Estimation of the surface roughness of K9 optical glass in precision grinding using the brittle material removal fraction based on an improved image processing algorithm

Abstract

Estimation of the surface roughness of K9 optical glass in precision grinding using the brittle material removal fraction based on an improved image processing algorithm In optical glass grinding, material removal of the workpiece surface generally consists of a simultaneous brittle and ductile removal mode. In previous work, the area fraction of brittle material removal on a machined surface, termed the brittle material removal fraction (BRF), was used to sense the surface roughness of optical glass during ultrasonic vibration-assisted grinding (UAG). In this work, to verify the significance of the BRF on material removal during traditional machining of optical glass, the BRF of K9 glass in precision grinding (PG) was investigated. By analysing the characteristics of a micro-topography image of the machined surface, an improved image processing algorithm was developed to calculate the BRF in PG, based on the previous image processing algorithm for UAG. A series of PG experiments were conducted to estimate the influence of machining conditions, including cutting depth, wheel speed and feed rate, on the BRF. Surface roughness and grinding forces were also measured to investigate the relationships between the BRF, surface quality and process parameters in PG of K9 glass. Experimental results show the improved image processing algorithm is valid to obtain the BRF of optical glass during PG and the BRF is also a reasonable variable to sense surface quality during PG of optical glass.