In this paper, a new analytical model is proposed to describe the behavior of uncertainty for a generic vision-based measurement system applied to mechanical vibration measurement. In particular, this paper proposes a novel way to evaluate the effects of motion blur. The theoretical framework presented here takes into account the camera acquisition parameters, the dynamics of the measurand (in terms of instantaneous speed), and the image scaling factor to develop a physical model of uncertainty when measuring a mainly monomodal vibration. Uncertainty is evaluated starting from the normalized discrepancy between a measured position and the actual one. The analytical model proposed here has been validated extensively with the help of a test stand that can generate biaxial monomodal vibrations. The motion of a target mounted on the test stand has been simultaneously monitored by a stereo vision rig and a set of triangulation lasers. Model validation has been carried out using two measurement techniques: stereo vision blob analysis and digital image correlation. The experimental results show that the proposed model is able to represent the behavior of uncertainty for both the techniques. After the model has been validated, it is shown how it is possible to exploit it to estimate the uncertainty of a vision rig starting from the nominal characteristics of both the vision system and the target. This can be a tool to facilitate the design of vision-based measurement systems

In this paper, the effects of motion blur on 2-D digital image correlation (DIC) measurements are discussed, with a particular focus on the description of displacement measurement uncertainty. The research started with the simulation of motion blur with a suitable literature-based algorithm. Then the state of the art of uncertainty analysis in the context of DIC was compared with simulation results, and it was found that the effects of motion blur on uncertainty are not predicted correctly by the literature models. This phenomenon is explained by the fact that the literature models do not consider motion blur. Consequently, a simple monodimensional case is analyzed. In this way, it has been possible to evaluate the sensitivity of DIC correlation function [evaluated as the sum of squared differences (SSD)] to motion blur. Using these results, it is possible to extend the analysis to the case of a generic image with the help of a power-law model. Eventually, the model proposed in this paper is able to represent the effects of motion blur correctly.

Digital image correlation (DIC) is a widely adopted optical technique to detect motions and deformations dealing with vision-based systems. Considering DIC dynamic applications, motion blur represents one of the most relevant sources of measurement uncertainty. This paper proposes an innovative approach to compensate the effect of motion blur on images coming from deformable bodies, where the amount of blur (w) varies within the single frame. A subset-based technique is developed to estimate and then remove motion blur for each image region. The algorithm is validated both on synthetic images and experimental data, demonstrating its effectiveness at improving the accuracy of the displacements measured by DIC.

Frustrated total internal reflection (FTIR) of light is a physical phenomenon which can be used to accomplish several measurement tasks. This paper deals with the design and modeling of pressure field or force sensors based on FTIR. In fact, it is possible to convert the value of contact pressure into a light intensity signal, owing to the frustration of reflection of a dedicated medium. In this sense, it is possible to measure pressure/forces with a camera system or a photosensitive sensor. In this paper, the physical principles of the technique are recalled. Then, an experiment will document the behavior of FTIR at micromechanical level. Consequently, a Greenwood-Williamson (GW) model is proposed as a tool to predict the response of the FTIR-based pressure sensor. Experimental data and uncertainty analysis show that the design methodology is able to predict the behavior of the sensor with an uncertainty that is about ±10% of the actual specimen response, thus providing an effective tool to optimize the FTIR experiments.