Recognition Method of Coal-Rock Reflection Spectrum Using Wavelet Scattering Transform and Bidirectional Long-Short-Term Memory
文献类型：期刊论文
| 作者 | Ding, Z. W.3; Zhang, C. F.3; Huang, X.4; Liu, Q. S.5; Liu, B.4; Gao, F.5; Li, L.1; Liu, Y. X.2 |
| 刊名 | ROCK MECHANICS AND ROCK ENGINEERING
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| 出版日期 | 2023-10-24 |
| 页码 | 22 |
| 关键词 | Intelligent mining Coal-rock identification Reflection spectrum Wavelet scattering transform Bidirectional long-short-term memory |
| ISSN号 | 0723-2632 |
| DOI | 10.1007/s00603-023-03600-z |
| 英文摘要 | Classifying and recognizing the reflection spectrum of coal-rock is an innovative method for coal-rock identification in coal mining process. Herein, a classification and recognition method of coal-rock reflection spectrum based on wavelet scattering transform (WST) and bidirectional long-short-term memory (BiLSTM) network was proposed to improve the recognition speed and accuracy. First, the reflection spectra of coal-rock samples were obtained using the coal-rock reflection spectrum information acquisition platform, and two spectral databases with different coal-rock states and different sampling parameter combinations were established to train the network model. Second, the original data were preprocessed by Gaussian filtering and randomly divided into the training set and test set. The wavelet scattering network was used to effectively extract spectral features from the reflection spectrum and generate a feature matrix. Finally, the training set feature matrix was input into the BiLSTM network model for training to obtain the WST-BiLSTM model. The effectiveness of the proposed network model was verified using the test set. The experimental results showed that the WST-BiLSTM model can classify and identify the coal-rock reflection spectrum more accurately than other related models in literature, and the recognition accuracy for the two databases reached 99.4% and 100%. Based on the constructed multi-state and multi-parameter combination spectral database, the proposed coal-rock recognition model has good adaptability to the reflected spectrum collected by different parameters. Hence, this model can provide a theoretical basis and technical premise for automatic and intelligent coal mining. A reflection spectrum database is established with different coal-rock states and sampling parametersA coal-rock reflection spectrum recognition model is developed using wavelet scattering transform feature extraction method.Training speed and recognition accuracy of the model are improved by changing the sampling parameters. |
| 资助项目 | First and foremost, the authors thank the research team of China University of Mining and Technology for guiding the construction of the spectral data acquisition platform in this experiment. The authors are thankful for the financial assistance provided b[52074209] ; First and foremost, the authors thank the research team of China University of Mining and Technology for guiding the construction of the spectral data acquisition platform in this experiment. The authors are thankful for the financial assistance provided b[51874232] ; First and foremost, the authors thank the research team of China University of Mining and Technology for guiding the construction of the spectral data acquisition platform in this experiment. The authors are thankful for the financial assistance provided b[52074258] ; National Natural Science Foundation of China[2021JLM-06] ; Natural Science Basic Research Program of Shaanxi Province (Shaanxi Coal and Chemical Industry Group Co., Ltd.)[2022CFA084] ; Outstanding Youth Fund Program of Natural Science Foundation of Hubei Province, China |
| WOS研究方向 | Engineering ; Geology |
| 语种 | 英语 |
| WOS记录号 | WOS:001090366900002 |
| 出版者 | SPRINGER WIEN |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/39757]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Huang, X. |
| 作者单位 | 1.Shaanxi Coal & Chem Ind Technol Res Inst Co Ltd, Xian 710199, Shaanxi, Peoples R China 2.Shandong Energy Grp Xibei Min Co Ltd, Xian 710016, Peoples R China 3.Xian Univ Sci & Technol, Coll Energy Engn, Xian 710054, Shanxi, Peoples R China 4.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Hubei, Peoples R China 5.Wuhan Univ, Key Lab Geotech & Struct Engn Safety Hubei Prov, Wuhan 430072, Hubei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ding, Z. W.,Zhang, C. F.,Huang, X.,et al. Recognition Method of Coal-Rock Reflection Spectrum Using Wavelet Scattering Transform and Bidirectional Long-Short-Term Memory[J]. ROCK MECHANICS AND ROCK ENGINEERING,2023:22. |
| APA | Ding, Z. W..,Zhang, C. F..,Huang, X..,Liu, Q. S..,Liu, B..,...&Liu, Y. X..(2023).Recognition Method of Coal-Rock Reflection Spectrum Using Wavelet Scattering Transform and Bidirectional Long-Short-Term Memory.ROCK MECHANICS AND ROCK ENGINEERING,22. |
| MLA | Ding, Z. W.,et al."Recognition Method of Coal-Rock Reflection Spectrum Using Wavelet Scattering Transform and Bidirectional Long-Short-Term Memory".ROCK MECHANICS AND ROCK ENGINEERING (2023):22. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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