数控机床主轴振动信号监测及提取方法优化研究  

Research on monitoring and optimal extraction method of spindle vibration signal of CNC machine tool

作　　者：苏健 汪木兰[1] 朱晓春[1] 丁文政[1] Su Jian;Wang Mulan;Zhu Xiaoehun;Ding Wenzheng(Nanjing Institute of Technology,Jiangsu Key LaboratoxT of Advanced Numerical Control Technology,Jiangsu Nanjing,211167,China)

机构地区：[1]南京工程学院江苏省先进数控技术重点实验室,江苏南京211167

出　　处：《机械设计与制造工程》2018年第11期16-20,共5页Machine Design and Manufacturing Engineering

基　　金：江苏省高校自然科学研究项目(14KJA460003)

摘　　要：为进一步提升数控机床主轴生产率和使用寿命,研究了预测与健康管理系统。以机床系统主轴振动信号为研究对象,着重研究振动信号监测及优化方法,提出利用三次样条插值函数的优化分析算法提取时频域特性。实验结果表明,对比常规FFT算法,此算法幅值误差精度提高了32%以上,保证了机床主轴运行监测数据的精确性。构建全面、结构简单、通用性强、精度高的监测系统是机床健康运行的保障和未来发展的必然趋势。The prognostic and health management system is studied deeply in order to furtherly improve the productivity and service life of CNC machine tool spindle. Taking the vibration signal of machine tool spindle as object,the optimization analysis algorithm based on cubic spline interpolation function is proposed to extract the time-frequency domain characteristics,which focuses on the method of vibration signal monitoring and optimization. Compared with the conventional FFT algorithm,the experimental results show that the data error accuracy of the algorithm is improved by more than 32%,which ensures the accuracy of the machine tool spindle operation monitoring data. Constructing a comprehensive structure,strong versatility,high precision monitoring system is the inevitable trend of machine tool healthy operation and future development.

关 键 词：数控机床 健康管理 主轴振动 信号监测 三次样条插值 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]