A Registration Method for Profile Error Inspection of Complex Surface Under Minimum Zone Criterion
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Although registration of the measured model and the design model has been widely studied, it remains an open problem in complex surface profile error inspection. False rejection of some qualified parts is prone to occur due to the improper registration between the measured points and the nominal model. To solve this problem, we define a surface profile error metric in terms of a new range norm under minimum zone criterion. An optimal framework based on the range norm is proposed to find the registration pose of the measurement data set, in which the surface profile error is minimized. To deal with the computational intractability, the non-differentiable merit function is uniformly approximated by a smooth aggregation function, which can be effectively solved with the limited-memory Quasi-Newton method. Distinct numerical stability control and the active set selection mechanism are proposed to guarantee the accuracy and efficiency of the method. Experiments on a simulated and a real part are included to verify the superiority of the proposed method.
KeywordsSurfaces inspection Profile error Registration Minimum zone criterion Aggregation function Norm
This work was supported by Natural Science Foundation of China (Grant No. 51575276).
- 1.ISO 17450-1. (2011). Geometrical Product Specifications (GPS)—General Concepts—Part 1: Model for Geometrical Specification and Verification.Google Scholar
- 6.Peng, W., Ji, W. X., Chen, W. L., & Shao, K. (2018). Rigid surface matching by analysis and correspondences. International Journal of Precision Engineering and Manufacturing, 19(9), 1360–1376.Google Scholar
- 10.International Organization for Standardization, Geneva, Switzerland. (2004). ISO 1101: Geometrical Product Specifications (GPS)—tolerances of form, orientation, location and run out, 2nd edn.Google Scholar
- 11.International Standard Organization. (2007). ISO/TS 17450-1-2007, Geometrical product specifications (GPS)-General concepts—Part 1: Model for geometrical specification and verification, Switzerland: ISO Copyright Office.Google Scholar
- 12.ISO 25178-2. (2012). Geometrical product specifications-surface texture: Areal part 2: Definitions and surface texture parameters.Google Scholar
- 22.Zhang, X., Xiao, H., Zhang, H., He, X., & Xu, M. (2016). Uncertainty estimation in form error evaluation of freeform surfaces for precision engineering. In Proceedings of SPIE (vol. 9903, p. 99031G).Google Scholar
- 32.Cui, C., Lia, T., Blunt, A., Jiang, X., Huang, H., Ye, R., & Fan, W. (2013). The assessment of straightness and flatness errors using particle swarm optimization. In 12th CIRP Conference on Computer Aided Tolerancing, Procedia CIRP 10 (pp. 271–275).Google Scholar
- 33.Chen, Y. F., Zhu, L. Q., Chen, Q. S., & Meng, H. (2010). Evaluation of the profile error of complex surface through particle swarm optimization. In International conference on advanced technology of design and manufacture (pp. 148–152).Google Scholar
- 35.Zhang, K. (2008). Spatial straightness error evaluation with an ant colony algorithm. In Proceedings of the IEEE international conference on granular computing (GRC08), Piscataway: IEEE Press (pp. 793–796).Google Scholar
- 36.Liu, J., Wang, G. L., & Pan, X. D. (2011). Minimum-zone form tolerance evaluation for cylindrical surfaces using adaptive ant colony optimization. Journal of Computational Information Systems, 7(12), 4480–4490.Google Scholar