Interactive Visual Analysis of Structure-borne Noise Data

• Main Authors: Splechtna, Rainer, Gracanin, Denis, Todorovic, Goran, Goja, Stanislav, Bedic, Boris, Hauser, Helwig, Matkovic, Kresimir
• Format: Journal Article
• Language: English
• Published: 07-09-2022
• Subjects: Computer Science - Graphics
• DOI: 10.48550/arxiv.2209.03083

Numerical simulation has become omnipresent in the automotive domain, posing
new challenges such as high-dimensional parameter spaces and large as well as
incomplete and multi-faceted data. In this design study, we show how
interactive visual exploration and analysis of high-dimensional, spectral data
from noise simulation can facilitate design improvements in the context of
conflicting criteria. Here, we focus on structure-borne noise, i.e., noise from
vibrating mechanical parts. Detecting problematic noise sources early in the
design and production process is essential for reducing a product's development
costs and its time to market. In a close collaboration of visualization and
automotive engineering, we designed a new, interactive approach to quickly
identify and analyze critical noise sources, also contributing to an improved
understanding of the analyzed system. Several carefully designed, interactive
linked views enable the exploration of noises, vibrations, and harshness at
multiple levels of detail, both in the frequency and spatial domain. This
enables swift and smooth changes of perspective; selections in the frequency
domain are immediately reflected in the spatial domain, and vice versa. Noise
sources are quickly identified and shown in the context of their neighborhood,
both in the frequency and spatial domain. We propose a novel drill-down view,
especially tailored to noise data analysis. Split boxplots and synchronized 3D
geometry views support comparison tasks. With this solution, engineers iterate
over design optimizations much faster, while maintaining a good overview at
each iteration. We evaluated the new approach in the automotive industry,
studying noise simulation data for an internal combustion engine.