Structural Vibration

Structural vibration analysis focuses on understanding and predicting the movement of structures in response to various forces, aiming to improve safety, efficiency, and performance. Current research heavily utilizes machine learning, particularly deep neural networks (like CNNs and RNNs) and ensemble methods, to analyze vibration data from diverse sources, including aircraft, UAVs, and industrial machinery, for tasks such as fault detection, damage identification, and signal denoising. These advancements are crucial for applications ranging from structural health monitoring in infrastructure to predictive maintenance in manufacturing, improving reliability and reducing costs. The development and validation of robust, interpretable models, often incorporating signal processing techniques, remain key challenges.