刀具磨损状态监测技术研究进展
2019-05-17
作者：郭景超，李安海
单位：山东大学机械工程学院；山东大学高效洁净机械制造教育部重点实验室；机械工程国家级实验教学示范中心（山东大学）
摘要：随着工业4.0的到来，对制造业智能化的要求越来越高，刀具作为机械加工中的重要组成部分，其智能化监测也变得愈加重要。本文从监测信号、信号处理和分类模型三个方面阐述了刀具磨损状态监测技术的最新研究进展。比较了不同监测信号的优点与不足，深入分析了信号处理及分类模型的原理。对刀具磨损状态监测的未来发展进行了展望，提出了引入深度学习方法，期望能够提高智能化监测的准确性和鲁棒性。
关键词：刀具磨损状态监测；智能监测；信号处理；特征提取；模式识别
中图分类号：TG506；TH161文献标志码：ADOI：10.3969/j.issn.1000-7008.2019.05.001
Advances in Monitoring Technology of Tool Wear Condition
Guo Jingchao，Li Anhai
Abstract:With the development of Industry 4.0，the intelligent requirements of manufacturing industry are getting higher and higher.As an important part of mechanical processing，cutting tool intelligent monitoring are becoming more and more important.In this paper，the research advances in tool wear monitoring technology is described from three aspects:signal acquisition，feature extraction and classification.The advantages and disadvantages of different monitoring signals are compared，and the principles of feature extraction and classification models are deeply analyzed.The future development of tool wear condition monitoring is prospected，and deep learning method is proposed，which is expected to improve the accuracy and robustness of intelligent monitoring.
Keywords:tool wear condition monitoring；intelligent monitoring；signal processing；feature extraction；pattern recognition