视频数据挖掘的非接触式桥梁振动监测

为克服传统桥梁监测技术施工难、成本高和观测点少等不足,利用视觉技术实现了非接触式桥梁振动状态监测。该方法包含视频数据采集、视频数据分析与结果可视化等3个环节。其中,视频数据分析环节又包含3个步骤:首先,对视频中的稳定像素点进行定位;然后,根据视频中稳定像素点的数值变化,由视频数据挖掘方法建立视频热噪声模型;最后,由视频热噪声模型计算出视频中桥梁各局部位置上的振动频率。实验结果表明,该方法可有效侦测到桥梁可见结构部件上出现的人眼不易察觉的微弱振动,并对桥梁不同局部位置上出现的振动频率进行同步定量测算,从而提供了一种便捷高效、成本合理、通用性好的桥梁结构健康监测新途径。

Non-contact bridge vibration monitoring based on video data mining

To overcome the defects of traditional bridge health monitoring methods, visual technology is employed for non-contact bridge vibration monitoring. The method consists of video data acquisition, video data analysis and results visualization. And the viedo data analysis contains three steps. First, the stable pixels of a video are located. Then, a video thermal noise model is built via video data mining by tracking the variations of all stable pixels of the video. At last, the vibration frequency of each local position of the bridge in the video is calculated by the thermal noise model. The experimental results show that the method can effectively detect the imperceptible tiny vibrations in visible structure components of bridges, and it can measure the frequencies of vibrations in different local positions of bridges quantitatively and synchronously. Therefore, the method can provide a novel bridge structure health monitoring approach that is convenient, low-cost and universal.