Advancing Textile Membranes through Simulation, Functionalization, and AI‐Assisted Structural Monitoring

Research output: Contribution to journal › Conference article › Contributed › peer-review

Abstract

<jats:title>Abstract</jats:title> <jats:p>This study presents the development of a functional membrane monitoring system integrating sensor networks into textile membranes for real‐time structural health monitoring. The approach combined finite element method (FEM) simulations for stress analysis with textile‐integrated strain sensors based on silver‐coated polyamide, precision resistance alloys and shape memory alloys. A regressive AI model was developed and trained using 840 data sets from FEM data and experimental data. The system achieved a 0–10 % strain measurement range with less than 0.25 % uncertainty, 100 stress values per square meter spatial resolution, one‐second real‐time response, and over 95 % reliability for defect detection including cracks and delamination. The functional demonstrator validates AI‐driven membrane monitoring with applications in architecture, energy, and safety sectors, demonstrating scalable potential for smart structural systems.</jats:p>

Details

Original languageEnglish
Pages (from-to)255-261
Journalce/papers : Proceedings in Civil Engineering
Volume9
Issue number4-5
Publication statusPublished - Oct 2026
Peer-reviewedYes

Conference

Title8th TensiNet Symposium & 7th Essener Membranbau Symposium
SubtitleShaping the Pathway to Future – Tensioned Membrane Design
Duration30 September - 2 October 2026
Website
LocationUniversität Duisburg-Essen
CityEssen
CountryGermany

External IDs

ORCID /0000-0003-3849-3798/work/230749556
ORCID /0000-0001-7450-9641/work/230750928

Keywords