Developing Inspection Robot for Corrosion Detection in Pipes by Image Processing Method
Authors
Tzu-Chia Chen
College of Management and Design, Ming Chi University of Technology, New Taipei City, Taiwan, ROC
Dikambai Nurdaulet
Position Master of Pedagogical Sciences, Place of work Kazakh National Pedagogical University Named After Abai, Kazakhstan
Nurgali Zaurbekov
Position Doctor of Technical Sciences, Professor of the Department of Informatics and Informatization of Education, Place of Work Kazakh National Pedagogical University Named After Abay, Kazakhstan
Dikambai Nurdaulet
Position Master of Pedagogical Sciences, Place of Work Kazakh National Pedagogical University named After Abai, Kazakhstan
Nurgali Zaurbekov
Position Doctor of Technical Sciences, Professor of the Department of Informatics and Informatization of Education Place of work Kazakh National Pedagogical University named after Abay, Kazakhstan
Corrosion of transmission pipes causes wear and failure of systems, and other disadvantages include financial losses for replacing the system, maintenance costs, system failure and the need for repairs, contamination of products. In contact, leakage or destruction of products and causing danger to life is indicated. Therefore, in this paper, the method of checking and detecting the location of corrosion and detecting the level of corrosion for timely repair and replacement of parts is presented. The proposed method is based on image processing algorithms, and as a result, it is included in the category of non-destructive inspection methods. The innovation of the proposed method is both in providing a new processing algorithm for identifying corrosion and in providing a suitable lighting method. In this method, first the correct lighting is done and then the images obtained from the inspection are pre-processed for the identification stage. Image pre-processing includes changing the color format, removing noise and smoothing. Then the corrosions are identified by the edge detection algorithm and their amount is estimated by morphological operations. The results show that the presented method has been able to accurately detect corrosion in complex pipes.
