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Statistical methods to compare batch flotation grade-recovery curves and rate constants

机译:比较批次浮选品位-回收率曲线和速率常数的统计方法

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摘要

Grade-recovery curves obtained from kinetic batch flotation testing are, like any other measurement, subject to experimental error. This leads to uncertainty in the true position of each cumulative grade-recovery point, the curve itself, and the kinetics. This uncertainty is rarely if ever taken into account when interpreting such curves, in particular when comparing curves obtained under different conditions. This paper proposes a methodology to deal with this problem. The standard formula is used to establish true confidence intervals for the grade and recovery at each replicated timed concentrate point, and the 2-sample t-test is used to compare these point values between tests conducted under different conditions. The properties of the grade-recovery curves can be compared by fitting an appropriate model to the two data sets and using a bootstrap to create distributions of differences between the model parameters and the model predictions of recovery at any chosen concentrate grade, reflecting the uncertainty in the original data. It is then easy to construct hypothesis tests on the parameter differences and on the mean difference at the chosen grade(s) between the two curves. The same approach can be used to construct confidence intervals on the fitted curves and to test differences in estimated flotation rates. An extra sum of squares test can be used to compare the fitted grade-recovery curves as a whole. Details of the methods are presented, suitable for spreadsheets.
机译:与其他任何测量方法一样,从动力学间歇浮选测试中获得的品位恢复曲线也容易受到实验误差的影响。这将导致不确定每个累积坡度恢复点的真实位置,曲线本身以及动力学。在解释此类曲线时,尤其是在比较不同条件下获得的曲线时,很少考虑到这种不确定性。本文提出了一种解决该问题的方法。标准公式用于建立每个重复定时浓缩点的品位和回收率的真实置信区间,而2样本t检验用于比较在不同条件下进行的测试之间的这些点值。可以通过将合适的模型拟合到两个数据集并使用引导程序创建模型参数与模型预测之间的差异分布来比较品位恢复曲线的特性,该预测参数反映了所选精矿品位,反映了不确定性。原始数据。这样就很容易针对两条曲线之间所选等级的参数差异和均值差异构建假设检验。可以使用相同的方法在拟合曲线上构建置信区间,并测试估计浮选率的差异。可以使用额外的平方和检验来比较拟合的坡度-恢复曲线的整体。给出了方法的详细信息,适用于电子表格。

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