Camera-based measurement for transverse vibrations of moving catenaries in mine hoists using digital image processing techniques

Yao, Jiannan; Xiao, Xingming; Yao, Liu

doi:10.1088/0957-0233/27/3/035003

Cited by 11 publications

(9 citation statements)

References 16 publications

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“…To tackle this problem, target tracking algorithms such as mean shift 26 normally use the best matched region in the current image as a template to track the target in the next image. However, the way makes that the template is updated too frequently, and it is easy to accumulate matching errors, causing the drift of the matching template and the failure of target tracking.…”

Section: Locating the Vertical Ropesmentioning

confidence: 99%

“…Yan et al 25 carried out the displacement measurement of the cables in a footbridge by target tracking algorithm. In previous work, we applied target tracking algorithm, 26 the digital graphics overlay method 27 and edge detection algorithm 28 to measure the transverse vibrations of mine hoisting ropes, but these approaches can only achieve positioning of single rope at integer pixel level, which is imprecise enough for multi-rope hoisting system.…”

Section: Introductionmentioning

confidence: 99%

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Vision-based transverse vibration displacement measurement of hoisting vertical ropes in mine hoists

Xiao

et al. 2021

Advances in Mechanical Engineering

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At present, there is no appropriate way to measure the transverse vibration response of moving hoisting vertical rope in hoist. Therefore, a vision-based measurement method combining the digital image correlation (DIC) and digital image processing (DIP) algorithms is proposed in this paper. In this method, a reference line perpendicular to the vertical ropes is added in image sequence by DIP algorithm to form some virtual cross targets, which makes the improved DIC algorithm with adaptive template updating (ATU) rule can track the moving hoisting vertical rope without any labels. Then for distinguishing all ropes in the measuring area, a displacement threshold is set to locate the current measured rope and exclude the other ropes. The transverse vibration displacements of the hoisting vertical rope in an actual mine hoist was measured in three background situations, verifying the feasibility of the proposed method. Moreover, in a laboratory artificial vibration test, the measurement results from the proposed vision method and a laser displacement sensor yielded a very good agreement. The two experimental results indicate that it is fairly reasonable and effective to measure the transverse vibration displacements of hoisting vertical ropes.

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Section: Locating the Vertical Ropesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vision-based transverse vibration displacement measurement of hoisting vertical ropes in mine hoists

Xiao

et al. 2021

Advances in Mechanical Engineering

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“…Winkler et al [ 10 ] use digital image correlation to obtain measurement of local deformations in steel mono strands. Yao et al proposed a non-contact video-based measurement for transverse displacements of hoisting catenaries in mine hoist using mean shift tracking [ 11 , 12 ] and digital image processing techniques [ 13 ]. Wu et al [ 14 ] proposed a non-contact and unmarked machine vision measurement method for measuring the transverse vibration displacement of hoisting vertical ropes.…”

Section: Introductionmentioning

confidence: 99%

Inspection Method of Rope Arrangement in the Ultra-Deep Mine Hoist Based on Optical Projection and Machine Vision

Shi

Tan

Xue³

2021

Sensors

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Due to the importance of safety detection of the drum’s rope arrangement in the ultra-deep mine hoist and the current situation whereby the speed, accuracy and robustness of rope routing detection are not up to the requirements, a novel machine-vision-detection method based on the projection of the drum’s edge is designed in this paper. (1) The appropriate position of the point source corresponding to different reels is standardized to obtain better projection images. (2) The corresponding image processing and edge curve detection algorithm are designed according to the characteristics of rope arrangement projection. (3) The Gaussian filtering algorithm is improved to adapt to the situation that the curve contains wavelet peak noise when extracting the eigenvalues of the edge curve. (4) The DBSCAN (density-based spatial clustering of applications with noise) method is used to solve the unsupervised classification problem of eigenvalues of rope arrangement, and the distance threshold is calculated according to the characteristics of this kind of data. Finally, we can judge whether there is a rope arranging fault just through one frame and output the location and number of the fault. The accuracy and robustness of the method are verified both in the laboratory and the ultra-deep mine simulation experimental platform. In addition, the detection speed can reach 300 fps under the premise of stable detection.

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“…Ribeiro et al 19 built a non-contact dynamic displacement measurement system for railway bridges deck based on binary image and image scanning technique to track the central point of the predefined target. Yao et al 20 applied mean shift tracking algorithm and digital graphics overlay method 21 based on monocular vision to measure the transverse vibrations of hoisting catenaries in mine hoists.…”

Section: Introductionmentioning

confidence: 99%

Machine vision–based measurement approach for transverse vibrations of moving hoisting vertical ropes in mine hoists using edge location

Xiao

Yao

et al. 2019

Measurement and Control

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Hoisting vertical rope is a continuum of one-dimensional movement during operation of hoist, and there are no appropriate ways to measure its vibration displacement at present. In this paper, a non-contact and unmarked machine vision measurement method is proposed for measuring the transverse vibration displacement of hoisting vertical ropes. First, we construct the background image to extract the ropes by the background difference method. Subsequently, a novel row-column data statistics filtering algorithm is proposed and applied to the edge detection image for removing the edges of the unmeasured rope. Finally, Hough transformation is used to locate the two edge lines at the boundary of rope and obtain the line parameters, which can be used to calculate the vibration displacement of the measured points at different times. The transverse vibration displacement of a moving hoisting vertical rope in a mine hoist was measured by using the reported machine vision measurement method, verifying the feasibility of the method. In order to verify the validity of the method, a simulation experimental system was built. The proposed method and the laser displacement sensor were used to measure the artificial transverse vibration displacement of a vertical rope simultaneously. The two results are in good consistency, which indicates that the proposed method can be fairly reasonable and accurate to measure the transverse vibration displacement of vertical rope in mine hoists.

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Camera-based measurement for transverse vibrations of moving catenaries in mine hoists using digital image processing techniques

Cited by 11 publications

References 16 publications

Vision-based transverse vibration displacement measurement of hoisting vertical ropes in mine hoists

Vision-based transverse vibration displacement measurement of hoisting vertical ropes in mine hoists

Inspection Method of Rope Arrangement in the Ultra-Deep Mine Hoist Based on Optical Projection and Machine Vision

Machine vision–based measurement approach for transverse vibrations of moving hoisting vertical ropes in mine hoists using edge location

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