Full-Field Modal Property Extraction from Motion Video Measurement: Considering Out-of-Plane Motions

Abstract

Aging problems and potential damage of structures will increase the risks of structural collapse in the upcoming extreme loading events (i.e., earthquakes, hurricanes). Thus, structural health monitoring (SHM) is an essential technique to determine structural soundness through in-situ measurements. However, a successful SHM system requires a dense array of sensors that may be challenging in real-world applications. Alternatively, the structural response can be acquired through motion videos. This measurement method not only overcomes the disadvantages of the conventional SHM systems but also gives the opportunity to investigate more detailed dynamic behavior. In this study, a full-field modal property extraction method based on motion videos is proposed, in particular for out-of-plane motions. The measurements are first padded to reduce the distortion effect caused by the image pyramid. The responses are then compressed and decomposed into sub-bands using an image pyramid decomposition. The modal properties are subsequently extracted using the OMA approach known as frequency-domain stochastic subspace identification. The advantages and limitations of the proposed approach are illustrated numerically using a physics-based graphics model of a continuous beam. Subsequently, experimental validation is conducted for a 3-story model building using the Intel RealSenseTM D415 depth camera. Modal properties are shown to be determined quickly, with high accuracy and noise robustness.