Zhang Dashan, Guo Jie, Lei Xiujun, Zhu Changan
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230027, China.
Sensors (Basel). 2016 Apr 22;16(4):572. doi: 10.3390/s16040572.
The development of image sensor and optics enables the application of vision-based techniques to the non-contact dynamic vibration analysis of large-scale structures. As an emerging technology, a vision-based approach allows for remote measuring and does not bring any additional mass to the measuring object compared with traditional contact measurements. In this study, a high-speed vision-based sensor system is developed to extract structure vibration signals in real time. A fast motion extraction algorithm is required for this system because the maximum sampling frequency of the charge-coupled device (CCD) sensor can reach up to 1000 Hz. Two efficient subpixel level motion extraction algorithms, namely the modified Taylor approximation refinement algorithm and the localization refinement algorithm, are integrated into the proposed vision sensor. Quantitative analysis shows that both of the two modified algorithms are at least five times faster than conventional upsampled cross-correlation approaches and achieve satisfactory error performance. The practicability of the developed sensor is evaluated by an experiment in a laboratory environment and a field test. Experimental results indicate that the developed high-speed vision-based sensor system can extract accurate dynamic structure vibration signals by tracking either artificial targets or natural features.
图像传感器和光学器件的发展使得基于视觉的技术能够应用于大型结构的非接触式动态振动分析。作为一种新兴技术，基于视觉的方法允许进行远程测量，并且与传统的接触式测量相比，不会给测量对象带来任何额外的质量。在本研究中，开发了一种基于高速视觉的传感器系统以实时提取结构振动信号。由于电荷耦合器件（CCD）传感器的最大采样频率可达1000Hz，因此该系统需要一种快速运动提取算法。两种高效的亚像素级运动提取算法，即改进的泰勒近似细化算法和定位细化算法，被集成到所提出的视觉传感器中。定量分析表明，这两种改进算法的速度至少比传统的上采样互相关方法快五倍，并且具有令人满意的误差性能。通过在实验室环境中的实验和现场测试对所开发传感器的实用性进行了评估。实验结果表明，所开发的基于高速视觉的传感器系统可以通过跟踪人工目标或自然特征来提取准确的动态结构振动信号。
