1 Â Â Â Grinding design test technology research
There are currently three main types of methods for predicting the power consumption of a grinding process: a Bond-based approach, a proprietary test (eg SPI, SMC)-based model approach, a complex population balance /smash model/grading model approach. . All methods for predicting the unit power consumption of a grinding process are empirical.
    The mineral processing researchers studied the grinding characteristics of the ore itself, determined the grinding parameters of the ore, and established the selectivity function and fragmentation function of the ore grinding. The various models of computer simulation techniques are then used to scale up and design the semi-self-grinding circuit and the ball-milling circuit. At present, the Canadian SGS law, the Australian OMC (Orway Mineral Consultants Ltd) company law, the University of Queensland Mineral Research Center ( JKMRC) method, and the Metso company's overall balance simulation method (PBM) have been used for commercial services.
2 grinding theory research
    Guan Yamei et al. studied the parameter determination method of self-grinding machine semi-autogenous grinding machine. It is proposed that there are basically three methods of similar calculation, semi-empirical formula calculation and theoretical formula calculation of ball mill using self-grinding mill grinding power calculation, and enumerated Related formulas. Ji Shao Jiangang, who referred the application of power law in the selection of the SAG mill.
    Hou Ying et al. studied the effect of grinding kinetic parameters on grinding speed. Yin Hai et al. studied the effect of transfer rate on grinding fineness. It uses the frequency change speed laboratory ball mill, grinding experimental study Dahongshan copper ore. Dong Weimin and others studied the kinematics of the grinding medium of the super-speed ball mill , and obtained the trajectory equation of the grinding medium of the super-speed ball mill, the impact velocity of the ore, the impact force formula and the number of impacts. Yuan Dong et al. studied the regression model of grinding effect.
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