For the limitation of the single-factor ball mill load prediction, we extracted the characteristic information values of vibration, grinding and current in the grinding process, and used the support vector machine (SVM) combined with grid search and cross-validation for grinding machine load prediction.By determining the type of mill load, we obtained the basic reliability distribution function (mass function).Through the improved D-S evidence fusion rule, a multi-source heterogeneous signal feature layer fusion method for mill load was proposed.Through the example verification and comparison between different algorithms, we found when the method is applied to the mill load prediction, higher confidence, faster convergence, and greater stability fusion results are obtained.
Key words
Mill load /
D-S evidence /
Multi-source signal /
Signal fusion
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