希尔伯特-黄变换
情态动词
流离失所(心理学)
振动
信号(编程语言)
计算机科学
信号处理
桥(图论)
噪音(视频)
快速傅里叶变换
人工智能
声学
计算机视觉
算法
滤波器(信号处理)
电信
物理
图像(数学)
医学
心理学
雷达
化学
高分子化学
内科学
心理治疗师
程序设计语言
作者
Zhaocheng Yan,Gongfa Chen,Wei Luo,David Bassir,Gongfa Chen
摘要
This paper proposes two approaches, Empirical Mode Decomposition (EMD) and Fourier Transform (FT), to correct the vibration signals measured by an Unmanned Aerial Vehicle (UAV), which overcomes the difficulty of selection of reference points used in other correction methods, such as homography transformation and three-dimensional reconstruction. In the method of this paper, a UAV is used to collect the video of a vibrated bridge, and the displacement signal of the bridge is obtained from the video by Kanade–Lucas–Tomasi (KLT) optical flow method, which contains false displacement caused by the ego-motion of the UAV during the measurement. The false displacement can be effectively eliminated by EMD and FT to obtain the real displacement signal. Finally, the displacement signal is processed by the Operational Modal Analysis (OMA) technique to obtain the bridge modal parameters. The performance of correcting vibration signals and extracting bridge modal parameters from the vibration signals based on EMD, FT, and Differential Filtering (DF) are compared by taking the fixed camera measurement as a reference (the accuracy of measuring bridge vibration with fixed cameras has been verified) in this paper, and it is demonstrated that EMD has better reliability in processing signal measured by UAVs, which is mainly due to the absence of random factors and too much noise in the signal processing process of EMD.
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