The Geological Disasters Defense Expert System of the Massive Pipeline Network SCADA System Based on FNN

The Geological Disasters Defense Expert System of the Massive Pipeline Network SCADA System Based on FNN
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基于FNN的大型管网SCADA系统地质灾害防御专家系统

DOI:
10.1007/978-3-642-29426-6_4
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发表时间:
2012-04
期刊:
Lecture Notes in Computer Science
影响因子:
--
通讯作者:
Xeidong Cao,Cundang Wei ,Jie Li,Li Yang,Dan Zhang,Gang Tang,
Xeidong Cao,Cundang Wei ,Jie Li,Li Yang,Dan Zhang,Gang Tang,
中科院分区:
其他
文献类型:
--
作者:
Xeidong Cao,Cundang Wei ,Jie Li,Li Yang,Dan Zhang,Gang Tang,

文献摘要

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SCADA系统在大规模管网的长距离运行监测中发挥着重要作用,该管网可能会因滑坡、地质灾害而遭受巨大破坏。通过分析SCADA系统收集的详细信息,检测岩石的变形和位移,是预测滑坡地质灾害危害的关键。本文利用先进的TDR实时监测技术对岩石的倾角、位移、湿度等因素进行监测,并利用因子神经网络(FNN)理论建立模拟型因子神经网络模型。具体而言,基于模糊神经网络模型,通过对SCADA系统中大型网络的实时信息进行分析,设计了一个地质灾害潜在风险预测专家系统。
The SCADA system plays an important role in monitoring the long distance operation of mass pipeline network, which may experience huge damage due to landslides geological hazards. It is critical to detect the deformation and displacement of rock to forecast the damage of landslides geological hazards through analyzing detailed information collected by SCADA system. In this paper, we use advanced TDR real-time technology to monitor the factors of rock’s inclination, displacement, and humidity, and take advantage of factor neural network (FNN) theory to build a simulation-type factor neural network model. Particularly, based on FNN model, we design an expert system to forecast the potential risks of geological disasters through analyzing the real-time information of the large-scale network in the SCADA system.
DOI: --
发表时间: 2009
期刊: The Chinese Journal of Geological Hazard and Control
影响因子: --
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影响因子: --
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