Grinding dynamics characterization of ores by under sieve size
The magnetite ore was taken as the subject of study. Firstly,batch grinding experiments were performed by three distinct media environments of steel balls,ceramic balls,and binary media. Secondly,particle size characteristic curves were derived by sieving each grinding product. Finally,statistical analysis and linear regression calculations were applied to the under sieve size,and the grinding kinetics characteristics of magnetite ore under varying grinding media environments were revealed. The results show that under sieve size change rate of actual ores is influenced by grinding time. It does not conform to first-order kinetics but exhibits n-order kinetic characteristics,and the accuracy of linear regression calculation is relatively high. Although the grinding medium environment may affect the dynamic parameters of under sieve size,it does not alter the dynamic behavior,which still conforms to n-order dynamic characteristics. The linear correlation between the sieving particle size and grinding time of fine-grained magnetite is not significant(R2<0.90),indicating that it does not exhibit zero-order output characteristics,but rather demonstrates significant power function characteristics (R2>0.99). The expansion formula of the dynamic prediction model for under sieve size of actual magnetite ore is a binary composite function nested with exponential functions. The parameter functions s(x) and m(x) lack specific functional characteristics are both fourth-order polynomial functions,aligning with the n-order grinding kinetics variation law. They can accurately predict the trend of under sieve size changes and address the limitations of conventional cumulative yield kinetics in characterizing grinding characteristics.
万方数据
维普
