Interactive Visual Analysis of Structure-borne Noise Data
Rainer Splechtna, Denis Gracanin, Goran Todorovic, Stanislav Goja, Boris Bedic, Helwig Hauser, Kresimir Matkovic

TL;DR
This paper presents an interactive visual analysis approach for high-dimensional structure-borne noise data from automotive simulations, enabling engineers to identify noise sources efficiently and improve design processes.
Contribution
It introduces a novel interactive visualization method with linked views and drill-down capabilities tailored for noise data analysis in automotive engineering.
Findings
Enhanced ability to identify noise sources quickly
Improved understanding of noise, vibration, and harshness interactions
Faster iteration over design optimizations
Abstract
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…
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Taxonomy
TopicsData Visualization and Analytics · Vehicle Noise and Vibration Control
