Measurement of local strain: machine vision and finite element method

Shahri, Seyyed Ehsan Eftekhari; Lakhi, Mohammad; Ranjbar, Sadegh

doi:10.1007/s12206-021-0211-2

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…In this new method, several calligraphy posts are written on the finite element model. It eliminates the limitations of machine vision method, including its sensitivity to vibration, which is the most important advantage of this machine vision model [4]. These related research methods are combined with machine learning technology in machine vision methods, which deal with colors, shapes, textures, and font sizes from calligraphy.…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Zhou

2022

Journal of Sensors

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Machine vision is a noncontact measurement method. In some jobs that are not suitable for artificial work environment or artificial vision, machine vision is usually used to replace artificial vision to meet the traditional requirements. Therefore, this paper quotes machine vision into the intelligent scoring and style research of calligraphy post. Firstly, it briefly introduces the related concepts and steps of calligraphy post and briefly explains the style of calligraphy post. Then for the third part of the machine vision localization research algorithm, the correlation function algorithm was proposed in the research field to explain and analyze. Finally, by comparing other research methods of machine vision, it shows that machine vision is more conducive to the study of calligraphy style intelligent scoring, through the experimental study of people on the calligraphy style and calligraphy style of people on the intelligent score. At the end, it is proposed that machine vision can greatly promote the study of intelligent scoring and style of calligraphy and also reflect the accuracy and usability of intelligent scoring for calligraphy style. On-contact test of machine vision refers to not touching the tested object, so as to obtain the test result. It is a three-dimensional testing technology. Among them, the test system of machine vision is relatively simple. It is easy to move and easy to collect data, and the cost of this noncontact test is low. It has more accurate testing technology. A plurality of test quantities can be simultaneously tested by image laser detection of the test quantity without touching the object.

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Section: Introductionmentioning

confidence: 99%

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Zhou

2022

Journal of Sensors

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“…Ye et al (2016) reviewed the strain measuring method of structures based on machine vision. Shahri et al (2021) developed a method based on machine vision to detect material deformation. In vision-based measuring strain methods, the most typical one is the digital image correlation (DIC) method (Pan et al, 2009(Pan et al, , 2018Spencer et al, 2019), which is capable of non-destructive, non-contact operation, and full-field measurement.…”

Section: Introductionmentioning

confidence: 99%

Strain measurement based on cooperative operation with different smartphones

Xie

Zhang

Ding

et al. 2022

Computer aided Civil Eng

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Strain measurement is one of the critical procedures in detecting failures and health monitoring for various structures in the field of civil engineering. This article demonstrates a smartphone-based cooperative strain measurement method called micro image strain sensing (MISS) for widespread and low-cost structural strain monitoring. The method relies on smartphones, the piston-type sensor with a microscope fitted on it, and the Android platform with cloud computing. The detailed principle of the MISS method and fabrication of the MISS sensor and the comparison of measurement accuracy with fiber Bragg grating sensor are presented. The results show that the error is within 10 με., which satisfies the engineering requirement, and the sensor exhibits high flexibility, high reliability, and high linearity. The work highlights the potential of widespread usage and public participation in smartphone-based strain measurement for the structural health monitoring of the next generation.

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Measurement of local strain: machine vision and finite element method

Cited by 2 publications

References 12 publications

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Research on Intelligent Scoring and Style of Calligraphy Post Based on Machine Vision

Strain measurement based on cooperative operation with different smartphones

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