Gear Defect Detection Using Machine Learning

Registration ID: IJNRD_196958

Published ID: IJNRD2305832

DOI: Click Here to Get

Tejas Sanjay Desai , P.G.Kulkarni , Tushar Ajay Magar , Amaan Irshad Shaikh

Defects , Deformations , Machine Vision , Projection

Appearance defects inspection plays a vital role in gear quality control. Human inspection is a traditional way to remove defective gears, which is instable and time consuming. In this paper, we develop a machine vision system for gear defect inspection, which can inspect various types of defects on gear covers, such as deformations, rusts, scratches and so on. The proposed system designs a novel image acquisition system to enhance the defects appearances and get controlled image acquisition environment. A series of image processing methods are proposed or utilized to inspect the defects. Especially, for the deformation defects on seal, we find a common rule on the distribution of projection, and design a simple but effective inspection algorithm based on the rule. The proposed system is evaluated and compared with skilled human by the recall, precision and F-measure. Experimental results show that the proposed vision system has high accuracy and efficiency.

Published Paper   E-Certificate

Tejas Sanjay Desai, P.G.Kulkarni, Tushar Ajay Magar, & Amaan Irshad Shaikh (May-2023). Gear Defect Detection Using Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), i239-i247. https://ijnrd.org/papers/IJNRD2305832.pdf

Volume 8 Issue 5, May-2023

Pages : i239-i247

Paper Reg. ID: IJNRD_196958

Published Paper Id: IJNRD2305832

Downloads: 000121974

Research Area: Mechanical Engineering 

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305832.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305832

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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