Information Granularity With the Self-Emergence Mechanism for Event Detection in WSN-Based Tunnel Health Monitoring

Li Gang; He Bin; Zhou Yanmin; Zhu Zhongpan; Huang Hongwei

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Information Granularity With the Self-Emergence Mechanism for Event Detection in WSN-Based Tunnel Health Monitoring

机译：基于WSN的隧道健康监测中的事件检测自出射机机制的信息粒度

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Because of its rapid deployment, low cost, self-organization, node distribution and other characteristics, the wireless sensor networks (WSNs) are very suitable for various types of monitoring systems. Event detection using sensor data is the purpose of the monitoring system. To build the bridge between data and phenomena, this work proposes an information granularity. The information granularity characterizes the health state of each monitoring ring in the tunnel by qualitative description and quantitative representation. Through building the tree augmented naive Bayesian-based qualitative classifier based on the minimum risk, a qualitative description method of the information granularity is proposed, which is taken as a preliminary judgment of disasters. Inspired by vague set theory, a quantitative representation method of the information granularity is also presented, which analyzes disaster phenomena in detail. To realize the multiscale online monitoring of the entire tunnel state, a kind of self-emergence mechanism of the information granularity is also described. The information granularity is formed gradually through distributed computing during information transmission, which characterizes the event autonomously. The experimental results show that the information granularity realizes rapid, accurate and multiscale representation of tunnel health status.

机译：由于其快速部署，低成本，自组织，节点分配和其他特性，无线传感器网络（WSN）非常适合各种类型的监控系统。使用传感器数据的事件检测是监控系统的目的。为了构建数据和现象之间的桥梁，这项工作提出了一种信息粒度。信息粒度通过定性描述和定量表示表征隧道中每个监测环的健康状态。通过基于最小风险构建基于树增强的天真贝叶斯的定性分类，提出了信息粒度的定性描述方法，被视为灾害的初步判断。灵感来自模糊集理论，还提出了信息粒度的定量表示方法，详细分析了灾害现象。为了实现整个隧道状态的多尺度在线监测，还描述了一种信息粒度的自出射机机制。通过在信息传输期间通过分布式计算逐渐形成信息粒度，其在自主地表征事件的表征中。实验结果表明，信息粒度意识到隧道健康状况的快速，准确和多尺度表示。

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来源
《IEEE sensors journal》 |2020年第15期|8265-8275|共11页
作者
Li Gang; He Bin; Zhou Yanmin; Zhu Zhongpan; Huang Hongwei;
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作者单位

Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China;

Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China;

Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China;

Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China;

Tongji Univ Dept Geotech Engn Shanghai 200092 Peoples R China;

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原文格式 PDF
正文语种 eng
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关键词
Monitoring; Event detection; Sensor phenomena and characterization; Bayes methods; Sensor systems; Event detection; information granularity; vague set; self-emergence mechanism; tunnel health monitoring;

机译：监测;事件检测;传感器现象和表征;贝叶斯方法;传感器系统;事件检测;信息粒度;模糊的套装;自我出现机制;隧道健康监测;

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Information Granularity With the Self-Emergence Mechanism for Event Detection in WSN-Based Tunnel Health Monitoring

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