[1]齐爱玲１,李 琳１,朱亦轩２,等.基于融合特征的双通道CNN滚动轴承故障识别[J].机械与电子,2021,(05):15-19.
　QI Ailing,LI Lin,ZHU Yixuan,et al.Dual Channel CNN Bearing Fault Identification Based on Fusion Feature[J].Machinery & Electronics,2021,(05):15-19.
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基于融合特征的双通道CNN滚动轴承故障识别()
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机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2021年05期
页码:
15-19
栏目:
设计与研究
出版日期:
2021-05-24

文章信息/Info

Title:
Dual Channel CNN Bearing Fault Identification Based on Fusion Feature
文章编号:
１００１-２２５７(２０２１) ０５-００１５-０５
作者:
齐爱玲１; 李 琳１; 朱亦轩２; 张广明３
１．西安科技大学计算机科学与技术学院,陕西 西安 ７１００５４;２．北京化工大学信息科学与技术学院,北京 １０２２００;
３．西安科技大学机械工程学院,陕西 西安 ７１００５４
Author(s):
QI Ailing１; LI Lin１; ZHU Yixuan２; ZHANG Guangming３
(１．College of Computer Science and Technology,Xi’an University of Science and Technology,Xi’an ７１００５４, China;
２．College of Information Science and Technology, BeijingUniversityofChemicalTechnology,Beijing １０２２００, China;
３．College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an ７１００５４,China)
关键词:
故障诊断; 深度学习; 卷积神经网络; 时频图
Keywords:
fault diagnosis; deep learning; CNN; the time frequency image
分类号:
TH１３３.３３
文献标志码:
A
摘要:
针对传统的滚动轴承故障识别方法效果较差,对专家经验依赖较高的问题,提出一种基于融合特征的双通道CNN滚动轴承故障识别方法.该方法首先将原始信号采用小波分解方法生成时频图,再将时频图和原始故障信号融合输入到Lenet-５网络中,进一步对故障特征进行准确提取,在输出层对数据进行融合,使用Softmax分类器对轴承故障进行分类.实验结果表明,该方法对不同种类的滚动轴承故障的识别均能做出准确的判断,识别准确率高.
Abstract:
The traditional fault identification method has poor effect and relies more on expertexperience,so to solve this problem, a two-channel CNN rolling bearing fault identification method based on fusion features was proposed．In this method, the original signal was first generated by Morlet wavelet method, and then the time-frequency diagram and the original fault signal were fused and input into lenet-５ network,and the fault features were further accurately extracted．The data were fused at the output layer,and the faults were classified by Softmaxc lassifier．The experimental results show that this method can make accurate judgment on the identification of different kinds of rolling bearing faults with high accuracy．

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备注/Memo

备注/Memo:
收稿日期:２０２０-０８-１０
基金项目:国家自然科学基金资助项目(６１６７４１２１)?
作者简介:齐爱玲(１９７２－),女,陕西铜川人,博士,副教授,研究方向为人工智能、数据挖掘和图像处理等;李 琳(１９９６－),女,山东聊城人,硕士,研究方向为人工智能,通信作者.
更新日期/Last Update: 2021-05-26