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This paper proposed a novel in-plane displacement field measurement algorithm using an optical flow strategy. We built a linear illumination model between images before and after deformation to guarantee intensity invariability. We used image upsampling and a reliability-guided strategy to find the matching points accurate to 0.5 pixels in the reference and deformed images. The criterion to determine the reliability is zero-mean normalized cross-correlation coefficient. Afterward, we used the brightness constancy constraint combined with Lucas-Kanade optical flow constraint in a specific image region to obtain an overdetermined linear equation. We applied the noniterative least-squares algorithm to solve the equations and to achieve the displacement offsets. This research utilized multithread calculation to handle the complete cracking applications. We estimated the computing efficiency and calculation precision of the proposed method through a series of experimental speckle patterns. All results demonstrated the correctness, effectiveness, and robustness of the proposed method.

In this study, a high-speed camera system is developed to complete the vibration measurement in real time and to overcome the mass introduced by conventional contact measurements. The proposed system consists of a notebook computer and a high-speed camera which can capture the images as many as 1000 frames per second. In order to process the captured images in the computer, the normalized cross-correlation (NCC) template tracking algorithm with subpixel accuracy is introduced. Additionally, a modified local search algorithm based on the NCC is proposed to reduce the computation time and to increase efficiency significantly. The modified algorithm can rapidly accomplish one displacement extraction 10 times faster than the traditional template matching without installing any target panel onto the structures. Two experiments were carried out under laboratory and outdoor conditions to validate the accuracy and efficiency of the system performance in practice. The results demonstrated the high accuracy and efficiency of the camera system in extracting vibrating signals.

Rotational angle and speed are important parameters for condition monitoring and fault diagnosis of rotating machineries, and their measurement is useful in precision machining and early warning of faults. In this study, a novel vision-based measurement algorithm is proposed to complete this task. A high-speed camera is first used to capture the video of the rotational object. To extract the rotational angle, the template-based Lucas-Kanade algorithm is introduced to complete motion tracking by aligning the template image in the video sequence. Given the special case of nonplanar surface of the cylinder object, a nonlinear transformation is designed for modeling the rotation tracking. In spite of the unconventional and complex form, the transformation can realize angle extraction concisely with only one parameter. A simulation is then conducted to verify the tracking effect, and a practical tracking strategy is further proposed to track consecutively the video sequence. Based on the proposed algorithm, instantaneous rotational speed (IRS) can be measured accurately and efficiently. Finally, the effectiveness of the proposed algorithm is verified on a brushless direct current motor test rig through the comparison with results obtained by the microphone. Experimental results demonstrate that the proposed algorithm can extract accurately rotational angles and can measure IRS with the advantage of noncontact and effectiveness.