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: Dejian Sun, Bing Wang, Xiong Hu, Wei Wang
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2019/9216809
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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
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institution Kabale University
issn 1070-9622
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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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