在可变的工具工件系统中适应削聊天检测:一种使用信号重建和能量比率的新方法
Zehui Zheng1, Shuxian Zheng1, Xiubing Jing1
1Key Laboratory of Equipment Design and Manufacturing Technology, School of Mechanical Engineering, Tianjin University, Tianjin 300072, China.
ISA transactions
|March 4, 2026
概括
本研究介绍了一种用于研磨的智能聊天识别方法,使用频率分析和信号重建来实时检测聊天. 信号重建后的聊天与稳定能量比率 (CSERSR) 指标有效地识别了各种系统中的聊天.
科学领域:
- 制造业 工程 制造工程
- 机械振动 - 机械振动
- 信号处理 信号处理
背景情况:
- 削过程中的声会降低表面质量和工具寿命.
- 可持续制造需要及时检测聊天.
- 现有的方法在各种工具工件系统中缺乏适应性.
研究的目的:
- 为研磨开发一个智能聊天识别方法.
- 为了实现在不同工具工件系统中实时检测聊天.
- 引入一种用于聊天评估的新能源指标.
主要方法:
- 使用频率分布分析自动识别聊天和稳定频率.
- 使用波段包分解 (WPD) 进行自适应信号重建,用于信号组件提取.
- 信号重建后的聊天与稳定的能量比率 (CSERSR) 指标的发展.
主要成果:
- 拟议的方法在模拟和实验中准确地识别不同程度的聊天.
- CSERSR在实时中有效量化聊天严重程度.
- 该方法在不同的工具工件系统中证明了可靠性和适应性.
结论:
- 开发的智能聊天识别方法对可持续的削有效.
- 该CSERSR指标提供了一个可靠的实时聊天检测措施.
- 这种方法比现有的聊天分析技术有了显著的进步.
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