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Deep Learning for Structural Health Monitoring by sidhnt45 is a document available to read on EtoBox.

What is Deep Learning for Structural Health Monitoring about?

This paper presents a hybrid deep learning framework combining 1D CNN and LSTM for structural health monitoring (SHM) using multisensor time-series data. The proposed model achieves high accuracy in damage localization and detection, demonstrating over 96.6% accuracy in numerical simulations and over 99.6% in real-world applications. The integration of CNN for feature extraction and LSTM for temporal analysis effectively enhances the detection of structural damages.

Author

sidhnt45

Language

EN