Research on coal-rock recognition based on sound signal analysis
The recognition of the cutting state of shearer is the key technology to realize variable speed cutting and mining automation. It is of great significance for improving shearer reliability, ensuring personal safety and improving coal quality. This paper proposed a coal-rock recognition method based...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201823204075 |
| _version_ | 1831588923023818752 |
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| author | Chen Xihui Yang Zenan Cheng Gang |
| author_facet | Chen Xihui Yang Zenan Cheng Gang |
| author_sort | Chen Xihui |
| collection | DOAJ |
| description | The recognition of the cutting state of shearer is the key technology to realize variable speed cutting and mining automation. It is of great significance for improving shearer reliability, ensuring personal safety and improving coal quality. This paper proposed a coal-rock recognition method based on sound signal analysis. The original sound signal produced during the cutting process of shearer is decomposed by variational mode decomposition (VMD), and the obtained IMFs can construct a signal matrix. The signal matrix is processed by singular value decomposition (SVD), and a series of singular values can be obtained and defined as the signal features. Finally, the coal-rock recognition is realized by extreme learning machine (ELM) based on the extracted signal features. The experiment results show that the overall recognition accuracy is 91.7% under the actual cutting condition, which verifies the effectiveness of the proposed method in coal-rock recognition, and lays a theoretical foundation for the automation and intellectualization of shearer mining. |
| first_indexed | 2024-12-18T00:32:11Z |
| format | Article |
| id | doaj.art-d233f1c67bd34874ba5c3b29a2d497d4 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-18T00:32:11Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-d233f1c67bd34874ba5c3b29a2d497d42022-12-21T21:27:06ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-012320407510.1051/matecconf/201823204075matecconf_eitce2018_04075Research on coal-rock recognition based on sound signal analysisChen XihuiYang Zenan0Cheng Gang1College of Mechanical and Electrical Engineering, Hohai UniversitySchool of Mechatronic Engineering, China University of Mining and TechnologyThe recognition of the cutting state of shearer is the key technology to realize variable speed cutting and mining automation. It is of great significance for improving shearer reliability, ensuring personal safety and improving coal quality. This paper proposed a coal-rock recognition method based on sound signal analysis. The original sound signal produced during the cutting process of shearer is decomposed by variational mode decomposition (VMD), and the obtained IMFs can construct a signal matrix. The signal matrix is processed by singular value decomposition (SVD), and a series of singular values can be obtained and defined as the signal features. Finally, the coal-rock recognition is realized by extreme learning machine (ELM) based on the extracted signal features. The experiment results show that the overall recognition accuracy is 91.7% under the actual cutting condition, which verifies the effectiveness of the proposed method in coal-rock recognition, and lays a theoretical foundation for the automation and intellectualization of shearer mining.https://doi.org/10.1051/matecconf/201823204075 |
| spellingShingle | Chen Xihui Yang Zenan Cheng Gang Research on coal-rock recognition based on sound signal analysis MATEC Web of Conferences |
| title | Research on coal-rock recognition based on sound signal analysis |
| title_full | Research on coal-rock recognition based on sound signal analysis |
| title_fullStr | Research on coal-rock recognition based on sound signal analysis |
| title_full_unstemmed | Research on coal-rock recognition based on sound signal analysis |
| title_short | Research on coal-rock recognition based on sound signal analysis |
| title_sort | research on coal rock recognition based on sound signal analysis |
| url | https://doi.org/10.1051/matecconf/201823204075 |
| work_keys_str_mv | AT chenxihui researchoncoalrockrecognitionbasedonsoundsignalanalysis AT yangzenan researchoncoalrockrecognitionbasedonsoundsignalanalysis AT chenggang researchoncoalrockrecognitionbasedonsoundsignalanalysis |