Date of Award


Publication Type

Master Thesis

Degree Name



Mechanical, Automotive, and Materials Engineering

First Advisor

Gaspar, Robert (Mechanical, Automotive & Materials Engineering), Ahmadi, Majid (Electrical & Computer Engineering)


Engineering, Automotive.




Vibration in motor vehicles is largely influenced by the engine and thus has become the focus of much automotive testing. Engine idle vibration is focused on since deviations in the vibration signature are prevalent at this operating condition. The objective of this thesis was to derive a best-practice method for the analysis of engine idle vibration. Variability of the engine vibration signatures was calculated through the implementation of multiple analysis techniques. These methods included: angle domain analysis, the fast Fourier transform, the discrete cosine transform, the moving average model, and the auto-regressive moving average model. Also included in the investigation were examinations of data normalization, detrending, and filtration. The results of the analyses were then evaluated with reference to the correlation between similar engines and the identification of outliers. It was found that the fast Fourier transform analysis technique provided the best overall results. The moving average model and the auto-regressive moving average models were also identified as methods that have great potential in vibration analysis but are limited by their computational intensity.