光学 精密工程, 2018, 26 (12): 3087, 网络出版: 2019-01-27   

基于稀疏编码空间金字塔匹配和GA-SVM的列车故障自动识别

Automatic fault recognition algorithm for key parts of train based on sparse coding based spatial pyramid matching and GA-SVM
作者单位
1 湖北工业大学 机械工程学院, 湖北 武汉 430068
2 南京大学 计算机科学与技术系, 江苏 南京 210023
引用该论文

孙国栋, 周振, 王俊豪, 张杨, 赵大兴. 基于稀疏编码空间金字塔匹配和GA-SVM的列车故障自动识别[J]. 光学 精密工程, 2018, 26(12): 3087.

SUN Guo-dong, ZHOU Zhen, WANG Jun-hao, ZHANG Yang, ZHAO Da-xing. Automatic fault recognition algorithm for key parts of train based on sparse coding based spatial pyramid matching and GA-SVM[J]. Optics and Precision Engineering, 2018, 26(12): 3087.

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孙国栋, 周振, 王俊豪, 张杨, 赵大兴. 基于稀疏编码空间金字塔匹配和GA-SVM的列车故障自动识别[J]. 光学 精密工程, 2018, 26(12): 3087. SUN Guo-dong, ZHOU Zhen, WANG Jun-hao, ZHANG Yang, ZHAO Da-xing. Automatic fault recognition algorithm for key parts of train based on sparse coding based spatial pyramid matching and GA-SVM[J]. Optics and Precision Engineering, 2018, 26(12): 3087.

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