Vibration Signal

Vibration signal analysis aims to extract meaningful information from the vibrations of various systems, primarily for fault detection and condition monitoring in machinery and structures. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and graph neural networks (GNNs) to analyze time-frequency representations of vibration data, often incorporating techniques like transfer learning and ensemble methods to improve accuracy and robustness. This field is crucial for predictive maintenance in industries like manufacturing and energy, enhancing safety and efficiency by enabling early detection of anomalies and potential failures in complex systems.