• 论文
主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
时间序列ARIMA模型在煤矿地音监测系统中的应用
  • Title

    Application of time series ARIMA model in coal mine ground sound monitoring system

  • 作者

    孙学波刘宁王元杰陈法兵李岩

  • Author

    SUN Xuebo;LIU Ning;WANG Yuanjie;CHEN Fabing;LI Yan

  • 单位

    中煤科工开采研究院有限公司

  • Organization
    CCTEG Coal Mining Research Institute
  • 摘要
    针对目前微震监测系统在冲击地压临震预警存在滞后性的问题,应用地音监测系统对冲击地压进行监测,同时进行了时间序列ARIMA模型在数据预测方面的研究。研究采用四通道ARES-5/E地音监测系统进行连续数据监测,首先对地音多通道监测数据进行数据清洗,剔除随机与干扰数据;然后对数据进行平稳性检验与数据差分分析;接着建立ARIMA数据模型并对模型进行相关性估计,识别模型参数后再对模型的有效性进行检验,通过检验后的模型对地音数据进行预测与识别。通过对石拉乌素矿地音设备监测的长期数据进行多层次提取并预测发现,时间序列ARIMA模型在中短期地音数据预测方面具有显著优势。
  • Abstract
    In view of the lag of the current microseismic monitoring system in the imminent warning of rockburst, the earth sound monitoring system is applied to monitor rockburst and the time series ARIMA model is studied in data prediction. The 4-channel ARES- 5/ e geoacoustic monitoring system is installed for continuous data monitoring. Firstly, the multi-channel geoacoustic monitoring data are cleaned to eliminate random and interference data, and then the data are tested for stationarity and data difference analysis. Then, the ARIMA data model is established and the correlation of the model is estimated. After identifying the model parameters, the validity of the model is tested, With the verified model, the ground sound data is predicted and recognized. Through the multi - level extraction of the long - term data monitored by the geological sound equipment of Shilawusu Mine and the prediction of the geological sound data value in the later period, it is found that the time series ARIMA model has excellent prediction advantages in the prediction of medium and short-term geological sound data.
  • 关键词

    时间序列ARIMA模型冲击地压地音监测系统

  • KeyWords

    time series; ARIMA model; rock burst; ground sound monitoring system

  • 基金项目(Foundation)
    中国煤炭科工集团有限公司集团产学研项目(2019-TD-2-CXY006)
  • DOI
  • 引用格式
    孙学波, 刘 宁, 王元杰, 等. 时间序列 ARIMA 模型在煤矿地音监测系统中的应用 [J]. 煤炭工程, 2023,55(10): 111-117.
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主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会

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