Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powe...Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.展开更多
In order to overcome the limitation that rock mass instability warnings are caused by a lack of deep consideration of the inherent mechanism of disaster formation, early warning signs of rock mass instability were det...In order to overcome the limitation that rock mass instability warnings are caused by a lack of deep consideration of the inherent mechanism of disaster formation, early warning signs of rock mass instability were detected and multi-field coupling was analyzed. A multi-field coupling model of a damaged rock mass was established. The relationship between microseismic activity parameters and rock mass stability was analyzed, and a multi-parameter early warning index system was established and its solution program was compiled. Based on the D-S data fusion theory,an early warning model of rock mass instability combining multi-field coupling analysis and microseismic monitoring was constructed. Taking an underground mine stope as an object, the multi-field coupling model and its solution program were used to analyze mining response characteristics. The seismic field data were used to verify the accuracy of the multi-field coupling analysis. The early warning model was used to predict the instability of stope rock mass,and the early warning result is consistent with a real-world scenario.展开更多
随着智能控制系统(Intelligent Control System,ICS)的发展,发电行业所具备的大量数据能够被逐步利用,与机理融合,借助算法提高机组运行的经济性和安全性。本文借助智能控制系统的平台,以滑动平均、最小二乘等方法,建立数据与机理融合...随着智能控制系统(Intelligent Control System,ICS)的发展,发电行业所具备的大量数据能够被逐步利用,与机理融合,借助算法提高机组运行的经济性和安全性。本文借助智能控制系统的平台,以滑动平均、最小二乘等方法,建立数据与机理融合的受热面汽水系统回归模型,通过多维度评估比较模型与实际的差异,判断并定位受热面汽水系统的泄漏情况,以简单直观的画面进行展示。展开更多
基金provided by the State Key Research Development Program of China (No.2016YFC0801403)Key Research Development Program of Jiangsu Provence (No.BE2015040)+1 种基金National Natural Science Foundation of China (Nos.51674253,51734009 and 51604270)Natural Science Foundation of Jiangsu Province (No.BK20171191)
文摘Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.
基金Project(2017yfc0602901)supported by the National Key R&D Program of China during the Thirteenth Five-Year Plan PeriodProject(2017zzts204)supported by the Fundamental Research Funds for the Central Universities of Central South University,China
文摘In order to overcome the limitation that rock mass instability warnings are caused by a lack of deep consideration of the inherent mechanism of disaster formation, early warning signs of rock mass instability were detected and multi-field coupling was analyzed. A multi-field coupling model of a damaged rock mass was established. The relationship between microseismic activity parameters and rock mass stability was analyzed, and a multi-parameter early warning index system was established and its solution program was compiled. Based on the D-S data fusion theory,an early warning model of rock mass instability combining multi-field coupling analysis and microseismic monitoring was constructed. Taking an underground mine stope as an object, the multi-field coupling model and its solution program were used to analyze mining response characteristics. The seismic field data were used to verify the accuracy of the multi-field coupling analysis. The early warning model was used to predict the instability of stope rock mass,and the early warning result is consistent with a real-world scenario.
文摘随着智能控制系统(Intelligent Control System,ICS)的发展,发电行业所具备的大量数据能够被逐步利用,与机理融合,借助算法提高机组运行的经济性和安全性。本文借助智能控制系统的平台,以滑动平均、最小二乘等方法,建立数据与机理融合的受热面汽水系统回归模型,通过多维度评估比较模型与实际的差异,判断并定位受热面汽水系统的泄漏情况,以简单直观的画面进行展示。
