A marker-free method for structural dynamic displacement measurement based on optical flow

Abstract

Information on dynamic displacement is an effective indicator for structures condition evaluation and provides a quantised insight into the structural analysis. This paper proposes a low-cost system based on computer vision using a smartphone to measure dynamic displacement, and then identify the dynamic properties of structures. Conventional sensors like linear variable differential transformers (LVDT), GPS, and accelerometer in monitoring systems have limitations of high price, inaccessibility, and accuracy. However, some new technologies eliminate these disadvantages. For example, a smartphone with a high-resolution camera becomes more affordable, which is regarded as appropriate equipment for structural health monitoring (SHM). Based on the optical flow, this method allows users to track points with a specific interval in the chosen region and reduces the displacement drift induced by the Kanade–Lucas–Tomasi (KLT) method. With the method applied, the region of interest is relocated according to pixel motion, and feature points are reselected. The accuracy of the system is verified on a laboratory suspension bridge model, and the results of modal frequency are confirmed with an accelerometer and FEM simulations.