归一化变尺度随机共振的刀具状态监测

姜增辉; 谢峰; 王海宁

doi:10.13433/j.cnki.1003-8728.20190266

归一化变尺度随机共振的刀具状态监测

doi: 10.13433/j.cnki.1003-8728.20190266

姜增辉^1,,
谢峰^1, ,,
王海宁²

1.
安徽大学电气工程与自动化学院，合肥　230601
2.
中国电子科技集团公司第四十三研究所，合肥　230088

基金项目: 国家自然科学基金项目（51975003）与安徽省学术和技术带头人科研项目（2017D135）资助

详细信息

作者简介:
姜增辉（1996−），硕士研究生，研究方向为机械故障诊断，检测技术与自动化装置，941078044@qq.com

通讯作者:
谢峰，教授，硕士生导师，jeexf199@163.com

中图分类号: TG115.5⁺8;TH117.1
计量
- 文章访问数: 166
- HTML全文浏览量: 38
- PDF下载量: 15
- 被引次数: 0
出版历程
- 收稿日期: 2019-06-06
- 网络出版日期: 2020-11-07
- 刊出日期: 2020-10-05

Condition Monitoring of Tools with Normalized Variable-scale Stochastic Resonance

1.
School of Electrical Engineering and Automation, Anhui University, Hefei 230601, China
2.
The 43rd Research Institute of China Electronics Technology Group Corporation, Hefei 230088, China

摘要

摘要: 针对传统时频域检测方法不能有效检测出刀具急剧磨损初期微弱特征信息的问题，提出一种归一化变尺度随机共振监测刀具状态的新方法。该方法通过换元将经典双稳态随机共振系统模型变化为归一化形式，变化之后的随机共振（Stochastic resonance，SR）方法把混合信号进行放大，使得SR方法适用于大参数系统，通过仿真验证了该方法的可行性。并使用该方法对刀具进行实时监测，成功检测出了以主轴基频和立铣刀转频为特征的刀具磨损信息，表明了归一化变尺度随机共振在刀具状态监测中的实用性和有效性。
- 刀具磨损 /
- 尺度变换 /
- 随机共振 /
- 状态监测
Abstract: Aiming at the problem that the traditional time-frequency domain detection method can not effectively detect the weak fault feature information at the initial stage of sharp tool wear, a new method of tool condition monitoring with normalized variable-scale stochastic resonance is proposed. This method changes the model of the classical bistable stochastic resonance system into a normalized form by substitution. After the change, the stochastic resonance (SR) method amplifies the mixed signals, making the SR method suitable for large-parameter system. The feasibility of this condition monitoring method is verified by simulation. The method is used to monitor the tool in real time, tool wear information characterized by spindle fundamental frequency and end mill rotation frequency was successfully detected, which shows the practicability and effectiveness of the normalized variable-scale stochastic resonance in the tool condition monitoring.
- tool wear /
- scale transformation /
- stochastic resonance (SR) /
- condition monitoring

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图 1 输入信号（大参数）时域图及频谱图

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图 2 输出信号（大参数）时域图及频谱图

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图 3 实验装置图

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图 4 振动信号分析流程图

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图 5 输入加噪信号放大120倍时域图

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图 6 主轴基频特征频率

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图 7 输入加噪信号放大240倍时域图

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图 8 立铣刀转频特征频率

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