A review on deep learning in planetary gearbox health state recognition: methods, applications, and dataset publication
Beijing University of Technology · Beijing Jiaotong University
Abstract
Abstract Planetary gearboxes have various merits in mechanical transmission, but their complex structure and intricate operation modes bring large challenges in terms of fault diagnosis. Deep learning has attracted increasing attention in intelligent fault diagnosis and has been successfully adopted for planetary gearbox fault diagnosis, avoiding the difficulty in manually analyzing complex fault features with signal processing methods. This paper presents a comprehensive review of deep learning-based planetary gearbox health state recognition. First, the challenges caused by the complex vibration characteristics of planetary gearboxes in fault diagnosis are analyzed. Second, according to the popularity of…
Citation impact
- FWCI
- 37.91
- Percentile
- 100%
- References
- 172
Authors
3Topics & keywords
- Deep learning
- Computer science
- Artificial intelligence
- Fault (geology)
- Machine learning
- Artificial neural network
- Convolutional neural network
- Autoencoder