基于Wavelet leader和优化的等距映射算法的回转支承自适应特征提取
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赵祥龙,陈捷,洪荣晶,王华,李媛媛
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Adaptive feature extraction method for slewing bearing based on Wavelet leader and optimized isometric mapping method
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Xiang-long ZHAO,Jie CHEN,Rong-jing HONG,Hua WANG,Yuan-yuan LI
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| 表 4 其他方法的识别结果 |
| Tab.4 Recognition results of other methods |
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| 分类器 | 方法 | Rc/% | t /s | | LSSVM | 时域特征 | 85.33 | 377.801 | | 频域特征 | 88.00 | 366.634 | | 时频域特征 | 89.33 | 352.214 | | 时域-频域-时频域混合特征 | 92.00 | 417.547 | | BP神经网络 | HGWO-ISOMAP-Wavelet leader | 88.67 | 30.158 | | 降维前-Wavelet leader | 82.67 | 217.013 | | f1-f2-f3 | 86.00 | 28.765 | | f1-f2-f4 | 88.45 | 29.127 | | f2-f3-f4 | 67.33 | 29.333 | | 时域特征 | 66.00 | 17.497 | | 频域特征 | 66.67 | 21.377 | | 时频域特征 | 68.67 | 20.046 | | 时域-频域-时频域混合特征 | 75.33 | 23.223 |
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