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基于域间依赖模型的多域故障诊断算法 被引量:1
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作者 简江涛 荀鹏 蔡开裕 《计算机技术与发展》 2015年第4期13-17,共5页
在多域环境下,组合服务所调用的子服务跨越多个管理域,对域间故障传播产生的跨域症状进行诊断时需要管理域之间相互协作。针对这一问题,文中提出了域间依赖模型,阐明了症状与管理域的依赖关系,并基于该模型提出多域故障诊断算法,并从时... 在多域环境下,组合服务所调用的子服务跨越多个管理域,对域间故障传播产生的跨域症状进行诊断时需要管理域之间相互协作。针对这一问题,文中提出了域间依赖模型,阐明了症状与管理域的依赖关系,并基于该模型提出多域故障诊断算法,并从时间性能方面对算法进行了改进。文中首先通过症状簇划分算法对症状集合进行划分,对同一症状簇协同诊断;然后通过对跨域症状与关联域依赖关系的概率评估,选择最可能的关联域集合进行诊断;最后,仿真结果表明该算法可以较为准确地诊断多域环境下的服务故障。 展开更多
关键词 依赖关系 域间依赖模型 故障诊断 概率评估 症状簇
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Superposition model for analyzing the dynamic ground subsidence in mining area of thick loose layer 被引量:2
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作者 Defeng Hou Dehai Li +1 位作者 Guosheng Xu Yanbin Zhang 《International Journal of Mining Science and Technology》 EI CSCD 2018年第4期656-661,共6页
The dynamic ground subsidence due to underground mining is a complicated time-dependent and rate- dependent process. Based. on the theory of rock rheology and probability integral method, this study developed the supe... The dynamic ground subsidence due to underground mining is a complicated time-dependent and rate- dependent process. Based. on the theory of rock rheology and probability integral method, this study developed the superposltlOn model for the prediction and analysis of the ground dynamic subsidence in mining area of thick !oose layer. The model consists of two parts (the prediction of overlying bedrock and the prediction of thick loose layer). The overlying bedrock is regarded as visco-elastic beam, of which the dynamic subsidence is predicted by the Kelvin visco-elastic rheological model. The thick loose layer is regarded as random medium, and the ground dynamic subsidence, is predicted by the probability integral model. At last, the two prediction models are vertically stacked in the same coordinate system, and the bedrock dynamic subsidence is regarded as a variable mining thickness input into the prediction model of ground dynamic subsidence. The prediction results obtained were compared w^th actual movement and deformation data from Zhao I and Zhao II mine, central China. The agreement of the prediction results with the. field measurements.show that the superposition model (SM) is more satisfactory and the formulae obtained are more effective than the classical single probability Integral model(SPIM), and thus can be effectively used for predicting the ground dynamic subsidence in mining area of thick loose layer. 展开更多
关键词 Thick loose layer Dynamic groundsubsidence Kelvin visco-elastic rheological model Random medium Single probability integral model Superposition model
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