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As the advantages of high forming accuracy, fast material removal efficiency and slight machining defects, the ultraprecision grinding using micro-powder diamond wheel has been widely applied to the processing of large aperture and complex surface optical elements. Due to the brittleness and hardness of optical materials, micro-powder diamond wheel is easy to wear during grinding process, which affects the surface roughness and depth of sub-surface damage layer of components. In order to accurately characterize the wear state of diamond wheel in the grinding process, a method based on in-situ micro-observation of grinding wheel and abrasive particle image contour recognition was proposed to detect the diamond wheel. First, based on the grinding experiments, the surface micromorphology of grinding wheel was acquired by in-situ microscopic observation, and the wear forms of the grinding wheel were analyzed. Then the average distribution density of wear particles and average wear area were taken as the evaluation parameters of the wear state of the wheel. After outstanding the edge profile of abrasive particles by Laplacian enhancement operator and binary processing, the edge profiles of wear particles were extracted out. And by calculating the number and projection area of each wear abrasive particles, the average distribution density of wear particles and the average wear area in the measured region on the surface of grinding wheel were obtained. At the end, the wear state of resin bonded diamond grinding wheel used for grinding fused silica optics was tested. The experimental results showed that the diamond wheel states of initial wear stage and steady wear stage were accurately identified by the parameters of distribution density of wear abrasive particles and average wear area.
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