声发射
磨料
材料科学
分层(地质)
刀具磨损
涂层
波形
信号(编程语言)
过程(计算)
机械加工
GSM演进的增强数据速率
信号处理
声学
机械工程
复合材料
计算机科学
工程类
冶金
电子工程
人工智能
电气工程
古生物学
物理
数字信号处理
生物
俯冲
构造学
程序设计语言
操作系统
电压
作者
Eckart Uhlmann,Tobias Holznagel
标识
DOI:10.1016/j.cirpj.2022.02.024
摘要
Milling of fibre-reinforced plastics is a challenging task. The highly abrasive fibres lead to high tool wear and coating failures, which cause increasing process forces and temperatures. Machining with a worn tool, in turn, can result in unwanted workpiece damages such as delamination or fibre protrusion. Reliable monitoring of the process must therefore be able to detect damages to the milling tool and the workpiece alike. The presented process monitoring approach measures the acoustic emission generated by the milling tool cutting edge entering the workpiece with a sensor attached to the tool holder. Specific acoustic emission frequency spectra and waveforms are emitted in the cutting zone for different tool wear states. Coating failures as well as other acoustic emission events due to workpiece damages can be robustly detected and distinguished by feature extraction and signal processing as well. The developed setup, the monitoring parameterisation techniques and signal processing algorithms as well as experimental and monitoring results are presented and discussed in this paper.
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