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As the drive to make automobiles more noise and vibration free continues, it has become necessary to analyze transient events as well as periodic and random phenomena. Averaging of transient events requires a repeatable event as well as an available trigger event. Knowing the exact event time, the data can be post-processed by re-sampling the time scale to capture the recorded event at the proper instant in time to allow averaging. Accurately obtaining the event time is difficult given the sampling restrictions of current data acquisition hardware. This paper discusses the ideal hardware needed to perform this type of analysis, and provides analytical examples showing the transient averaging improvements using time scale re-sampling. These improvements are applied to noise source identification of a single transient event using an arrayed microphone technique. With this technique, the averaging is performed using time delays between potential sources and microphones in the array.

A general time-varying nonlinear dynamic model of a hypoid gear pair for rear axle applications is proposed. The dynamic model considers time-varying mesh position, line of action, mesh stiffness, mesh damping and backlash nonlinearity. Based on the model, dynamic analysis is conducted to study the effect of mean load, mesh damping and mesh parameter variations on dynamic mesh force response and the interaction between them and backlash nonlinearity. Numerous nonlinear phenomena such as tooth impacts and jump discontinuities are revealed by computational results.

A combined lumped parameter, finite element (FE) and boundary element (BE) model is developed to predict the whine noise from rear axle. The hypoid geared rotor system, including the gear pair, shafts, bearings, engine and load, is represented by a lumped parameter model, in which the dynamic coupling between the engaging gear pair is represented by a gear mesh model condensed from the loaded tooth contact analysis results. The lumped parameter model gives the dynamic bearing forces, and the noise radiated by the gearbox housing vibration due to the dynamic bearing force excitations is calculated using a coupled FE-BE approach. Based on the predicted noise, a new procedure is proposed to tune basic rear axle design parameters for better sound quality purpose. To illustrate the salient features of the proposed method, the whine noise from an example rear axle is predicted and tuned.