Intelligent Diagnosis Using Continuous Wavelet Transform and Gauss Convolutional Deep Belief Network
Civil Aviation University of China · Southwest Jiaotong University · +3 more institutions
Abstract
Bearing fault diagnosis is of significance to ensure the safe and reliable operation of a motor. Deep learning provides a powerful ability to extract the features of raw data automatically. A convolutional deep belief network (CDBN) is an effective deep learning method. In this article, a novel vibration amplitude spectrum imaging feature extraction method using continuous wavelet transform and image conversion is proposed, which can extract the image features with two-dimensional and eliminate the effect of handcrafted features under low signal-to-noise ratio conditions, different operating conditions, and data segmentation. Then, a novel CDBN with Gaussian distribution is constructed to learn the…
Citation impact
- FWCI
- 32.87
- Percentile
- 100%
- References
- 29
Authors
7- HZHuimin ZhaoCorresponding
Civil Aviation University of China, Southwest Jiaotong University
- JLJie Liu
China Household Electrical Appliances Research Institute
- HCHuayue Chen
China West Normal University
- JCJie Chen
Wenzhou Institute of Technology Testing & Calibration
- YLYang Li
China Household Electrical Appliances Research Institute
Topics & keywords
- Artificial intelligence
- Computer science
- Feature extraction
- Deep learning
- Pattern recognition (psychology)
- Deep belief network
- Bearing (navigation)
- Wavelet transform