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Kalman Filter-based Data Recovery in Wireless Smart Sensor Network for Infrastructure Monitoring

机译:无线传感器网络中基于卡尔曼滤波器的数据恢复,用于基础设施监控

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摘要

Extensive research effort has been made during the last decade to utilize wireless smart sensors for evaluating and monitoring structural integrity of civil engineering structures. The wireless smart sensor commonly has sensing and embedded computation capabilities as well as wireless communication that provide strong potential to overcome shortcomings of traditional wired sensor systems such as high equipment and installation cost. However, sensor malfunctioning particularly in case of long-term monitoring and unreliable wireless communication in harsh environment are the critical issues that should be properly tackled for a wider adoption of wireless smart sensors in practice. This study presents a wireless smart sensor network(WSSN) that can estimate unmeasured responses for the purpose of data recovery at unresponsive sensor nodes. A software program that runs on WSSN is developed to estimate the unmeasured responses from the measured using the Kalman filter. The performance of the developed network software is experimentally verified by estimating unmeasured acceleration responses using a simply-supported beam.
机译:在过去的十年中,已经进行了广泛的研究,以利用无线智能传感器来评估和监视土木工程结构的结构完整性。无线智能传感器通常具有传感和嵌入式计算功能以及无线通信功能,这些功能具有强大的潜力,可以克服传统有线传感器系统的缺点,例如设备和安装成本较高。但是,传感器故障,尤其是在长期监视和恶劣环境下不可靠的无线通信的情况下,是应在实际中广泛采用无线智能传感器的关键问题。这项研究提出了一种无线智能传感器网络(WSSN),该网络可以估计未测量的响应,以便在无响应的传感器节点上恢复数据。开发了在WSSN上运行的软件程序,以使用卡尔曼滤波器从测量值中估算出未测量的响应。通过使用简单支撑的梁估算未测得的加速度响应,对开发的网络软件的性能进行了实验验证。

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