Detection of Pitting in Gears Using a Deep Sparse Autoencoder
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 adapt...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-05-01
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| Series: | Applied Sciences |
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| Online Access: | http://www.mdpi.com/2076-3417/7/5/515 |
| _version_ | 1818838424978718720 |
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| author | Yongzhi Qu Miao He Jason Deutsch David He |
| author_facet | Yongzhi Qu Miao He Jason Deutsch David He |
| author_sort | Yongzhi Qu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T03:38:11Z |
| format | Article |
| id | doaj.art-222ebef846a449fa89b2cdf3b91c0b87 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-19T03:38:11Z |
| publishDate | 2017-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-222ebef846a449fa89b2cdf3b91c0b872022-12-21T20:37:19ZengMDPI AGApplied Sciences2076-34172017-05-017551510.3390/app7050515app7050515Detection of Pitting in Gears Using a Deep Sparse AutoencoderYongzhi Qu0Miao He1Jason Deutsch2David He3School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, ChinaDepartment of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USADepartment of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USADepartment of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USAIn 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.http://www.mdpi.com/2076-3417/7/5/515gearpitting detectiondeep sparse autoencodervibrationdeep learning |
| spellingShingle | Yongzhi Qu Miao He Jason Deutsch David He Detection of Pitting in Gears Using a Deep Sparse Autoencoder Applied Sciences gear pitting detection deep sparse autoencoder vibration deep learning |
| title | Detection of Pitting in Gears Using a Deep Sparse Autoencoder |
| title_full | Detection of Pitting in Gears Using a Deep Sparse Autoencoder |
| title_fullStr | Detection of Pitting in Gears Using a Deep Sparse Autoencoder |
| title_full_unstemmed | Detection of Pitting in Gears Using a Deep Sparse Autoencoder |
| title_short | Detection of Pitting in Gears Using a Deep Sparse Autoencoder |
| title_sort | detection of pitting in gears using a deep sparse autoencoder |
| topic | gear pitting detection deep sparse autoencoder vibration deep learning |
| url | http://www.mdpi.com/2076-3417/7/5/515 |
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