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Gold Science and Technology >

2022 , Vol. 30 >Issue 2: 209 - 221

DOI: https://doi.org/10.11872/j.issn.1005-2518.2022.02.162

Mining Technology and Mine Management

Identification and Classification Method of Underground AE Source Based on Improved CEEMDAN-DCNN

  • Xuebin XIE ,
  • Tao LIU ,
  • Huan ZHANG
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  • School of Resources and Safety Engineering，Central South University，Changsha 410083，Hunan，China

Received date: 2021-11-03

  Revised date: 2021-12-28

  Online published: 2022-06-17

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Highlights

Accurate classification and identification of acoustic emission sources is an important basis for the study of acoustic emission ground pressure monitoring， forecasting and early warning.Aiming at the clas-sification and identification of acoustic emission event signals and mining operation noise signals of surrounding rock masses in underground mines， an intelligent recognition and classification method based on improved complete ensemble empirical mode decomposition and deep convolutional neural network（DCNN）was proposed.Firstly，the signal was decomposed by CEEMDAN， the decomposed IMF components were screened， and the components greater than the permutation entropy threshold or less than the correlation coefficient threshold were removed， and the residual IMF components were reconstructed to obtain the denoised waveform.Then， the DCNN method was used to automatically extract high-dimensional features from the denoised waveform.Finally， the features were used for classification and recognition of softmax classifier to realize intelligent multi-classification of underground signal sources.The results of this research show that：（1）Aiming at the difficulty of multi-classification of waveforms received by acoustic emission monitoring equipment，a waveform classification and recognition method based on improved CEEMDAN-DCNN is proposed.Combined with the advantages of improved CEEMDAN’s advantages of adaptive analysis，pro-cessing of nonlinear and non-stationary signals and the ability of DCNN to automatically extract high-dimensional features， the intelligent multi-classification of underground signal sources is realized.（2）In order to verify the advantages of the improved CEEMDAN algorithm， the simulation signal is constructed to simulate the acoustic emission signal of surrounding rock mass containing noise signal， and the background noise component and pseudo component are eliminated by a joint threshold.The results show that the improved CEEMDAN algorithm can eliminate noise signals and some false components， and retain the essential characteristics of the signal.（3）Through the test， the accuracy of waveform classification based on the improved CEEMDAN-DCNN method in this paper reaches 97.12%. Compared with the traditional SVM， ANN， and CNN methods， the accuracy of waveform classification is higher and the stability is better. The accuracy of DCNN classification and recognition is improved dueing to the signal preprocessed by improved CEEMDAN.（4）The waveform recognition and classification method in this paper can accurately identify the acoustic emission events of surrounding rock masses and non-surrounding rock masses， provide reliable basic research data for ground pressure monitoring and early warning models， and increase the accuracy of ground pressure monitoring and safety early warning and forecasting.

Cite this article

Xuebin XIE , Tao LIU , Huan ZHANG . Identification and Classification Method of Underground AE Source Based on Improved CEEMDAN-DCNN[J]. Gold Science and Technology, 2022 , 30(2) : 209 -221 . DOI: 10.11872/j.issn.1005-2518.2022.02.162

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一季度我国黄金产量同比增长超一成，消费量下降近一成

4月27日，中国黄金协会发布2022年一季度黄金行业发展运行情况。今年一季度，我国产金83.401 t，同比增长12.04%；黄金实际消费量260.26 t，同比下降9.69%；黄金价格振荡飙升，已逼近历史最高水平。

（1）黄金生产

2022年一季度，国内原料黄金产量为83.401 t，比2021年一季度增产8.962 t，同比增长12.04%。其中，黄金矿产金完成65.009 t，有色副产金完成18.392 t。另外，2022年一季度进口原料产金24.034 t，同比增长0.18%，若加上这部分进口原料产金，全国共生产黄金107.435 t，同比增长9.15%。

与去年同期相比，2022年一季度我国产金大省山东和河南黄金生产企业已基本恢复以往年度的正常产能，全国黄金产量较去年同期大幅上涨。山东省烟台地区黄金矿产资源实现快速整合，产业集中度进一步提升。

2022年一季度，大型黄金企业（集团）境内矿山矿产金产量33.856 t，比去年同期增长10%，占全国的比重为52.08%。大型黄金企业（集团）继续稳步推进海外矿山资源开发，海外黄金矿山产量显著提升。2022年一季度，紫金矿业、山东黄金和赤峰黄金等企业境外矿山实现矿产金产量11.144 t，同比增长45.11%。

（2）黄金消费

2022年一季度，全国黄金实际消费量260.26 t，与2021年同期相比下降9.69%。其中，黄金首饰168.86 t，同比下降0.19%；金条及金币69.62 t，同比下降27.71%；工业及其他用金21.78 t，同比下降4.10%。

受益于消费需求释放，又恰逢春节、元宵节、情人节购物热潮，1~2月黄金首饰消费保持强势，但随着3月份黄金价格的上涨及国内部分地区发生聚集性疫情，黄金首饰消费受到较大冲击，一季度整体消费被拉低。

全球政治经济形势的多变支撑了黄金投资需求，一些大型黄金零售商和商业银行金条销量仍维持一定增长，但金价的高企加重了民间投资者的观望情绪，标准小金条出库量大幅下降，导致金条销量整体下滑。在北京冬奥会纪念币和贺岁纪念币热销的带动下，金币消费反而较上一年同期有所增长。

http://www.goldsci.ac.cn/article/2022/1005-2518/1005-2518-2022-30-2-209.shtml

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