A theoretical model for predicting the Peak Cutting Force of conical picks

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Published Dec 23, 2013
DOI https://doi.org/10.3221/IGF-ESIS.27.06

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Gao Kuidong
School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China
Du Changlong
School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China
Jiang Hongxiang
School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China
Liu Songyong
School of Mechanical and Electrical Engineering, China University of Mining & Technology, Xuzhou 221116, China

Abstract

In order to predict the PCF (Peak Cutting Force) of conical pick in rock cutting process, a theoretical model is established based on elastic fracture mechanics theory. The vertical fracture model of rock cutting fragment is also established based on the maximum tensile criterion. The relation between vertical fracture angle and associated parameters (cutting parameter n and ratio B of rock compressive strength to tensile strength) is obtained by numerical analysis method and polynomial regression method, and the correctness of rock vertical fracture model is verified through experiments. Linear regression coefficient between the PCF of prediction and experiments is 0.81, and significance level less than 0.05 shows that the model for predicting the PCF is correct and reliable. A comparative analysis between the PCF obtained from this model and Evans model reveals that the result of this prediction model is more reliable and accurate. The results of this work could provide some guidance for studying the rock cutting theory of conical pick and designing the cutting mechanism.

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    Issue
    Vol. 8 No. 27 (2014): January 2014
    Section
    Miscellanea

    How to Cite

    Kuidong, G., Changlong, D., Hongxiang, J., & Songyong, L. (2013). A theoretical model for predicting the Peak Cutting Force of conical picks. Frattura Ed Integrità Strutturale, 8(27), pages 43–52. https://doi.org/10.3221/IGF-ESIS.27.06

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