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Analysis of cutting force signals by wavelet packet transform for surface roughness monitoring in CNC turning

机译:小波包变换分析切削力信号,实现数控车削表面粗糙度监测

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摘要

On-line monitoring of surface finish in machining processes has proven to be a substantial advancement over traditional post-process quality control techniques by reducing inspection times and costs and by avoiding the manufacture of defective products. This study applied techniques for processing cutting force signals based on the wavelet packet transform (WPT) method for the monitoring of surface finish in computer numerical control (CNC) turning operations. The behaviour of 40 mother wavelets was analysed using three techniques: global packet analysis (G-WPT), and the application of two packet reduction criteria: maximum energy (E-WPT) and maximum entropy (SE-WPT). The optimum signal decomposition level (L_j) was determined to eliminate noise and to obtain information correlated to surface finish. The results obtained with the G-WPT method provided an in-depth analysis of cutting force signals, and frequency ranges and signal characteristics were correlated to surface finish with excellent results in the accuracy and reliability of the predictive models. The radial and tangential cutting force components at low frequency provided most of the information for the monitoring of surface finish. The E-WPT and SE-WPT packet reduction criteria substantially reduced signal processing time, but at the expense of discarding packets with relevant information, which impoverished the results. The G-WPT method was observed to be an ideal procedure for processing cutting force signals applied to the real-time monitoring of surface finish, and was estimated to be highly accurate and reliable at a low analytical-computational cost.
机译:与传统的后处理质量控制技术相比,通过减少检查时间和成本以及避免生产有缺陷的产品,在线监测加工表面的光洁度已证明是一项重大进步。本研究应用了基于小波包变换(WPT)方法的切削力信号处理技术,以监控计算机数控(CNC)车削操作中的表面光洁度。使用三种技术分析了40个子小波的行为:全局数据包分析(G-WPT),以及两个数据包缩减标准的应用:最大能量(E-WPT)和最大熵(SE-WPT)。确定最佳信号分解水平(L_j)以消除噪声并获得与表面光洁度相关的信息。用G-WPT方法获得的结果提供了对切削力信号的深入分析,并且频率范​​围和信号特性与表面光洁度相关,在预测模型的准确性和可靠性方面具有优异的结果。低频时的径向和切向切削力分量为监控表面质量提供了大多数信息。 E-WPT和SE-WPT数据包减少标准显着减少了信号处理时间,但以丢弃带有相关信息的数据包为代价,这使结果变糟。 G-WPT方法被认为是处理切削力信号的理想方法,该信号被应用于表面光洁度的实时监控,并被认为以较低的分析计算成本实现了高精度和可靠性。

著录项

  • 来源
    《Mechanical systems and signal processing》 |2018年第1期|634-651|共18页
  • 作者单位

    Higher Technical School of Industrial Engineering, Energy Research and Industrial Applications Institute (NEI), Department Applied Mechanics & Engineering of Projects, University of Castilla-La Mancha, Avda. Camilojose Cela, s, 13071 Ciudad Real, Spain;

    Higher Technical School of Industrial Engineering, Energy Research and Industrial Applications Institute (NEI), Department Applied Mechanics & Engineering of Projects, University of Castilla-La Mancha, Avda. Camilojose Cela, s, 13071 Ciudad Real, Spain;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Wavelet packet transform; Surface finish; Roughness; Cutting forces; CNC turning operations;

    机译:小波包变换;表面光洁度粗糙度切削力;CNC车削操作;

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