基于判别稀疏编码的轴承故障诊断方法
发布时间：2018-12-10 23:05
【摘要】：为解决轴承故障诊断中故障信号特征难以提取、不同故障程度间信号特征相近难以区分的问题,提出了基于判别稀疏编码的轴承故障诊断方法:在稀疏编码框架下,引入Fisher判别准则,增强不同类别故障字典的判别性,并基于重构误差,在频域上对故障信号进行处理。实验表明:与其他方法相比,该方案有效提高了轴承故障诊断的准确率,并具有较好的稳定性。
[Abstract]:In order to solve the problem that the fault signal feature is difficult to be extracted in bearing fault diagnosis and the signal features are similar to each other among different fault degrees, a bearing fault diagnosis method based on discriminant sparse coding is proposed. The Fisher criterion is introduced to enhance the discriminability of different fault dictionaries, and the fault signals are processed in frequency domain based on the reconstruction error. The experimental results show that compared with other methods, this scheme can effectively improve the accuracy of bearing fault diagnosis and has better stability.
【作者单位】： 解放军理工大学;苏州市公安局相城分局;
【分类号】：TH133.3
本文编号：2371377
[Abstract]:In order to solve the problem that the fault signal feature is difficult to be extracted in bearing fault diagnosis and the signal features are similar to each other among different fault degrees, a bearing fault diagnosis method based on discriminant sparse coding is proposed. The Fisher criterion is introduced to enhance the discriminability of different fault dictionaries, and the fault signals are processed in frequency domain based on the reconstruction error. The experimental results show that compared with other methods, this scheme can effectively improve the accuracy of bearing fault diagnosis and has better stability.
【作者单位】： 解放军理工大学;苏州市公安局相城分局;
【分类号】：TH133.3
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1 唐海峰;基于信号稀疏表征的故障诊断方法研究[D];上海交通大学;2014年
，本文编号：2371377
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