A Novel Shearer Cutting State Recognition Method Based on Improved Variational Mode Decomposition and LSSVM with Acoustic Signals
Joint Authors
Tan, Chao
Wang, Zhongbin
Si, Lei
Liang, Bin
Tong, Kuangwei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-16
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
The recognition of shearer cutting state is the key technology to realize the intelligent control of the shearer, which has become a highly difficult subject concerned by the world.
This paper takes the sound signal as analytic objects and proposes a novel recognition method based on the combination of variational mode decomposition (VMD), principal component analysis method (PCA), and least square support vector machine (LSSVM).
VMD can decompose a signal into various modes by using calculus of variation and effectively avoid the false component and mode mixing problems.
On this basis, an improved gravitational search algorithm (IGSA) is designed by using the position update mechanism of Levy flight strategy to find the optimal parameter combination of VMD.
Then, the feature extraction is achieved by calculating the envelope entropy and kurtosis of the decomposed intrinsic mode functions (IMFs).
To avoid dimensional disasters and reinforce the classification performance, PCA is introduced to choose useful features, and the LSSVM-based classifier is reasonably constructed.
Finally, the experimental results indicate that the proposed method is more feasible and superior in the recognition of shearer cutting states.
American Psychological Association (APA)
Wang, Zhongbin& Liang, Bin& Si, Lei& Tong, Kuangwei& Tan, Chao. 2020. A Novel Shearer Cutting State Recognition Method Based on Improved Variational Mode Decomposition and LSSVM with Acoustic Signals. Shock and Vibration،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1212816
Modern Language Association (MLA)
Wang, Zhongbin…[et al.]. A Novel Shearer Cutting State Recognition Method Based on Improved Variational Mode Decomposition and LSSVM with Acoustic Signals. Shock and Vibration No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1212816
American Medical Association (AMA)
Wang, Zhongbin& Liang, Bin& Si, Lei& Tong, Kuangwei& Tan, Chao. A Novel Shearer Cutting State Recognition Method Based on Improved Variational Mode Decomposition and LSSVM with Acoustic Signals. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1212816
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1212816