基于GWO-VMD的铣削刀具磨损状态监测  

Tool Wear Detection Based on Grey Wolf Optimized Variational Mode Decomposition

作　　者：孔前程 陈堂艳 魏伟 KONG Qiancheng;CHEN Tangyan;WEI Wei(School of Mechanical Engineering,Guangxi University,Nanning 530004,China;State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures,Guangxi University,Nanning 530004,China)

机构地区：[1]广西大学机械工程学院,南宁530004 [2]广西大学省部共建特色金属材料与组合结构全寿命安全国家重点实验室,南宁530004

出　　处：《组合机床与自动化加工技术》2025年第3期187-191,198,共6页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家重点研发项目(2022YFB4601601);广西科技计划项目基地与人才专项项目(GKAD23026149)。

摘　　要：针对铣削过程中刀具磨损对工件质量和效率的影响,提出一种基于灰狼优化(grey wolf optimizer,GWO)变分模态分解(variational mode decomposition,VMD)的刀具磨损状态监测方法。首先,以原始信号与固有模态函数(intrinsic mode functions,IMFs)的能量差作为适应度函数,通过GWO寻找VMD的最佳参数。其次,VMD将铣削力信号分解为IMFs,对IMFs进行希尔伯特黄变换(hilbert-huang transformation,HHT)。结果表明,GWO能准确寻找VMD的最佳参数(8,3977)。在GWO-VMD-HHT中,特征频率清晰直观,并且观察到了明显的能量频移现象。刀具磨损状态相关的频率主要集中在主轴频率及其倍频上。通过分析HHT谱中特定频率的能量分布情况,可以有效地识别刀具的磨损状态。A method for monitoring the tool wear status in milling processes was proposed to address the issues concerning its impact on workpiece quality and efficiency.This method was based on grey wolf optimizer(GWO)and variational mode decomposition(VMD).Initially,the energy difference between the raw signal and the intrinsic mode functions(IMFs)was utilized as the fitness function,and GWO was employed to search for the optimal parameters of VMD.Subsequently,VMD decomposes the milling force signal into IMFs,which were then subjected to the hilbert-huang transformation(HHT).The results demonstrate that GWO accurately identifies the optimal parameters for VMD(8,3977).Within the framework of GWO-VMD-HHT,the characteristic frequencies are distinctly visualized,revealing noticeable energy frequency shifting phenomena.Frequencies relevant to tool wear status predominantly concentrate around the spindle frequency and its harmonics.By analyzing the energy distribution of specific frequencies in the HHT spectrum,the tool wear status can be effectively identified.

关 键 词：刀具磨损监测 变分模态分解 灰狼优化 铣削 

分 类 号：TH162[机械工程—机械制造及自动化] TG71[金属学及工艺—刀具与模具]