Open Access Open Access  Restricted Access Subscription or Fee Access

Intelligent Gear Inspection: Defect Detection through Digital Image Processing Algorithms

Parshuram Sonawane, Chetan Patil, Piyush Bhamare, Nagesh Sonkamble, Sandesh Kshirsagar

Abstract


A significant contributor to poor reliability and a source of humiliation for businesses are gear problems. The majority of the inspection procedures used in these businesses are laborious and manually. More thorough and accurate inspection procedures are needed to improve accuracy in finding gear problems. The present work fills this gap by implementing a Gear Defect Recognizer that uses local thresholding in conjunction with computer vision methodology to spot potential flaws. The recognizer creates a less error-prone examination system in real time while identifying the gear flaws at a reasonable cost. The recognizer mostly employs an image collecting device to record physical gear images and then transforms the RGB photos into binary images using local filtering approaches and restoration processes. Later, the outputs of the processed image are the area of the faulty portion and compute the possible defective and non –defective gear as an output

Keywords


Defect detection, image processing, computer vision, thresholding, counting number of teeth.

Full Text:

PDF

References


Amandeep Mavi, Mandeep Kaur, (2012) ―Identify defects in Plastic (gears) using Digital image processing -A Review IRACST - International Journal of Computer Science and Information Technology & Security (IJCSITS), ISSN: 2249 -9555 Vol. 2, No.2, April 2012

. http://searchcio.techtarget.com/definition/Total-Quality-Management.

. Alisha Tremaine (2005), ―Characterization of Internal Defects in Open Die Forgings‖ FIERF Grant Project for Undergraduate Research November 17, 2005.

. S. Kamaruddin, Zahid A. Khan and S. H. Foong(2010) ― Application of Taguchi Method in the Optimization of Injection Moulding Parameters for Manufacturing Products from Plastic Blend ‖ IACSIT International Journal of Engineering and Technology, Vol.2, No.6, December 2010 ISSN: 1793-8236.

. Bernd Scholz-Reiter, Michael Lütjen, Hendrik Thamer, Dennis Dickmann, ―Towards Machine Vision based Surface Inspection of Micro-Parts‖, Recent Advances in Applied and Theoretical Mechanics, ISSN: 1790-2769 ISBN: 978-960-474- 1403.

Zhang Shujun, Chen Daqian, Xin Yingying, etc. Image based PET bottle cap and liquid level detection equipment [J]. Light industrial machinery, 2012, 2 (31):71-74.

] Zuo Jianzhong, Chen Xiqing, Yin Hui, etc. Edge detection based on wavelet transform [J]. Science and technology and engineering, 2007, 7 (8):1602-1604.

Wang Wencheng. Design of gear defect detection system based on Halcon [J]. Mechanical transmission, 2014,38 (9):60-64.

Yuan Tang lei, Dong Huajun, Tian Xiaojing, et al. A nonlinear model of binocular stereo vision system [J]. Journal of dalian jiaotong university, 2014, 33 (1): 53-55.

Sui Jing, Jin Weiqi. Realization of binocular stereo vision technology and its progress [J]. Application of electronic technology, 2004, (10):4-6.




DOI: https://doi.org/10.37628/ijcam.v9i1.1559

Refbacks

  • There are currently no refbacks.