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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM49436

Automatic Parameter Detection Of Gear By Image Processing

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM49436

Volume:

9 |

6 |

Jun 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SJ

Sumit Jamdade

MS

Mukund Salunkhe

RG

Rushikesh Gaikwad

VS

Viraj Sonawane

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Abstract

– Precision measurement of gears plays a vital role in gear measurement and inspection. The current methods of gear measurement are either time consuming or expensive. In addition, no single measurement method is available and capable of accurately measuring all gear parameters while significantly reducing the measurement time. The aim of this paper is to utilize the computer vision technology to develop a non-contact and rapid measurement system capable of measuring and inspecting most of spur gear parameters with an appropriate accuracy. A vision system has been established and used to capture images for gears to be measured or inspected. The introduced vision system has been calibrated for metric units then it was verified by measuring two sample gears and comparing the calculated parameters with the actual values of gear parameters. For small gears, higher accuracy could be obtained and as well as small difference

KEYWORDS

Image-operated sorting machine with conveyor Motorized conveyor Programmable Logic Controller (PLC) for conveyor control Real-time object tracking Defect detection software (Matlab) Sorting logic and decision module

Cite This Article

Sumit Jamdade, Mukund Salunkhe, Rushikesh Gaikwad, Viraj Sonawane, "Automatic Parameter Detection Of Gear By Image Processing," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 6, Jun 2025.

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Publication Date

6/3/2025

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Double-Blind Peer Review

Review Rounds: 2

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