Gear Integrated Error Determination Using the Gaussian Template Convolution-Facet Method

Abstract

A gear integrated error, a combination of individual and composite errors, carries richer information and has long been a key target of classic gear error measurement techniques. However, in the age of intelligent manufacturing, the classic methods for gear integrated error measurement are no longer able to meet the emerging requirements of large-scale gears and real-time online measurement. To address this gap, a novel approach to obtaining the gear integrated error based on GTC−Facet (Gaussian template convolution-Facet) is proposed. This method accurately pinpoints the sub-pixel contour of gears in images, enabling a quick derivation of the gear integrated error curve. From this curve, other individual and composite errors can be analyzed. The gear error information obtained through our method has higher measurement accuracy, achieving a positioning accuracy of 3.6 μm for the gear profile. Moreover, during the measurement process, the measured gear remains unclamped, and the entire measurement process can be completed within 0.35 s, which is much faster than classic methods. Our method meets the demands of online measurements and provides a new avenue for gear error measurement.