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Mechanism and monitoring and early warning technology for rockburst in coal mines 被引量:11
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作者 Xue-qiu He Chao Zhou +4 位作者 Da-zhao Song Zhen-lei Li An-ye Cao Shen-quan He Majid Khan 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2021年第7期1097-1111,共15页
On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding t... On the basis of the massive amount of published literature and the long-term practice of our research group in the field of prevention and control of rockburst,the research progress and shortcomings in understanding the rockburst phenomenon have been comprehensively in-vestigated.This study focuses on the occurrence mechanism and monitoring and early warning technology for rockburst in coal mines.Results showed that the prevention and control of rockburst had made significant progress.However,with the increasing mining depth,several unre-solved concerns remain challenging.From the in-depth research and analysis,it can be inferred that rockburst disasters involve three main problems,i.e.,the induction factors are complicated,the mechanism is still unclear,and the accuracy of the monitoring equipment and multi-source stereo monitoring technology is insufficient.The monitoring and warning standards of rockburst need to be further clarified and im-proved.Combined with the Internet of Things,cloud computing,and big data,a study of the trend of rockburst needs to be conducted.Further-more,the mechanism of multiphase and multi-field coupling induced by rockburst on a large scale needs to be explored.A multisystem and multiparameter integrated monitoring and early warning system and remote monitoring cloud platform for rockburst should be explored and developed.High-reliability sensing technology and equipment and perfect monitoring and early warning standards are considered to be the de-velopment direction of rockburst in the future.This research will help experts and technicians adopt effective measures for controlling rock-burst disasters. 展开更多
关键词 coal mine ROCKBURST MECHANISM monitoring and early warning technology MULTIPARAMETER
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Designing a Teaching Website for Early Warning Technology Support Specialty Based on Information Architecture
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作者 Xiaobin Huang Yan Zhang 《Journal of Contemporary Educational Research》 2022年第1期7-11,共5页
With the advancement of education informatization,learning through the internet has become a very important approach.Existing teaching websites generally have problems such as low accuracy of information grouping and ... With the advancement of education informatization,learning through the internet has become a very important approach.Existing teaching websites generally have problems such as low accuracy of information grouping and obvious disconnection between the navigation system and content.Based on information architecture,a teaching website for early warning technical support specialty is designed in this paper from four aspects:content organization,identification,navigation,and interaction.The unification of information processing and information requirements is achieved using this method,which improves the quality of professional course construction for early warning technology support specialty. 展开更多
关键词 Information architecture early warning technology support specialty Website design
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An Artificial Intelligence Algorithm for the Real-Time Early Detection of Sticking Phenomena in Horizontal Shale Gas Wells
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作者 Qing Wang Haige Wang +2 位作者 Hongchun Huang Lubin Zhuo Guodong Ji 《Fluid Dynamics & Materials Processing》 EI 2023年第10期2569-2578,共10页
Sticking is the most serious cause of failure in complex drilling operations.In the present work a novel“early warning”method based on an artificial intelligence algorithm is proposed to overcome some of the known pr... Sticking is the most serious cause of failure in complex drilling operations.In the present work a novel“early warning”method based on an artificial intelligence algorithm is proposed to overcome some of the known pro-blems associated with existing sticking-identification technologies.The method is tested against a practical case study(Southern Sichuan shale gas drilling operations).It is shown that the twelve sets of sticking fault diagnostic results obtained from a simulation are all consistent with the actual downhole state;furthermore,the results from four groups of verification samples are also consistent with the actual downhole state.This shows that the pro-posed training-based model can effectively be applied to practical situations. 展开更多
关键词 Shale gas drilling sticking fault artificial intelligence risk early warning technology
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