陈怀海
    博士生导师
  • 招生学科专业:
    力学 -- 【招收博士、硕士研究生】 -- 航空学院
    机械 -- 【招收博士、硕士研究生】 -- 航空学院
  • 学位:工学博士学位
  • 职称:教授
  • 所在单位:航空学院
博士生导师
教师英文名称:CHEN Huaihai
电子邮箱:CHHNUAA@nuaa.edu.cn
所在单位:航空学院
学历:大连理工大学
办公地点:A18-613
性别:
联系方式:CHHNUAA@nuaa.edu.cn
毕业院校:西安交通大学

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标题:
A novel sparse filtering approach based on time-frequency feature extraction and softmax regression for intelligent fault diagnosis under different speeds
点击次数:
所属单位:
航空学院
发表刊物:
JOURNAL OF CENTRAL SOUTH UNIVERSITY
关键字:
intelligent fault diagnosis short time Fourier transform sparse filtering softmax regression
摘要:
Modern agricultural mechanization has put forward higher requirements for the intelligent defect diagnosis. However, the fault features are usually learned and classified under all speeds without considering the effects of speed fluctuation. To overcome this deficiency, a novel intelligent defect detection framework based on time-frequency transformation is presented in this work. In the framework, the samples under one speed are employed for training sparse filtering model, and the remaining samples under different speeds are adopted for testing the effectiveness. Our proposed approach contains two stages: 1) the time-frequency domain signals are acquired from the mechanical raw vibration data by the short time Fourier transform algorithm, and then the defect features are extracted from time-frequency domain signals by sparse filtering algorithm; 2) different defect types are classified by the softmax regression using the defect features. The proposed approach can be employed to mine available fault characteristics adaptively and is an effective intelligent method for fault detection of agricultural equipment. The fault detection performances confirm that our approach not only owns strong ability for fault classification under different speeds, but also obtains higher identification accuracy than the other methods.
ISSN号:
2095-2899
是否译文:
发表时间:
2019-06-01
第一作者:
陈怀海
通讯作者:
,陈怀海,陈怀海,陈怀海,陈怀海,陈怀海,陈怀海,陈怀海,陈怀海,陈怀海,陈怀海
其他作者:
Zhang Zhong-wei,李舜酩,Wang Jin-rui
发表时间:
2019-06-01
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