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PS-15: Tools for Envelope Leak Detection and Evaluation
Time:
Thursday, 25/Sept/2025:
9:30am - 10:30am
Location:Tchaikovsky
Presentations
Acoustic Leak Detection in Building Envelopes – Laboratory and Field Tests
Björn Schiricke1, Markus Diel1, Alexander Jahnke2, Michael Markus Ackermann2
1German Aerospace Center (DLR), Germany; 2Gesellschaft zur Förderung angewandter Informatik e.V. (GFaI), Germany
Airtight building envelopes are essential for energy efficiency. Fast and reliable leak detection is crucial, especially when retrofiting large buildings. In previous research, feasibility studies in the field and small-scale laboratory tests have demonstrated the potential of the acoustic beamforming method as a tool for rapid and large-scale leak detection. To systematically investigate leaks and analyze the measurement system's behavior, an airtight test facility (ATLAS), as introduced in earlier studies, has been cosonstructed. Building on foundational investigations from that research, this study presents findings from complex test specimens designed to simulate more realistic leakage scenarios. A sandwich system is used to model leaks with cavities (e.g. roof-wall transition) and a labyrinth system is used to simulate twisted leakages (e.g. window seals). The laboratory work is supplemented by an accompanying measurement campaign on a building in need of retrofit in order to ensure practical suitability. This investigation particularly focuses on the effects of the angle of incidence and the output signal from loudspeakers, using a leaky window as a case study. In the two measurement scenarios, leakages were located with success; notably, one leak featuring two consecutive cavities was detected by the measurement technology at the test facility. In addition, two real leakages were found at the analyzed window, whereby a newly developed evaluation algorithm was able to greatly improve simultaneous detectability. The findings indicate that acoustic beamforming is capable of detecting complex leaks in both laboratory and field settings. However, further experimentation is necessary to accurately classify measured noises and facilitate automated analysis.