摘要
为了解决现有视觉技术难以准确测量结构微小振动的问题,该文提出了一种基于宽带相位运动放大(BPMM)和亚像素模板匹配算法的结构振动测量和频率识别方法。首先,利用相机拍摄结构的振动视频图像,并对图像中的噪声进行初步去除。其次,在不需要结构频率先验信息的情况下,在包含所有感兴趣频率的宽频带内进行滤波,选取合适的放大倍数进行微小振动视频的放大处理,再利用亚像素模板匹配算法从放大后的视频中提取结构的位移时程响应。最后,对提取的结构位移进行归一化处理,得到结构的实际位移时程响应,利用快速傅里叶变换(FFT)获取结构的振动频率。结果表明:BPMM算法既能实现结构微小振动位移幅值的放大,又能有效去除微小振动视频中的噪声,提高了图像的信噪比,从运动放大后的视频图像中可以准确地识别结构的振动频率。通过3层框架结构的室内试验和实桥试验对该文方法进行了验证,识别误差分别在1%和5%以内。该文方法可在不需要结构频率先验信息的情况下实现微小振动的盲放大处理,具有噪声鲁棒性好、计算量小及适用性强等优点,为结构微小振动测量提供了一种新思路,具有良好的应用前景。
In order to solve the problem that the existing visual technology is difficult to accurately measure the small vibration of the structure,this paper proposed a method combining the broad⁃band phase⁃based motion magnification(BPMM)and sub⁃pixel template matching for structure vibration measurement and frequency identificationFirstly,the vibration video of the structure was captured by a camera with initial image noise removalSecondly,the broad⁃band filtering was executed in a wide band containing all the frequencies of interestA suitable magnification factor was selected for the magnification of the small vibrationsThe displacement time⁃history of the structure was then extracted from the amplified video using the sub⁃pixel template matching algorithmFinally,the extracted vibration displacement was normalized to obtain the actual displacement time⁃history,and the vibration frequencies of the structure were obtained using the fast Fourier transform(FFT)The results show that the BPMM algorithm can effectively remove the noise in the vibration video,which improves the signal to noise ratio of the image motionThe vibration frequency of the structure can be accurately identified from the video image after motion amplificationThe proposed method in this paper was verified by the actual measurement results of a three⁃story frame structure in laboratory and a field bridge,and the identification errors are within 1%and 5%,respectivelyThe proposed method can achieve the blind magnification of small vibrations without the priori information of structural frequency and has the advantages of good noise robustness,low computational cost,and strong applicabilityThe research results can provide new choice for the measurement of small vibrations of structures.
作者
孔烜
罗奎
邓露
易金鑫
殷鹏程
冀伟
Kong Xuan;Luo Kui;Deng Lu;Yi Jinxin;Yin Pengcheng;Ji Wei(College of Civil Engineering,Hunan University,Changsha 410082,China;Hunan Provincial Key Laboratory for Damage Diagnosis of Engineering Structures,Hunan University,Changsha 410082,China;China Railway Siyuan Survey and Design Group Co.,Ltd.,Wuhan 430063,China;Lanzhou Jiaotong University,Lanzhou730070,China)
出处
《土木工程学报》
EI
CSCD
北大核心
2023年第10期105-117,共13页
China Civil Engineering Journal
基金
国家自然科学基金(52008160)
湖南省优秀青年基金(2021JJ20015)
甘肃省重点研发计划(20YF3FA039)
兰州市人才创新创业项目(2021-RC-39)。
关键词
桥梁工程
模态识别
宽带相位运动放大
振动频率
机器视觉
非接触式
亚像素模板匹配
bridge engineering
modal identification
broad⁃band phase⁃based motion magnification
vibration frequency
computer vision
non⁃contact
sub⁃pixel template matching
