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Abstract

To study the correlation between noise and vibration during dry milling of aluminum alloy, a synchronous acquisition system of noise and vibration was established. Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on the least square method and MATLAB software programming, the multiple regression models of milling noise on milling parameters and milling vibration were established. According to the regression models, it is found that there is a strong correlation between milling noise, milling parameters, and milling vibration. The maximum value of the correlation coefficient R is 0.98. It also shows that the regression models based on milling parameters and milling vibration can well predict the noise of aluminum alloy during milling. In addition, the obtained model can provide a control equation for the future coupling analysis of vibration and noise and for the numerical simulation.

Keywords

Milling noise milling vibration milling parameters multivariate regression model of sound pressure level least square method

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Correlation analysis of noise sound pressure and vibration in aluminum alloy milling

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