Wear Mechanism and Prediction Model of Polycrystalline Diamond Tool in Milling Sand Mould

doi:10.3901/JME.2018.17.124

Abstract

Abstract: For the advantage of patternless casting technology in mould making, the wear mechanism of PCD tool is studied and the prediction models of wear ratio are built based on the sand mould milling experiments with polycrystalline diamond (PCD) tool. The micro phase morphology of wear zone of PCD tool is observed by scanning electron microscopy, from which the change rule with the processing time and the wear mechanism are studied. The results show that the high frequency scrape and impact of the raised sand particles on the flank during the sand milling process lead to the cleavage fracture of diamond particles and the scraping of the bonding material among the PCD particles in the surface of the tool, which cause the diamond particles to fall off. Furthermore, the microscopic defects in the tool and the "hard spots" in the sand mould cause the cutter micro chipping. Based on support vector machine (SVM) regression analysis algorithm, Matlab is used to compile the regression program of the ratio of wear to milling volume to build the prediction model of wear ratio based on the orthogonal experimental results. The influence of process parameters on tool wear ratio are predicted with the model, which can provide the basis for the wear control of the tool with high efficiency processing sand mould.

Key words: patternless casting, PCD tool, support vector machine (SVM), wear mechanism, wear prediction model

CLC Number:

TH16

SHAN Zhongde, ZHU Fuxian. Wear Mechanism and Prediction Model of Polycrystalline Diamond Tool in Milling Sand Mould[J]. Journal of Mechanical Engineering, 2018, 54(17): 124-132.

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