Coal-Rock Recognition in Top Coal Caving Using Bimodal Deep Learning and Hilbert-Huang Transform
Joint Authors
Wang, Zengcai
Zhang, Guoxin
Zhao, Lei
Qi, Yazhou
Wang, Jinshan
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This study employs the mechanical vibration and acoustic waves of a hydraulic support tail beam for an accurate and fast coal-rock recognition.
The study proposes a diagnosis method based on bimodal deep learning and Hilbert-Huang transform.
The bimodal deep neural networks (DNN) adopt bimodal learning and transfer learning.
The bimodal learning method attempts to learn joint representation by considering acceleration and sound pressure modalities, which both contribute to coal-rock recognition.
The transfer learning method solves the problem regarding DNN, in which a large number of labeled training samples are necessary to optimize the parameters while the labeled training sample is limited.
A suitable installation location for sensors is determined in recognizing coal-rock.
The extraction features of acceleration and sound pressure signals are combined and effective combination features are selected.
Bimodal DNN consists of two deep belief networks (DBN), each DBN model is trained with related samples, and the parameters of the pretrained DBNs are transferred to the final recognition model.
Then the parameters of the proposed model are continuously optimized by pretraining and fine-tuning.
Finally, the comparison of experimental results demonstrates the superiority of the proposed method in terms of recognition accuracy.
American Psychological Association (APA)
Zhang, Guoxin& Wang, Zengcai& Zhao, Lei& Qi, Yazhou& Wang, Jinshan. 2017. Coal-Rock Recognition in Top Coal Caving Using Bimodal Deep Learning and Hilbert-Huang Transform. Shock and Vibration،Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1204337
Modern Language Association (MLA)
Zhang, Guoxin…[et al.]. Coal-Rock Recognition in Top Coal Caving Using Bimodal Deep Learning and Hilbert-Huang Transform. Shock and Vibration No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1204337
American Medical Association (AMA)
Zhang, Guoxin& Wang, Zengcai& Zhao, Lei& Qi, Yazhou& Wang, Jinshan. Coal-Rock Recognition in Top Coal Caving Using Bimodal Deep Learning and Hilbert-Huang Transform. Shock and Vibration. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1204337
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204337