基于低成本地震动传感器的地震预警系统:系统文献综述

Chanthujan Chandrakumar, R. Prasanna, M. Stephens, M. L. Tan
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引用次数: 1

摘要

地震预警系统(EEWS)在探测地震时的地面震动,提醒公众和当局采取适当的安全措施,减少可能造成的生命财产损失方面发挥着重要作用。然而,高端地面运动传感器的成本使得大多数地震易发国家无力负担EEWS。基于微机电系统(MEMS)的低成本地震动传感器正在成为一种有前途的解决方案,用于构建经济实惠、可靠且强大的EEWS。本文通过对不同地区使用mems传感器构建低成本地震预警系统的不同方法和途径进行文献综述,为推进地震预警(EEW)研究做出贡献。对59篇文章的回顾发现,低成本的基于mems的EEWS可以成为产生可靠和精确的EEWS的可行解决方案,特别是对于发展中国家,并且可以在增加传感器密度方面作为高端EEWS的支持系统。并根据预警类型和所采用的EEW算法对eews进行分类。此外,在拟议的EEWS分类的支持下,它总结了研究人员在开发EEWS时尝试的不同方法。接下来,本文讨论了实现和维护低成本mems EEWS的挑战和复杂性,并提出了未来提高EEWS性能的研究方向,主要包括1)探索节点级处理,2)引入多传感器支持能力,以及3)采用基于地震动的EEW算法生成EEW。
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Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review
Earthquake early warning system (EEWS) plays an important role in detecting ground shaking during an earthquake and alerting the public and authorities to take appropriate safety measures, reducing possible damages to lives and property. However, the cost of high-end ground motion sensors makes most earthquake-prone countries unable to afford an EEWS. Low-cost Microelectromechanical systems (MEMS)-based ground motion sensors are becoming a promising solution for constructing an affordable yet reliable and robust EEWS. This paper contributes to advancing Earthquake early warning (EEW) research by conducting a literature review investigating different methods and approaches to building a low-cost EEWS using MEMS-based sensors in different territories. The review of 59 articles found that low-cost MEMS-based EEWSs can become a feasible solution for generating reliable and accurate EEW, especially for developing countries and can serve as a support system for high-end EEWS in terms of increasing the density of the sensors. Also, this paper proposes a classification for EEWSs based on the warning type and the EEW algorithm adopted. Further, with the support of the proposed EEWS classification, it summarises the different approaches researchers attempted in developing an EEWS. Following that, this paper discusses the challenges and complexities in implementing and maintaining a low-cost MEMS-based EEWS and proposes future research areas to improve the performance of EEWSs mainly in 1) exploring node-level processing, 2) introducing multi-sensor support capability, and 3) adopting ground motion-based EEW algorithms for generating EEW.
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