|本期目录/Table of Contents|

[1]李贵红,赵丽丽,杜 昕,等.基于EMD和香农熵的刀具磨损故障诊断系统开发[J].工业仪表与自动化装置,2019,(02):114-117.[doi:1000-0682(2019)02-0000-00]
　LI Guihong,ZHAO Lili,DU Xin,et al.Development of tools wearing fault diagnosis system based on EMD and Shannon[J].Industrial Instrumentation & Automation,2019,(02):114-117.[doi:1000-0682(2019)02-0000-00]
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基于EMD和香农熵的刀具磨损故障诊断系统开发

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2019年02期
页码:
114-117
栏目:
出版日期:
2019-04-15

文章信息/Info

Title:
Development of tools wearing fault diagnosis system based on EMD and Shannon
作者:
李贵红1; 赵丽丽2; 杜 昕1; 于俊虎1
1.兰州职业技术学院，兰州 730070；
2.甘肃能源化工职业学院，兰州 730207
Author(s):
LI Guihong1; ZHAO Lili2; DU Xin1; YU Junhu1
1. Lanzhou Vocational Technical College, Lanzhou 730070,China;2.Gansu Vocational College of Energy and Chemical Industy, Lanzhou 730207,China)
关键词:
刀具磨损; 经验模态分解; 香农熵; 支持向量机
Keywords:
tool wearing; empirical mode decomposition(EMD); Shannon; support vector machine
分类号:
TH117;TP277
DOI:
1000-0682(2019)02-0000-00
文献标志码:
A
摘要:
针对机床刀具磨损故障诊断，开发了基于经验模态分解和香农熵进行信号处理的刀具故障诊断系统。在信号处理阶段，对机床加工过程中刀具的振动信号进行经验模态分解，得到若干固有模态函数（IMF），并基于香农熵从分解得到的IMF分量中提取有效分量，去除虚假分量，最后将有效的IMF分量的能量作为特征向量输入向量机(SVM)分类器来识别刀具的磨损状态。经实验验证，该系统能对刀具磨损状态进行准确快速的判断。
Abstract:
For tool wear fault diagnosis，a CNC tool wearing fault diagnosis syetem was developed based on empirical mode decomposition(EMD) and Shannon for signal processing，In signal processing stage，empirical mode decomposition was done to vibration signal in the machining process，and then a number of intrinsic mode functions(IMFs) were gotten，and then extracting effective IMFs and excluding false functions according to Shannon，At last，the energy of effective IMF functions are taken as inputs of support vector machine(SVM) classifier to identify the state of cutter. Proved by test，this system could judge the tool wear state quickly and accurately.

参考文献/References:

[1] 孙巍伟,黄民,高延.基于EMD-HMM的机床刀具磨损故障诊断[J].机床与液压,2017(7):178-181.

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[7] 杨雪特.熵的引入、深化与泛化—从克劳修斯熵到香农熵[J].内江师范学院学报,1991(4):62-65.
[8] 王姣,刘海燕.基于支持向量机和遗传算法的刀具故障诊断[J].组合机床与自动化加工术,2013(1):74-76.
[9] 常勇,何婷.一种EEMD阈值降噪方法在故障诊断中的应用[J].工业仪表与自动化装置,2018(04):3-7.
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备注/Memo

备注/Memo:
收稿日期：2018-11-05
基金项目：甘肃省高等学校科研项目（2018A-252）；兰州市安宁区科技计划项目（2017-5）；甘肃省职业教育改革项目
作者简介：李贵红(1979),男,甘肃庆阳人,工学学士,副教授,主要从事机械设备故障诊断、维修及无损检测等方面的教学和科研工作。
更新日期/Last Update: 2019-04-15