Structural dynamic response analysis using deviations from idealized edge profiles in high-speed video

Zhang, Dashan; Tian, Bin; Ye, Wei; Hou, Wenhui; Guo, Jie

doi:10.1117/1.oe.58.1.014106

Cited by 5 publications

(2 citation statements)

References 36 publications

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“…As an emerging vibration measurement method, vision-based vibration detection has received extensive attention from scholars at home and abroad (Hati and Nelson, 2019;Feng et al, 2017;Chen et al, 2015;Wadhwa et al, 2017;Sarrafi et al, 2018;Choi and Han, 2018;Peng et al, 2020;Aoyama et al, 2018;Moya-Albor et al, 2020;Zhang et al, 2019). Visual vibration detection techniques can be divided into two categories according to whether optical targets are needed.…”

Section: Research Status Of Vibration Signal Detectionmentioning

confidence: 99%

Transformer Vibration Detection Based on YOLOv4 and Optical Flow in Background of High Proportion of Renewable Energy Access

Huang

Qin

et al. 2022

Front. Energy Res.

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In recent years, large-scale renewable energy access to substations has brought overload, harmonic, short circuit and other problems, which has led to an increase in the failure rate and shortening the service life of important power equipment such as transformers. Transformer is one of the key equipment in power system, and its operation status has an important impact on the safe and stable operation of power grid. In order to realize the real-time state evaluation of transformer, a real-time vibration signal detection method based on video is proposed in this paper. Firstly, YOLOv4 is used to detect the transformer object, and then the pyramid Lucas-Kanade optical flow method and Otsu method are used to calculate the transformer vibration vector. Experimental results show that the transformer vibration vector can be calculated in real time and accurately by using the proposed algorithm, so as to realize the real-time reliable analysis of the transformer state.

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Section: Research Status Of Vibration Signal Detectionmentioning

confidence: 99%

Transformer Vibration Detection Based on YOLOv4 and Optical Flow in Background of High Proportion of Renewable Energy Access

Huang

Qin

et al. 2022

Front. Energy Res.

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“…Recently, non-target-based CV systems have been developed to capture a structure’s existing features [25,26,27,28,29,30,31,32,33,34,35,36,37] for tracking displacement and system identification [38,39,40,41,42,43]. However, detection of a structure’s natural features can be very difficult due to a lack of contrast and background conditions.…”

Section: Introductionmentioning

confidence: 99%

Non-Target Structural Displacement Measurement Using Reference Frame-Based Deepflow

Won

Park

et al. 2019

Sensors

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Displacement is crucial for structural health monitoring, although it is very challenging to measure under field conditions. Most existing displacement measurement methods are costly, labor-intensive, and insufficiently accurate for measuring small dynamic displacements. Computer vision (CV)-based methods incorporate optical devices with advanced image processing algorithms to accurately, cost-effectively, and remotely measure structural displacement with easy installation. However, non-target-based CV methods are still limited by insufficient feature points, incorrect feature point detection, occlusion, and drift induced by tracking error accumulation. This paper presents a reference frame-based Deepflow algorithm integrated with masking and signal filtering for non-target-based displacement measurements. The proposed method allows the user to select points of interest for images with a low gradient for displacement tracking and directly calculate displacement without drift accumulated by measurement error. The proposed method is experimentally validated on a cantilevered beam under ambient and occluded test conditions. The accuracy of the proposed method is compared with that of a reference laser displacement sensor for validation. The significant advantage of the proposed method is its flexibility in extracting structural displacement in any region on structures that do not have distinct natural features.

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A video processing and machine vision-based automatic analyzer to determine sequentially total suspended and settleable solids in wastewater

Ramos

Fernandes

Almeida

et al. 2022

Analytica Chimica Acta

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Structural dynamic response analysis using deviations from idealized edge profiles in high-speed video

Cited by 5 publications

References 36 publications

Transformer Vibration Detection Based on YOLOv4 and Optical Flow in Background of High Proportion of Renewable Energy Access

Transformer Vibration Detection Based on YOLOv4 and Optical Flow in Background of High Proportion of Renewable Energy Access

Non-Target Structural Displacement Measurement Using Reference Frame-Based Deepflow

A video processing and machine vision-based automatic analyzer to determine sequentially total suspended and settleable solids in wastewater

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