Separation, Allocation and Psychoacoustic Evaluation of Vehicle Interior Noise

Besides optical and haptic criteria, the interior noise especially influences the quality impression of a vehicle. Separately audible disturbing noises are usually perceived as inadequate product quality. As a result, the reduction of disturbing noise components is a key factor for the overall product quality. Since the acoustic optimization is a complex and time consuming process, the need for an analysis tool which identifies automatically disturbing engine noise components within the vehicle interior noise is high. For this reason, a novel analysis tool has been developed which extracts tonal and impulsive engine noise components from the overall engine noise, and evaluates the annoyance of each noticeable engine component automatically. In addition, each disturbing noise is allocated to the emitting engine component. It is then possible to listen to each engine component noise individually and synthesize a target noise by superimposing manually weighted component noises. The noise separation into noise fragments is performed by means of the non-negative matrix factorization and image processing tools. These are then clustered according to their time correlation or other similarity-determining parameters. Classification algorithms are trained using chosen features to provide a noise source allocation. The extracted noise components as well as sound mixtures of those components are assessed by a psychoacoustic pleasantness rating metric. This metric is based on a multiple regression analysis between experimentally acquired pleasant values and objectively calculated psychoacoustic parameters as, e.g., loudness, sharpness, tonalness.