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煤样失稳破坏的多参量监测试验
引用本文:姜耀东,吕玉凯,赵毅鑫,宋义敏,陶磊. 煤样失稳破坏的多参量监测试验[J]. 岩石力学与工程学报, 2012, 31(4): 667-674
作者姓名:姜耀东  吕玉凯  赵毅鑫  宋义敏  陶磊
作者单位:(1. 中国矿业大学 煤炭资源与安全开采国家重点实验室,北京 100083;2. 中国矿业大学 力学与建筑工程学院,北京 100083)
基金项目:国家重点基础研究发展计划(973)项目(2010CB226801);国家自然科学基金资助项目(51174213);新世纪优秀人才项目(NCET–10–775)
摘    要: 为有效提取由于巷道掘进及工作面回采扰动所诱发的煤岩体剧烈失稳破坏的前兆信息,针对煤样在外载荷作用下失稳破坏前会伴随弹性波、电荷、温度等信号的异常变化的特性,进行包括运用声发射仪、LCR电桥、红外热像仪及静态应变仪等设备在内的监测设备对煤样在单轴加载下的失稳破坏过程进行同步监测;通过建立同一时间坐标轴对多参量监测数据进行对比分析,研究试样失稳破坏前各参量的演化规律;运用多元统计分析中的主成分分析及因子分析方法对多参量监测数据进行分析,发现声发射监测结果能较好地体现出试样破坏的前兆特征,并与应力结果相结合分析可以更好地掌握其失稳破坏的前兆信息。

关 键 词:采矿工程多参量失稳破坏前兆主成分分析因子分析
收稿时间:2011-08-08

MULTIPARAMETER MONITORING EXPERIMENTS FOR INSTABILITY DESTRUCTION OF COAL SAMPLES
JIANG Yaodong,LU Yukai,ZHAO Yixin,SONG Yiming,TAO Lei. MULTIPARAMETER MONITORING EXPERIMENTS FOR INSTABILITY DESTRUCTION OF COAL SAMPLES[J]. Chinese Journal of Rock Mechanics and Engineering, 2012, 31(4): 667-674
Authors:JIANG Yaodong  LU Yukai  ZHAO Yixin  SONG Yiming  TAO Lei
Affiliation:(1. State Key Laboratory of Coal Resources and Safe Mining,China University of Mining and Technology,Beijing 100083,China;;2. School of Mechanics and Civil Engineering,China University of Mining and Technology,Beijing 100083,China)
Abstract:In order to obtain the precursor information of intense instability destruction of coal and rock mass which is induced by the deep mining,roadway excavation and face mining disturbance,according to the abnormal signal of coal samples would produce under external loads,which include elastic wave,charge,temperature signals,etc.,monitoring devices including acoustic emission instrument,LCR bridge,infrared thermograph and static strain devices are used to synchronously monitor the failure process under uniaxial compression.In order to study the multiparameter evolution characteristics,all data are selected in the same time axis.Meanwhile,principal component analysis and factor analysis in multivariate statistical analysis are used to analyze the original monitoring results of multiparameter;and the results show that acoustic emission and stress monitoring results could better reflect the characteristics of the samples precursor destruction and get the precursor information of coal samples instability destruction.
Keywords:mining engineering  multi-parameter  instability destruction  precursors  principal component analysis  factor analysis
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