Automated Dimensional Analysis and Defect Recognition Using X-ray Images of Machinery Parts
Aman Kumar Mahapatra, Satyam Oza R · 2021
In the modern world, due to contemporaneous globalization and industrial revolutions many industries got nurtured into huge economies, thereby being a crucial source of income for countries around the globe. In that framework, the role of hardware and manufacturing industries, heavy machinery, and electrical companies became important and is still relevant as yet. This opportunity presents great scope for engineering fields to discover various techniques to make the process easier and efficient in terms of time, cost of manufacturing, and maintenance. While recognizing efficiency in terms of production quality and low maintenance it's crucial to consider errors which in heavy machinery parts are subjected to defects like Voids, Cracks, inclusions, notches, rough lines and any other metallurgical changes, etc. This paper highlights our key findings on automated methods of recognition of such defects and its dimensional analysis using Xray images. Now further these defects are classified into External or Surface-level defects and Internal or Non-surface level defects, external defects are easier to find on a machinery part but internal defects are a very serious concern.