Computer vision algorithms for measurement and inspection of spur gears

Precision measurement of gears plays a vital role in gear measurement and inspection. The current methods of gear measurement are either time consuming or expensive. In addition, no single measurement method is available and capable of accurately measuring all gear parameters while significantly reducing the measurement time. The aim of this paper is to utilize the computer vision technology to develop a non-contact and rapid measurement system capable of measuring and inspecting most of spur gear parameters with an appropriate accuracy. A vision system has been established and used to capture images for gears to be measured or inspected. A software (named GearVision) has been especially developed in-house using Microsoft Visual C++ to analyze the captured images and to perform the measurement and inspection processes. The introduced vision system has been calibrated for metric units then it was verified by measuring two sample gears and comparing the calculated parameters with the actual values of gear parameters. The maximum differences between the calculated parameters and the design values were ±0.101 mm for a spur gear with 156 mm outside diameter. For small gears, higher accuracy could be obtained and as well as small difference.

► Computer vision technology has been utilized to develop a non-contact and rapid measurement system capable of measuring and inspecting most of spur gear parameters.
► A vision system was used to capture Images for sample gears and a software has been developed, in-house, to perform the measurement and inspection processes.
► The introduced vision system has been calibrated for metric units and it was verified by comparing the calculated parameters for sample gears with the design values of standard gear parameters.
► The maximum differences between the calculated parameters and the design values were 0.101 mm for a spur gear with 156 mm outside diameter. For small gears, higher accuracy could be obtained as well as small difference