Abstract
The sound-quality metrics (SQ) mapping was developed using beamforming and Near-field Acoustical Holography (NAH) for noise source identification of diesel engines. Apart from tradition metrics, such as loudness, sharpness, and roughness, a new impulsiveness algorithm was made, and the algorithm predicted the perceived impulsiveness using time-varying loudness. The performance of noise source identification using sound pressure level (SPL) mapping was compared with that of the SQ mapping both in simulations and in practical measurements. A number of monopole sound sources having a specific characteristic, e.g. loudest, sharpest, and most impulsive, were simulated. The SQ mapping was also applied to identify noise sources in two diesel engines for commercial vehicles. The current investigation revealed that the SQ mapping provided an efficient way of identifying problematic noise sources in diesel engines.
