Global Modelling for Structural Health Monitoring

In this seminar, I presented updates on using a global TAGI-LSTM to model reversible effects in structural health monitoring (SHM). I demonstrated how the global model improves predictive performance over the local TAGI-LSTM, using either zero-shot filtering or fine-tuning on a target time series.

I also shared recent results from integrating the global model into the SKF framework while highlighting the current challenges we are addressing to unlock the model’s full potential for anomaly detection.

Source: CIV-ML’s Seminars