Automated inspection of spur gears using machine vision approach

The paper presents a machine-vision-based system for automated inspection of standard spur gears. Image processing algorithms are used for the measurement of important gear dimensions such as radii of addendum circle, dedendum circle and pitch circle, module, number of teeth, pressure angle, tooth thickness, circular pitch, radial run-out and tooth alignment error. Deviations from theoretical values according to gear standards are computed and a decision is made regarding acceptance/rejection. The performance of machine vision inspection system is evaluated in terms of its accuracy and precision. Accuracy is based on deviation of machine vision values from those obtained using traditional metrology instruments and gear standards. Precision is measured using partial gauge R&R study. The results obtained for gear images taken by different operators using different imaging devices are repeatable, reproducible and in good agreement with the true values. The results indicate that the machine vision approach is accurate and precise.