A machine vision system for inspecting mechanical parts
Year: 2025
Type: article
Abstract: Computer vision-based inspection has become widely used in manufacturing industries for part identification, dimensional inspection, and guiding material handling systems. Defect-free production cannot be achieved with sampling inspection methods; therefore, a 100 percentage inspection approach is mandatory to meet the zero-defect goals of manufacturing industries. Achieving this is possible with advanced technologies, such as vision-based inspection systems. In this study, a vision-based inspection system is proposed for part identification, defect detection, and dimensional measurement. The system is validated using machined parts, including a Druck plate, Pressure plate, and Retainer. A part identification algorithm is developed based on a geometry search approach. The inspection algorithm classifies parts based on edge relationships, utilizing edge detection techniques to identify each part's geometric features. Surface defects are identified by analyzing the pixel intensity gradients within defective regions. The system measures part dimensions using a vision system, with results comparable to those obtained from a coordinate measuring machine.
Source: Machine Graphics and Vision
Author: Rajamani Rajagounder
Institution: PSG College of Technology
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408972183