An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting
Shore bridge and other port cranes have some working condition characters including high speed, heavy load, and large impact. In order to solve the degradation feature extraction issue of hoisting mechanism gearbox, an online degradation feature extraction technique based on morphological fractal di...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/9216809 |
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| _version_ | 1832557088844283904 |
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| author | Dejian Sun Bing Wang Xiong Hu Wei Wang |
| author_facet | Dejian Sun Bing Wang Xiong Hu Wei Wang |
| author_sort | Dejian Sun |
| collection | DOAJ |
| description | Shore bridge and other port cranes have some working condition characters including high speed, heavy load, and large impact. In order to solve the degradation feature extraction issue of hoisting mechanism gearbox, an online degradation feature extraction technique based on morphological fractal dimension and sliding window Weibull fitting is proposed. Firstly, taking the vibration energy spectrum collecting from the gearbox as the online data source, the fractal dimension of the vibration energy spectrum during an analysis period is calculated and a fractal evolution curve is obtained. A three-parameter Weibull fitting on the fractal curve within a sliding window after setting the window’s width and step size is performed. The scale parameter of the Weibull fitting model is introduced as the performance degradation feature. The effectiveness of the technique is verified by the full-life vibration data of hoisting gearbox from Shanghai Port Group. The results show that the morphological fractal dimension is able to describe the fractal complexity of the vibration energy spectrum. The scale parameter of Weibull distribution is able to reflect the performance degradation trend of fractal curve smoothly, which lays a theoretical foundation for further solving the problem of online health assessment. |
| format | Article |
| id | doaj-art-405519c742314dd7b75fe2f1b5cb25e8 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-405519c742314dd7b75fe2f1b5cb25e82025-02-03T05:43:40ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/92168099216809An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull FittingDejian Sun0Bing Wang1Xiong Hu2Wei Wang3Shanghai Maritime University, Shanghai 201306, ChinaShanghai Maritime University, Shanghai 201306, ChinaShanghai Maritime University, Shanghai 201306, ChinaShanghai Maritime University, Shanghai 201306, ChinaShore bridge and other port cranes have some working condition characters including high speed, heavy load, and large impact. In order to solve the degradation feature extraction issue of hoisting mechanism gearbox, an online degradation feature extraction technique based on morphological fractal dimension and sliding window Weibull fitting is proposed. Firstly, taking the vibration energy spectrum collecting from the gearbox as the online data source, the fractal dimension of the vibration energy spectrum during an analysis period is calculated and a fractal evolution curve is obtained. A three-parameter Weibull fitting on the fractal curve within a sliding window after setting the window’s width and step size is performed. The scale parameter of the Weibull fitting model is introduced as the performance degradation feature. The effectiveness of the technique is verified by the full-life vibration data of hoisting gearbox from Shanghai Port Group. The results show that the morphological fractal dimension is able to describe the fractal complexity of the vibration energy spectrum. The scale parameter of Weibull distribution is able to reflect the performance degradation trend of fractal curve smoothly, which lays a theoretical foundation for further solving the problem of online health assessment.http://dx.doi.org/10.1155/2019/9216809 |
| spellingShingle | Dejian Sun Bing Wang Xiong Hu Wei Wang An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting Shock and Vibration |
| title | An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting |
| title_full | An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting |
| title_fullStr | An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting |
| title_full_unstemmed | An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting |
| title_short | An Online Degradation Feature Extraction Technique for Shore Bridge Gearbox Based on Morphological Fractal Dimension and Sliding Window Weibull Fitting |
| title_sort | online degradation feature extraction technique for shore bridge gearbox based on morphological fractal dimension and sliding window weibull fitting |
| url | http://dx.doi.org/10.1155/2019/9216809 |
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