Modal Analysis

Modal analysis is a technique used to identify the inherent vibrational characteristics (modes) of structures or systems from measured data, primarily aiming to understand their dynamic behavior and identify potential damage or anomalies. Current research emphasizes improving the robustness and accuracy of modal analysis, particularly in handling noisy or incomplete data, with a focus on Bayesian methods, stochastic subspace identification (SSI), and physics-informed neural networks (PINNs). These advancements are crucial for applications ranging from structural health monitoring of bridges and aircraft to the analysis of complex fluid flows and the control of continuum robots, enabling more reliable and efficient system identification and prediction.