کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
559140 | 1451861 | 2016 | 12 صفحه PDF | دانلود رایگان |
• A high-speed camera system is developed for displacement measurement.
• The Lucas–Kanade template tracking algorithm in computer vision is introduced.
• A modified inverse compositional algorithm is proposed to improve efficiency.
• The present algorithm can realize measurement without pre-designed target panel.
• Experiments demonstrated the accuracy and the efficiency of the camera system.
The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas–Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.
Journal: Mechanical Systems and Signal Processing - Volumes 66–67, January 2016, Pages 425–436