利用语义分割和复杂性追求算法进行复杂背景分割,以估算非接触式电缆振动频率

IF 3.6 2区 工程技术 Q1 ENGINEERING, CIVIL
Tianyong Jiang, Chunjun Hu, Lingyun Li
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引用次数: 0

摘要

本文提出了一种基于修正的全卷积网络语义分割的新型复杂背景分割方法,用于非接触式电缆振动频率估算。从视频数据中估算频率面临着背景物体运动的挑战,这直接影响了基于视频方法的准确性。为解决这一问题,我们对现有模型(U2-Net)进行了图像测试,以探索高效通道注意(ECA)和卷积块注意模块(CBAM)对电缆分割性能的影响。结果,确定了一个相对最优的模型。修改后的模型用于去除复杂背景,同时保留电缆特有的振动信号。随后,使用基于相位的运动估算算法计算了不同电缆位置的电缆振动编码相位矩阵。使用复杂性追寻 (CP) 算法从分割的视频中估算出电缆振动的模态响应。最后,估算出电缆的振动频率。所提出的方法在一个小型电缆模型上进行了验证。结果与加速度计的采样值十分吻合,平均相对误差为 4.50%。这一估算结果表明,所提出的方法在结构健康监测方面具有巨大潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Complex background segmentation for noncontact cable vibration frequency estimation using semantic segmentation and complexity pursuit algorithm

Complex background segmentation for noncontact cable vibration frequency estimation using semantic segmentation and complexity pursuit algorithm

This paper proposes a new complex background segmentation method based on the modified fully convolutional network semantic segmentation for noncontact cable vibration frequency estimation. The estimation of frequency from video data is challenged by the presence of background object motion, which directly impacts the accuracy of the video-based method. To address this issue, image tests were carried out among the existing model (U2-Net) to explore the effect of the efficient channel attention (ECA) and convolutional block attention module (CBAM) on cable segmentation performance. As a result, a relative optimal model was identified. This modified model was then used to remove the complex background, while retaining the vibration signals specific to the cable. Subsequently, phase matrices encoding cable vibration were calculated using a phase-based motion estimation algorithm at various cable locations. The modal response of the cable vibration was estimated using the complexity pursuit (CP) algorithm from the segmented video. Finally, the vibration frequency of the cable was estimated. The proposed method was validated on a small-scale cable model. The results are in good agreement with the values sampled by the accelerometer, with an average relative error of 4.50%. This estimation shows the significant potential of the proposed method in structural health monitoring.

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来源期刊
Journal of Civil Structural Health Monitoring
Journal of Civil Structural Health Monitoring Engineering-Safety, Risk, Reliability and Quality
CiteScore
8.10
自引率
11.40%
发文量
105
期刊介绍: The Journal of Civil Structural Health Monitoring (JCSHM) publishes articles to advance the understanding and the application of health monitoring methods for the condition assessment and management of civil infrastructure systems. JCSHM serves as a focal point for sharing knowledge and experience in technologies impacting the discipline of Civionics and Civil Structural Health Monitoring, especially in terms of load capacity ratings and service life estimation.
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