دورية أكاديمية
Detection of Pitting in Gears Using a Deep Sparse Autoencoder
| العنوان: | Detection of Pitting in Gears Using a Deep Sparse Autoencoder |
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| المؤلفون: | Yongzhi Qu, Miao He, Jason Deutsch, David He |
| المصدر: | Applied Sciences, Vol 7, Iss 5, p 515 (2017) |
| بيانات النشر: | MDPI AG, 2017. |
| سنة النشر: | 2017 |
| المجموعة: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| مصطلحات موضوعية: | gear, pitting detection, deep sparse autoencoder, vibration, deep learning, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| الوصف: | In this paper; a new method for gear pitting fault detection is presented. The presented method is developed based on a deep sparse autoencoder. The method integrates dictionary learning in sparse coding into a stacked autoencoder network. Sparse coding with dictionary learning is viewed as an adaptive feature extraction method for machinery fault diagnosis. An autoencoder is an unsupervised machine learning technique. A stacked autoencoder network with multiple hidden layers is considered to be a deep learning network. The presented method uses a stacked autoencoder network to perform the dictionary learning in sparse coding and extract features from raw vibration data automatically. These features are then used to perform gear pitting fault detection. The presented method is validated with vibration data collected from gear tests with pitting faults in a gearbox test rig and compared with an existing deep learning-based approach. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2076-3417 |
| Relation: | http://www.mdpi.com/2076-3417/7/5/515; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app7050515 |
| URL الوصول: | https://doaj.org/article/222ebef846a449fa89b2cdf3b91c0b87 |
| رقم الأكسشن: | edsdoj.222ebef846a449fa89b2cdf3b91c0b87 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20763417 |
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| DOI: | 10.3390/app7050515 |