Surface Quality Analysis Of Magnesium Alloy Sheet Based On Abrasive Belt Grinding And Grinding Technological Parameter Prediction

Magnesium Alloy is the lightest metal structure material being used in the industry currently, which has little density, high strength and stiffness, good casting performance, shock absorption, cutting performance, measurement stability, electromagnetic shielding and bountiful resource, easily retrieved, so it is widely used in aeromagnetic& aerospace, automobile, electronic, and others. But it has the defect of poor corrosion resistance, wear resistance, heat resistance, surface protect of Magnesium Alloy is a key technique to be solved. In modern industry, abrasive belt technique as a new grinding processing which has high efficacy, economical, widely use is regard as a very important processing method being compared to grinding wheel. So the paper proposes a method that uses abrasive belt to do surface pre-processing of Magnesium Alloy in the field of magnesium alloy processing, though this processing technique is not widely used, it has widely application prospect, it is very necessary to study surface quality of Magnesium Alloy based on abrasive belt grinding. Surface quality of Magnesium Alloy sheet is a important index as evaluating pre-processing quality of Magnesium Alloy base, though it reflects surface geometric characteristic and superficial layer characteristic, it has a big influence on surface processing of magnesium alloy sheet, wear resistance, matching quality, fatigue strength resistance, corrosion resistance and other using performance of Magnesium Alloy sheet. So studying surface quality of Magnesium Alloy sheet is very important, it not only improves the surface pre-processing of Magnesium Alloy, but also extends application range of Magnesium Alloy, it can also spread the use in Magnesium Alloy machining adopting abrasive belt grinding.Through experimental study and observing, measuring, relating to currently existing document data, the main efforts of this paper follow:(1) When we use abrasive belt to grind AZ31B Magnesium Alloy sheet, the grinding lines of surface is very clear and perfect, there is no bur on the surface of AZ31B sheet. Chipped grain is ploughed on the surface, metal slippage on both sides of chipped grain upheaval and pushes out, and the metal yields slippage, it has good surface quality.(2) Study the surface roughness of AZ31B Magnesium Alloy sheet adopting orthogonal experiment and one-factor experiment, grain size of abrasive belt has a big influence on the surface roughness, the following is abrasive belt velocity, feed velocity of grinding head, voltage of proportional valve. In the same condition, surface roughness reduces as grain size thins; the high abrasive belt velocity, the small surface roughness; feed velocity of grinding head has an influence on the surface roughness, the small the feed velocity, the low surface roughness.(3) The greater the grinding depth, the larger the remaining press stress of AZ31B Magnesium Alloy sheet when using thick grain size of abrasive belt. But when it gets to a certain grinding depth, the remaining press stress will diminish. The greater the grinding depth, the larger the remaining press stress when using thin grain size of abrasive belt, but the remaining press stress using thick grain size of abrasive belt is larger than the remaining press stress using thin grain size of abrasive belt.(4) The greater the grinding depth, the larger the hardness of AZ31B Magnesium Alloy sheet when using thick grain size of abrasive belt. But when it gets to a certain grinding depth, the hardness will diminish. The greater the grinding depth, the larger the hardness when using thin grain size of abrasive belt, but the hardness using thick grain size of abrasive belt is larger than the hardness using thin grain size of abrasive belt.Because of its complexity of processing procedure using abrasive belt, we adopt artificial neural net to predict grinding processing parameters. We build a model between grinding processing parameters(grain size of abrasive belt, abrasive belt velocity, feed velocity of grinding head, voltage of proportional valve) and surface roughness, surface hardness through BP neural network theory, and compare the predicting results of BP model to the experimental results, the results indicate that its correct and function to predict grinding processing parameters using BP neural network, it has the reference value to the study of Magnesium Alloy sheet performance and design and manufacturing of abrasive belt grinding machine.