1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling
The conventional pooling method for processing one-dimensional vibration signals may lead to certain issues, such as weakening and loss of feature information. The present study proposes the cubic spline interpolation pooling method. The method is appropriate for processing one-dimensional signals....
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/1949863 |
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| _version_ | 1832567360705265664 |
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| author | Shuzhan Huang Jian Tang Juying Dai Yangyang Wang Junjie Dong |
| author_facet | Shuzhan Huang Jian Tang Juying Dai Yangyang Wang Junjie Dong |
| author_sort | Shuzhan Huang |
| collection | DOAJ |
| description | The conventional pooling method for processing one-dimensional vibration signals may lead to certain issues, such as weakening and loss of feature information. The present study proposes the cubic spline interpolation pooling method. The method is appropriate for processing one-dimensional signals. The proposed method can transform the pooling problem into a linear fitting problem, use the cubic spline interpolation method with outstanding fitting effects, and calculate the fitting function of the input signals. Moreover, the values of the interpolation points are sequentially taken as the feature value output. Furthermore, the network using the conventional pooling method and the pooling network model proposed in the present study are compared, tested, and analyzed on the constructed simulation signals and the measured bearing dataset. It is concluded that the proposed pooling method can reduce the data dimension while improving the network feature extraction capability and is more appropriate for pooling one-dimensional signals. |
| format | Article |
| id | doaj-art-2e2df5ecfef04a44b80ad497874a196e |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-2e2df5ecfef04a44b80ad497874a196e2025-02-03T01:01:36ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/194986319498631DCNN Fault Diagnosis Based on Cubic Spline Interpolation PoolingShuzhan Huang0Jian Tang1Juying Dai2Yangyang Wang3Junjie Dong4School of Graduate, Army Engineering University of PLA, Nanjing 210000, ChinaSchool of Field Engineering, Army Engineering University of PLA, Nanjing 210000, ChinaSchool of Field Engineering, Army Engineering University of PLA, Nanjing 210000, ChinaSchool of Graduate, Army Engineering University of PLA, Nanjing 210000, ChinaSchool of Graduate, Army Engineering University of PLA, Nanjing 210000, ChinaThe conventional pooling method for processing one-dimensional vibration signals may lead to certain issues, such as weakening and loss of feature information. The present study proposes the cubic spline interpolation pooling method. The method is appropriate for processing one-dimensional signals. The proposed method can transform the pooling problem into a linear fitting problem, use the cubic spline interpolation method with outstanding fitting effects, and calculate the fitting function of the input signals. Moreover, the values of the interpolation points are sequentially taken as the feature value output. Furthermore, the network using the conventional pooling method and the pooling network model proposed in the present study are compared, tested, and analyzed on the constructed simulation signals and the measured bearing dataset. It is concluded that the proposed pooling method can reduce the data dimension while improving the network feature extraction capability and is more appropriate for pooling one-dimensional signals.http://dx.doi.org/10.1155/2020/1949863 |
| spellingShingle | Shuzhan Huang Jian Tang Juying Dai Yangyang Wang Junjie Dong 1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling Shock and Vibration |
| title | 1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling |
| title_full | 1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling |
| title_fullStr | 1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling |
| title_full_unstemmed | 1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling |
| title_short | 1DCNN Fault Diagnosis Based on Cubic Spline Interpolation Pooling |
| title_sort | 1dcnn fault diagnosis based on cubic spline interpolation pooling |
| url | http://dx.doi.org/10.1155/2020/1949863 |
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