Voronoi-Based Vacuum Leakage Detection in Composite Manufacturing
2026-03-31 • Computational Geometry
Computational Geometry
AI summaryⓘ
The authors studied how to find vacuum leaks during the making of composite materials. They used a math tool called Voronoi diagrams to divide the surface into regions based on vacuum connection points. This helps locate the leak in a smaller area, making it easier to find by hand. They improved their method with a refined version of these diagrams and tested both on a new dataset of known leak spots. Their results show this approach can predict leak locations accurately and help speed up the leak detection process.
vacuum leakage detectioncomposite manufacturingVoronoi diagramdiscrete geometrypartitioningflow measurementpredictive modelingleak localizationdataset
Authors
Christoph Brauer, Arne Hindersmann, Timo de Wolff
Abstract
In this article, we investigate vacuum leakage detection problems in composite manufacturing. Our approach uses Voronoi diagrams, a well-known structure in discrete geometry. The Voronoi diagram of the vacuum connection positions partitions the component surface. We use this partition to narrow down potential leak locations to a small area, making an efficient manual search feasible. To further reduce the search area, we propose refined Voronoi diagrams. We evaluate both variants using a novel dataset consisting of several hundred one- and two-leak positions along with their corresponding flow values. Our experimental results demonstrate that Voronoi-based predictive models are highly accurate and have the potential to resolve the leakage detection bottleneck in composite manufacturing.