Mathematical model for predicting sawing force of granitic rocks considering stochastic grains distribution and material elastic recovery. (October 2022)

• Record Type: Journal Article
• Authors: Sun, Depeng; Zhang, Heng; Zhang, Jinsheng
• Is Part Of: Measurement. Volume 202(2022)
• Publication Date: 2022-10
• Subjects: Sawing force model -- Frame saw -- Material elastic recovery -- Stochastic grains distribution; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.111822
• Languages: English
• ISSNs: 0263-2241

Abstract

Graphical abstract: Highlights: A novel model for predicting sawing force is developed. The distribution of abrasive grain and material elastic recovery are considered. Predicted sawing force are in good agreement with the experimental results. The hardness showed the highest influence on sawing force. Considering the material elastic recovery can improve the accuracy of the model. Abstract: The sawing force is the vital factor that affects the surface shape deviation and segment wear. However, the sawing force model in sawing rock by frame saw has not been reported yet. In this study, a theoretical sawing force model is proposed considering the distribution of abrasive grains and material elastic recovery. The kinematics equations of the sawing trajectory are analyzed in detail, and the stochastic grain density function is drawn to describe the distribution of grains. Then, experiments were carried out to verify the developed model, and the average error between predicted and experimental force is 4%. Finally, Extended Fourier Amplitude Sensitivity Test (EFAST) is used to analyze the parametric sensitivity analysis. The results showed that hardness, flywheel speed, and feed speed are the main influencing factors. Therefore, the developed model can provide a better understanding of the effects of process parameters and material properties on the sawing force.