cause of the axle whine noise. Critical factors in consideration are gear micro geometry variability, misalignments, temperature of operation and resulting bearing pre-load, operating loads, and structural resonances that carry the excitation to the occupant’s ear. The variability associated with gear micro-geometry plays crucial role during optimization in the quest for robust gear design.

In the automotive industry many components face fatigue failure due to prolonged vibrations. This is commonly known as Vibration Induced Fatigue (VIF). There are two approaches to evaluate this; time & frequency domain. A straight forward and widely used method is the rainflow counting technique in the time domain. This counting algorithm is readily available and, apart from the time history, it needs only one variable input (the number of stress ranges). In case of high cycle fatigue, longer time histories are required for a statistically representative fatigue estimate, which makes the time domain approach consume large amounts of time and resources. This shifts our interest towards frequency domain methods. In the frequency domain, Dirlik's method is proven to be robust and gives closer results to the time domain.