Abstract
In order to establish the combined prediction model of milling noise based on force-thermal-vibration multi-feature fusion, a simultaneous milling noise-vibration-thermal-force test system was established. Based on the gray correlation theory and test data, the relationship between milling sound pressure and milling parameters, milling vibration, milling force, and milling thermal was analyzed. Based on the least square method, three single prediction models of milling sound pressure level for three-directional vibration, milling thermal, and three-directional milling force were established. Then, the weight coefficients of the combined model are determined by the standard errors of the three single models, and the linear combination model of the mean square root of milling sound pressure level expressed by the three single prediction models and the corresponding weight coefficients was established. The correlation coefficient of the combined prediction model of sound pressure is 0.95, which is larger than the correlation coefficient of three single prediction models. It shows that the combined prediction model of sound pressure level with multiple features can better predict milling noise and provide theoretical guidance for milling tool condition monitoring.
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