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Analysis of microseismic activity in rock mass controlled by fault in deep metal mine 被引量:1
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作者 Liu Jianpo Liu Zhaosheng +2 位作者 Wang Shaoquan Shi Changyan Li Yuanhui 《International Journal of Mining Science and Technology》 SCIE EI CSCD 2016年第2期235-239,共5页
Aiming at evaluating the stability of a rock mass near a fault,a microseismic(MS) monitoring system was established in Hongtoushan copper mine.The distribution of displacement and log(/),the relationship between MS ac... Aiming at evaluating the stability of a rock mass near a fault,a microseismic(MS) monitoring system was established in Hongtoushan copper mine.The distribution of displacement and log(/),the relationship between MS activity and the exploitation process,and the stability of the rock mass controlled by a fault were studied.The results obtained from microseismic data showed that MS events were mainly concentrated al the footwall of the fault.When the distance to the fault exceeded 20 m,the rock mass reached a relatively stable state.MS activity is closely related to the mining process.Under the strong disturbance from blasting,the initiation and propagation of cracks is much faster.MS activity belongs in the category of aftershocks after large scale excavation.The displacement and log(C/) obtained from MS events can reflect the difference in physical and mechanical behavior of different areas within the rock mass,which is useful in judging the integrity and degradation of the rock mass. 展开更多
关键词 Deep mining fault Microseism(MS) Stability
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Overview of the Importance of Intelligent Approaches on Machinery Faults Diagnosis and Prediction Based on Prognostic and Health Management/Condition-Based Maintenance 被引量:1
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作者 OMIDI Ali LIU Shujie 《Journal of Donghua University(English Edition)》 EI CAS 2018年第3期270-273,共4页
Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accide... Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM. 展开更多
关键词 condition-based maintenance(CBM) prognostic and health management(PHM) machinery fault diagnosis data mining data processing
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