Academic Journal

Computer Vision System: Measuring Displacement and Bending Angle of Ionic Polymer-Metal Composites.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Computer Vision System: Measuring Displacement and Bending Angle of Ionic Polymer-Metal Composites.
Συγγραφείς: Manaf, Eyman, Fitzgerald, Karol, Higginbotham, Clement L., Lyons, John G.
Πηγή: Applied Sciences (2076-3417); Jul2022, Vol. 12 Issue 13, pN.PAG-N.PAG, 16p
Θεματικοί όροι: Python programming language, Computer systems, Computer vision, Standard deviations, Mathematical formulas, Mathematical functions, Angles
Περίληψη: Featured Application: The proposed vision system can be used to measure the displacement and bending angle of ionic polymer–metal composites (IPMCs). A computer vision system for measuring the displacement and bending angle of ionic polymer–metal composites (IPMC) was proposed in this study. The logical progression of measuring IPMC displacement and bending angle was laid out. This study used Python (version 3.10) in conjunction with OpenCV (version 4.5.5.64) for the development of the vision system. The coding functions and the mathematical formulas used were elaborated on. IPMC contour detection was discussed in detail, along with appropriate camera and lighting setups. Measurements generated from the vision system were compared to approximated values via a manual calculation method. Good agreement was found between the results produced by the two methods. The mean absolute error (MAE) and root mean squared error (RMSE) for the displacement values are 0.068080668 and 0.088160652, respectively, and 0.081544205 and 0.103880163, respectively, for the bending angle values. The proposed vision system can accurately approximate the displacement and bending angle of IPMCs. [ABSTRACT FROM AUTHOR]
Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Computer Vision System: Measuring Displacement and Bending Angle of Ionic Polymer-Metal Composites.
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  Data: Applied Sciences (2076-3417); Jul2022, Vol. 12 Issue 13, pN.PAG-N.PAG, 16p
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  Label: Abstract
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  Data: Featured Application: The proposed vision system can be used to measure the displacement and bending angle of ionic polymer–metal composites (IPMCs). A computer vision system for measuring the displacement and bending angle of ionic polymer–metal composites (IPMC) was proposed in this study. The logical progression of measuring IPMC displacement and bending angle was laid out. This study used Python (version 3.10) in conjunction with OpenCV (version 4.5.5.64) for the development of the vision system. The coding functions and the mathematical formulas used were elaborated on. IPMC contour detection was discussed in detail, along with appropriate camera and lighting setups. Measurements generated from the vision system were compared to approximated values via a manual calculation method. Good agreement was found between the results produced by the two methods. The mean absolute error (MAE) and root mean squared error (RMSE) for the displacement values are 0.068080668 and 0.088160652, respectively, and 0.081544205 and 0.103880163, respectively, for the bending angle values. The proposed vision system can accurately approximate the displacement and bending angle of IPMCs. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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              Text: Jul2022
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