光谱学与光谱分析 |
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Study on the Application of DBPSO Algorithm to Thickness Measurement of Surface Insulation Coating of Silicon Steel By NIR Spectrometry |
HE Jian-ping1,JIN Ping2 |
1. Automation Company of TISCO,Taiyuan 030003, China 2. Department of Electrical,Taiyuan University,Taiyuan 030009, China |
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Abstract A novel thickness measurement NIR spectrometry for surface insulation coating of silicon steel based on discrete binary particle swarm optimization (DBPSO) algorithm is presented. First, we used NIR spectrometer to collect the NIR spectra of insulation coating of silicon steel, and then, DBPSO algorithm was used to select the optimal wavelength variates and composed a new spectra set. Last, the authors created the thickness quantitative analysis model using kernel partial least square algorithm. The experimental results show that the absolute error range analyzed by created model was from -0.12 to 0.19 μm, and the maximal relative error was 14.31%, which completely met the practical measurement need. The research indicates that DBPSO is effective wavelength selection methods, which can efficiently select the wavelength variates carrying more useful information, improve the analysis accuracy and speed. And the NIR spectroscopy is an effective measurement method for thickness analysis of silicon steel insulation coating.
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Received: 2010-08-02
Accepted: 2010-12-08
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Corresponding Authors:
HE Jian-ping
E-mail: hejp@tisco.com.cn
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[1] HAN Xiao-guang, ZHANG Dun-ming(韩晓光,张墩明). Science & Technology Information(科技信息),2008,25: 376. [2] PENG Xue-lian(彭雪莲). Surface Technology(表面技术),2004,33(6):80. [3] CHEN Xiu-ming,LIN Li,LI Xi-meng,et al(陈秀明,林 莉,李喜孟,等). Journal of Aeronautical Materials(航空材料学报),2009,29(1): 87. [4] Pearson R K. Control Systems Technology,2002,10(1):55. [5] YAN Yan-lu,ZHAO Long-lian,HAN Dong-hai,et al(严衍禄,赵龙莲,韩东海,等). Foundation and Application of NIR Spectral Analysis(近红外光谱分析基础与应用). Beijing: China Light Industry Press(北京:中国轻工业出版社),2005. [6] Eberhart R,Kennedy J. IEEE Proceedings of the Sixth International Symposium on Micro Machine and Human Science. Nagoya:Japan, October 4-6, 1995,39. [7] Kennedy J, Eberhart R. IEEE International Conference on Neural Networks. Piscataway, Perth, Western Australia, 27,Nov.-1 Dec., 1995, 1942. [8] Brits R, Engelbrecht Andries Petrus, Van den Bergh F. Loating Multiple Optima Using Partiels Swarm Optimization Applied Mathematics and Computation, 2007: 189(2): 1859. [9] Kennedy J, Eberhart R. Proceedings of the Conference on Systems, Man, and Cybernetics, Orlando, FL, Oct. 12-15, 1997, 4104. [10] Smola A J, Learning with Kernels. Berlin: Technical University of Berlin, 1998. [11] Shawe-Taylor J, Cristianini N. Kernel Methods for Pattern Analysis. Cambridge: Cambridge University Press, 2004.
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