Abstract
A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares (FLS)-support vector machine (SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.
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Foundation item: Project(2012BAK09B02-05) supported by the National Key Technology R&D Program of China during the Twelfth Five-year Period; Project(51274250) supported by the National Natural Science Foundation of China
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Zuo, Hy., Luo, Zq., Guan, Jl. et al. Identification on rock and soil parameters for vibration drilling rock in metal mine based on fuzzy least square support vector machine. J. Cent. South Univ. 21, 1085–1090 (2014). https://doi.org/10.1007/s11771-014-2040-2
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DOI: https://doi.org/10.1007/s11771-014-2040-2