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

Abstract 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.