Janssens K., Kollar Z., Vecchio A.

A noise annoyance detection algorithm has been developed which automatically identifies a number of noise annoyance features from an engine run-up recording and visualizes them on top of the time-frequency spectrogram of the sound. The following important features are considered: resonances, masking, order non-linearities, booming and amplitude modulations. A unique order-based approach is used. In a first stage the significant powertrain orders are automatically detected and accurately tracked from the engine run-up sound with advanced singnature and order tracking methods. An appropriate tacho pulse signal is required to obtain accurate order tracking results in both amplitude and phase. Once this is achieved, the present resonances, masking effects, order non-linearities, booming phenomena and amplitude modulations are automatically identified from the extracted order data and visualized on top of the sound time-frequency spectrogram. This is based on psycho-acoustic principles, order synthesis techniques and new methods for operational modal analysis. The main reason why an order-based approach is used is to help the sound quality engineer to understand the various noise annoyance features in relation to the deterministic, physical components in the sound. For example, when the algorithm detects important amplitude modulations in a certain RPM region, it immediately informs which orders must be modified to reduce the modulations. The algorithm is very useful when it is used in closed loop with a virtual car sound synthesis tool. Based on the identified noise annoyance features, well-oriented virtual modifications can be applied in the sound synthesis tool. These modifications result in a new set of modified sounds which are then again objectively characterized in terms of noise annoyance untill a low-nuissance target sound is designed. An important benefit of this approach is that various sound management strategies can be assessed in a shorter period of time without the need for extensive jury testing.