Structural Low-Level Dynamic Response Analysis Using Deviations of Idealized Edge Profiles and Video Acceleration Magnification

Zhang, Dashan; Fang, Liangfei; Ye, Wei; Guo, Jie; Tian, Bin

doi:10.3390/app9040712

Cited by 6 publications

(3 citation statements)

References 37 publications

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“…After integrating the information from the three components, the bale density monitoring system for round balers was run in an interface developed in the Real View MDK5 development environment [ 22 ]. The main program of the bale density monitoring system was designed to initialize the system, detect the oil pressure, detect the load cell and the inertial measurement unit signals, and process, store and display the data.…”

Section: Methodsmentioning

confidence: 99%

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Yin

Chen

Liu

et al. 2023

Sensors

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Bale density is one of the main performance indicators to measure the quality of baler operation. In this study, a real-time baler bale density monitoring system was designed for the problem of difficult real-time measurement of bale density on round balers. Firstly, a weighing calculation model for the rolling and sliding stage of the bale was established, and the dynamic characteristics during the contact between the bale and the inclined surface were analyzed based on ADAMS dynamics simulation. Then, a real-time monitoring system for the bale density based on the contact pressure of the inclined surface, attitude angle measurement and hydraulic monitoring of the cylinder was constructed, and the accuracy of the weighing model was confirmed. The system was used to observe and analyze the changes in the pitch angle of the carrier table and the oil pressure in the rod chamber of the backpack cylinder during the operation of the round baler. Finally, the monitoring system was calibrated and the dynamic calibration equations were obtained. The results show that the maximum error between the calculated value of the original weighing model and the actual weight was 3.63%, the maximum error of the calculated value of the weighing model corrected by the calibration equations was 3.40% and the measurement accuracy could be satisfied. The results show that the system was highly accurate and met the practical needs of bale weighing in the field.

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Section: Methodsmentioning

confidence: 99%

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Yin

Chen

Liu

et al. 2023

Sensors

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“…In recent years, structural monitoring and displacement measurement methods based on computer vision have continuously emerged [1][2][3][4][5][6][7][8][9][10][11] and verified in practical engineering applications of mechanical, civil, aviation, and other structures [12][13][14][15][16][17][18]. These methods aim to acquire an image sequence of the structured surface and achieve precise non-contact displacement measurement using a vision sensor [19].…”

Section: Introductionmentioning

confidence: 99%

A single-stage anchor-free rotating target visual detection algorithm suitable for flexible body vibration displacement measurement

Li,

Wang,

Liu

et al. 2024

Meas. Sci. Technol.

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The phenomenon of angular inclination of flexible structures during vibration poses a significant challenge to the applicability of visual vibration measurement methods because the target locked in the captured image will produce unknown geometric deformations such as scale, displacement, and angle in the time domain space, and the horizontal rectangular frame used for matching during target detection will also increase the false detection rate of the target due to the introduction of more background information. Such subtle geometric deformations and false detections can lead to severe fit errors in the displacement curves regressed by the visual vibration measurement algorithm. To effectively improve the accuracy and robustness of vibration image target recognition, this article takes the flexible body captured by a high-speed camera as the target of vibration displacement measurement. It introduces the rotating target detection method based on deep learning into the field of visual vibration measurement, which verifies the feasibility of the deep learning method in flexible body vibration measurement, and based on the deep convolutional neural network framework, a high-precision displacement measurement algorithm based on single-stage anchor-free rotating target detection is proposed. The algorithm in this article first uses the CSPDarknet backbone network to extract multi-scale features of flexible structural image sequences. It then uses PANet to fuse the top-down and bottom-up bidirectional feature maps of the four bridge target feature maps obtained through the backbone network. The shallow and deep information is used for semantic feature fusion and combined with the Coordinate Attention mechanism to achieve target finding and fine positioning on the feature map. Finally, we use the coordinates of the bounding box obtained from the test to regress the position offset of the object's center point. To verify the accuracy of the algorithm in this article, we conducted experimental validation on the cable-stayed bridge model and the actual bridge and compared the performance with the traditional template matching algorithm, differential optical flow method, and various deep learning algorithms with different localization principles, as well as the displacement signals collected and processed by accelerometers. The experimental results of time-frequency characteristics analysis show that the vibration displacement trajectories regressed by the algorithm in this paper have the best overlap with the displacement measurements collected by the accelerometer, which verifies that the algorithm in this article has good application potential and implementation space in the field of condition monitoring of flexible structural bodies.

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“…The video-based procedures have been investigated for structural system identification of civil infrastructures in several research works. The main purpose of these researches is identification of natural vibration characteristics using remote video-based measurement techniques [33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. Both of low-quality equipments and high and super-high frame-rate cameras have been separately examined in structural system identification studies.…”

Section: Introductionmentioning

confidence: 99%

An enhanced indirect video-based measurement procedure for dynamic structural system identification applications

2021

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A video-based indirect sensing procedure for dynamic identification purposes is presented. To overcome major limitations of video-based methods in real on-site measurements, a novel three step pre-modification, magnification, post-modification process is developed. This process includes revision of the initial input video record in order to delete disturbing objects, utilizing a magnification method to filter the frequency content of the monitored motion and using a revision step for elimination of noises generated during magnification process. Finally, a set of digital signal and image processing analyses are performed on the modified video using virtual visual sensor technology. Based on the results of this research, motion signals of the monitored object are detected. The proposed approach has been used for identification of dynamic characteristics of two historic masonry minarets in Istanbul. Results shows that the proposed procedure is able to assess the dynamic characteristics of the monitored structure with a high-level of accuracy.

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Structural Low-Level Dynamic Response Analysis Using Deviations of Idealized Edge Profiles and Video Acceleration Magnification

Cited by 6 publications

References 37 publications

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

Design and Experiments of a Real-Time Bale Density Monitoring System Based on Dynamic Weighing

A single-stage anchor-free rotating target visual detection algorithm suitable for flexible body vibration displacement measurement

An enhanced indirect video-based measurement procedure for dynamic structural system identification applications

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