基于EMD复杂度与鉴别信息的磨削颤振预测

为避免磨削加工中出现颤振,提出一种基于经验模式分解(empiracal mode decomposition,简称EMD)复杂度与鉴别信息的颤振预测方法。采用经验模式分解对磨削加工中滤波后的振动信号进行分解,获得振动信号的本征特征函数;采用L-Z复杂度指标对本征特征函数进行复杂度分析,获得磨削颤振特征值;采用鉴别信息对复杂度变化进行量化,通过鉴别信息对磨削加工颤振进行预测。在外圆磨床实验平台对该方法的有效性进行了验证,分别采用变工件转速、变砂轮转速和变磨削厚度3种加工方式逼近颤振状态。分析结果表明,当磨削加工趋于颤振时对应的鉴别信息值增大。实验结果通过鉴别信息的大小可以对磨削加工中的颤振进行预测。

Method of Grinding Chatter Predicting Based on Complexity of EMD and Discrimination Information

In order to avoid grinding chatter, a new method to predict grinding chatter is presented in the grinding process based on complexity of empirical mode decomposition and discrimination information. In this method, firstly, empirical mode decomposition is used to obtain the intrinsic mode function of filtered vibration signal detected in the grinding process. Then, complexity of intrinsic mode function is calculated by the L-Z complexity, and the characteristic value of grinding chatter prediction is obtained. Finally, the analysis of discrimination information is used to quantify the changing of complexity, and discrimination information is used to predict grinding chatter in grinding process. In this paper, cylindrical grinding experimental platform is used to verify the validity of this method. Three different processing which are varying workpiece speed, varying grinding wheel speed and varying grinding depth are operated to tend to chatter state, then we use this method to analyze vibration signals detected in three different processing. Experimental results show that when three different processing tend to chatter state, discrimination information will increase gradually, therefore, the value of the identification information can predict chatter in the grinding.