Abstract
By using depth from focus (DFF) alone to obtain the 3D wear area reconstruction of grinding wheel, the depth values in the 3D wear area image are not continuous while by using shape from shading (SFS) alone, the 3D wear area cannot be fully obtained. A novel method that uses Fourier transform to fuse the methods of DFF and SFS is proposed in this paper. The proposed method can achieve depth continuity in tool wear images. After performing high-pass filtering and low-pass filtering for the 3D reconstructed images of DFF and SFS, respectively, in frequency domain, the 3D wear area reconstruction image of grinding wheel can then be obtained by Fourier inversion. Experimental results showed that the 3D wear area reconstruction image obtained by the proposed method can achieve better accuracy for the tool wear volume than using DFF or SFS alone. And the efficiency of the proposed method is proved to be better than microscopes.
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Aibin Zhu, Dayong He and Jianwei Zhao contributed equally to this work.
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Zhu, A., He, D., Zhao, J. et al. 3D Wear Area Reconstruction of Grinding Wheel by Frequency-Domain Fusion. Int J Adv Manuf Technol 88, 1111–1117 (2017). https://doi.org/10.1007/s00170-016-8846-3
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DOI: https://doi.org/10.1007/s00170-016-8846-3