基于级联粗糙集的数控机床智能诊断方法的研究

摘要

By considering the complexity influencing factors of CNC machinery fault,the application of cascade rough set on the NC machine fault diagnosis is analyzed. Take vibration signal amplitude of tool spindle, feeding spindle and knife library as the condition attributes, the first level rough set is used to determine the fault parts in tool spindle. Then, in the second rough set, the spindle frequency, vibration amplitude, high frequency components of energy and frequency distribution is used as the condition attributes to analysis the fault reason. The methods of cascade rough set can reduce the condition attributes and the decision accuracy is improved.%采用级联粗糙集进行数控机床故障诊断.以数控机床主轴、进给和刀库各部件振动信号幅值为条件属性,进行第一级粗糙集决策并诊断出主轴故障;进而通过主轴的转频、振动幅值、高频成分的能量及频率分布情况为条件属性,进行第二级粗糙集决策并诊断出产生故障的具体原因.级联粗糙集分析方法减小了由条件属性较多导致决策精度变差的可能性,提高了数控机床智能诊断的精度.