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10 October 2013 Self-adaptive grain recognition of diamond grinding wheel and its grains assessment
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Proceedings Volume 8916, Sixth International Symposium on Precision Mechanical Measurements; 89162H (2013) https://doi.org/10.1117/12.2035785
Event: Sixth International Symposium on Precision Mechanical Measurements, 2013, Guiyang, China
Abstract
An improved Canny operator based on the method of Maximum Classes Square Error is adopted to get a self-adaptive threshold for grain recognition. First, a grinding wheel surface was measured by using a vertical scanning white light interferometric (WLI) system and reconstructed with an improved centroid algorithm; then the grains were extracted using the proposed method based on the fact that the peak intensity difference (ΔI) between maximum and minimum intensities on interferometric curve from diamond is larger than that from bond due to different reflective characteristics of different materials; third the grain protrusion parameters are investigated for grinding performance analysis. The experiments proved that the proposed grain recognition method is effective and assessment parameters are useful for understanding grinding performance.
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Changcai Cui, Lijun Zhou, Qing Yu, Hui Huang, and Ruifang Ye "Self-adaptive grain recognition of diamond grinding wheel and its grains assessment", Proc. SPIE 8916, Sixth International Symposium on Precision Mechanical Measurements, 89162H (10 October 2013); https://doi.org/10.1117/12.2035785
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