loading-history and trend features to estimate the damage evolution

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• Published Subscription Original Research 22 Sep 2026

  A IoT-Enabled Predictive Intelligence for Real-Time Failure and Damage Evolution Monitoring of Polymer Composites

  By Ekta Singh, Rupesh Kumar, Galla Damodara Krishna Kishore, Gogineni Krishna Chaitanya, D. Naga Malleswari, D. Gouse Peera

  Abstract: Damage assessment of carbon-fibre-reinforced polymer composites is still challenging since the damage occurs as a combination of matrix cracking, interfacial debonding, delamination and fibre fracture. The present work proposes a framework for predictive-intelligence based on IoT for multiaxial fatigue and compression-after-impact (CAI) CFRP experiments, employing publicly available acoustic-emission (AE) datasets. A causal CNN–GRU attention model is developed by integrating time-domain, spectral, wavelet, loading-history and trend features to estimate the damage …

  Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article →