| 含稀疏度约束的非负张量分解算法及其在故障诊断中的应用(英文) |
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| 引用本文： | 彭森,许飞云,贾民平,胡建中.含稀疏度约束的非负张量分解算法及其在故障诊断中的应用(英文)[J].东南大学学报,2009,25(3):346-350. |
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| 作者姓名： | 彭森 许飞云 贾民平 胡建中 |
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| 作者单位： | 东南大学机械工程学院,南京,211189 |
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| 基金项目： | The National Natural Science Foundation of China，the Natural Science Foundation of Jiangsu Province，the National High Technology Research and Development Program of China (863 Program) |
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| 摘 要： | 针对双谱分析在应用于机械设备故障诊断过程中面临的问题,提出了含有稀疏度约束的非负张量分解算法及基于此的二次故障特征提取方法.首先,改进已有的非负张量分解算法,加入稀疏度控制策略;其次,将机械振动信号的双谱图像堆叠为一个三阶张量;然后利用改进后的分解算法对该张量进行二次故障特征提取,得到代表局部特征的"基图像";最后,通过计算得出基图像在构成原双谱图像中所占的权重,并将得到的权重向量用于故障分类.将该方法应用于齿轮箱故障诊断的结果表明,从齿轮箱振动信号的双谱中提取出来的二次特征不仅能够反映出系统中存在的一些非线性特征,而且二次特征与故障特征频率之间有直观的对应关系,从而为解释齿轮箱故障与对应双谱之间的关系提供了很大的方便.
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| 关 键 词： | 非负张量分解 稀疏度 特征提取 双谱 齿轮箱 |
Sparseness-controlled non-negative tensor factorization and its application in machinery fault diagnosis |
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| Peng Sen Xu Feiyun Jia Minping Hu Jianzhong.Sparseness-controlled non-negative tensor factorization and its application in machinery fault diagnosis[J].Journal of Southeast University(English Edition),2009,25(3):346-350. |
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| Authors: | Peng Sen Xu Feiyun Jia Minping Hu Jianzhong |
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| Institution: | Peng Sen Xu Feiyun Jia Minping Hu Jianzhong(School of Mechanical Engineering,Southeast University,Nanjing 211189,China) |
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| Abstract: | Aiming at the problems of bispectral analysis when applied to machinery fault diagnosis,a machinery fault feature extraction method based on sparseness-controlled non-negative tensor factorization(SNTF) is proposed.First,a non-negative tensor factorization(NTF) algorithm is improved by imposing sparseness constraints on it.Secondly,the bispectral images of mechanical signals are obtained and stacked to form a third-order tensor.Thirdly,the improved algorithm is used to extract features,which are represented... |
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| Keywords: | non-negative tensor factorization sparseness feature extraction bispectrum gearbox |
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