Open Access Journal

ISSN : 2394-6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

ISSN : 2394-6849 (Online)

Image Processing Based Defect Detection and Identification Algorithm for Industrial Pipes and Raspberry Pi Based Industrial Process Monitoring

Author : Aditi Gharge 1 Varsha Lembhe 2

Date of Publication :18th August 2017

Abstract: This paper present an algorithm for detecting and distinguishing certain manufacturing faults that may arise in case of industrial pipes manufacturing. In many of the industries, detection of defect is performed manually by skilled person. The major difficulties of manual o inspection method are lack of visibility, time consuming higher cost, and comparatively less acurte Therefore, this paper plans a new methodology for the automated detection of defect in pipes manufacturing process. Presence of holes and cracks in pipe are an vital indicator in manufacturing process to be cost-effective and avoid environmental damage . Furthermore, the paper give attention on monitoring three major industrial factors like temperature, water level, and light intensity. This system is designed with various sensors and raspberry pi. The design includes interfacing of sensors with PIC controller and LCD display. Thus our system is designed for multiple input and output activities for industrial applications

Reference :

  1. [1] Ragvaran K, J. Thiyagarajan (ph.D), “Raspberry PI Based Global Industrial Process Monitoring Through Wireless Communication”, International Conference on Robotics, Automation, Control and Embedded Systems – RACE 2015.

    [2] Darshani B., E. Vigneswaran, “Industrial Process Monitoring and Control Using Raspberry Pi”, ARPN Journal of engineering and applied sciences, vol.11, no.2, January 2016.

    [3] Amol A.Dharmapurikar, R.B. Waghmare, “Design & Implementing A Secured Wireless Communication System By Using Gprs & Raspberry Pi In Automation”, International Journal Of Science, Technology & Management Volume No.4, Issue No.3, March 2015.

    [4] Md. Ashraful Alami , M M Naushad Ali Musaddeque Anwar AI-Abedin Syedi , Nawaj Sorifi , Md. Abdur Rahamani, “An Algorithm to Detect and Identify Defects of Industrial Pipes Using Image Processing”, IEEE,20 14.

    [5] Yong xiong Wang and Iianbo Su, "Automated defect and contaminant inspection of HVAC duct." Automation in Construction, vol. 41, (Science Direct),2014.

    [6] Tung-Ching Su, Ming-Der Yang and Ii-Yuan Lin,"Morphological segmentation based on edge detection for sewer pipe defects on CCTV images. " Expert Systems with Applications, vol. 38, no. 10, pp. 13094-13114, September 2011.

    [7] O. Duran, K. Althoefer and L. D. Seneviratne, "Automated pipe defect detection and categorization using camera/laser-based profiler and artificial neural network," IEEE Trans. on Automation Science and Eng., vol. 4, no. l, pp. 118-126, January 2007.

    [8] Wu Xue-Fei, Baihua "Automated assessment of buried pipeline defects by image processing," in Proc. of IEEE International Conference on Intelligent Computing and Intelligent Systems, 2009, vol. 4, pp. 583-587, November 2009

    [9] Matthieu Jones, Donald Bailey, Liqiong Tang, “Prototype of High Speed Pipe Inspection Robot”, 19th International Conference on Mechatronics and Machine Vision in Practice (M2VIP12), 28-30th Nov 2012, Auckland, NewZealand

    [10] I. Abdel-Qader, M. E. Kelly and O. Abudayyeh, "Analysis of edge detection techniques for crack identification in bridges,"1. Comput.Civil Eng. , vol. 17, no.4, pp. 255-263, October 2003.

    [11] O. Folorunso and O. R. Vincent, "A Descriptive Algorithm for Sobel Image Edge Detection," in Proc. of 9th Conf. on Informing Science and IT Education (InSITE), Macon, GA, USA, pp. 97- 107, 2009.

    [12] Tung-Ching Su, Tsung-Chiang Wu, Ii-Yuan Lin and Ming-Der Yang, "Morphological segmentation based on edge detection for sewer pipe defects on CCTV images. " Expert Systems with Applications, vol. 38, no. 10, pp. 13094-13114, September 2011.

    [13] T. Azizzadeh, M. S. Safizadeh, “Automated Detection of Inner Surface Defects in Pipes Using Image Processing Algorithms”, Int J Advanced Design and Manufacturing Technology, Vol. 5/ No. 5/ December – 2012.

    [14] O. R. Vincent, O. Folorunso, “A Descriptive Algorithm for Sobel Image Edge Detection”, Proceedings of Informing Science & IT Education Conference (InSITE) 2009


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