论文标题
结构传播噪声数据的交互式视觉分析
Interactive Visual Analysis of Structure-borne Noise Data
论文作者
论文摘要
数值模拟已在汽车域中无所不在,提出了新的挑战,例如高维参数空间以及大和不完整和多方面的数据。在这项设计研究中,我们展示了噪声模拟的高维频谱数据的交互式视觉探索和分析如何在相互冲突的标准中促进设计改进。在这里,我们专注于结构传播噪声,即来自振动机械零件的噪声。在设计和生产过程的早期发现有问题的噪声源对于减少产品的开发成本及其上市时间至关重要。在可视化和汽车工程的密切合作中,我们设计了一种新的交互式方法,以快速识别和分析关键的噪声源,也有助于对分析系统的了解。几个精心设计的交互式链接视图使频率和空间域中的多个细节探索噪音,振动和苛刻性。这使透视图可以迅速而平稳。频域中的选择立即反映在空间域中,反之亦然。在频率和空间域中,噪声源很快在其邻居的背景下显示。我们提出了一种新颖的钻孔视图,尤其是针对噪声数据分析量身定制的。拆分框图和同步3D几何视图支持比较任务。借助此解决方案,工程师在设计优化方面进行迭代速度更快,同时在每次迭代中保持良好的概述。我们评估了汽车行业的新方法,研究了内燃机的噪声模拟数据。
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.