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A Novel Distributed Linear-Spatial-Array Sensing System Based on Multichannel LPWAN for Large-Scale Blast Wave Monitoring

机译:基于MultiShannel LPWAN的大型爆炸波监测的新型分布式线性空间阵列传感系统

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摘要

Traditional wired monitoring systems exhibit huge limitations in blast wave monitoring. To meet the requirements of long range, low cost, weight reduction, increased ease of installation maintenance, and big-data transmission in blast wave monitoring, a new distributed linear-spatial-array (D-LSA) sensing system based on low-power wide-area network (LPWAN) is proposed in this paper. This approach adopts a multichannel LoRa and NB-IoT air-blast gateway (M-CLNAG) and multiple FPGA-based wireless pressure LoRa nodes (FWPLNs) to construct a large-scale LPWAN for blast wave monitoring. The empirical models of dynamic parameter calculation (peak overpressure, duration of the positive phase and impulse) on the basis of D-LSA sensing system are redesigned for blast wave monitoring as well. Furthermore, we have evaluated the errors between the measured data from D-LSA sensing system and data from the redesigned empirical models. Finally, the wireless quality performance in terms of received signal strength indication (RSSI) and packet receive rate (PDR) for blast wave monitoring is also verified. This paper is conducted to provide new insights into how a sensing system integrating with LPWAN is designed in blast wave monitoring for acquiring dynamic parameters accurately and carrying out remote network communication efficiently, and further opening a door for wireless sensor network (WSN) in more blast wave monitoring scenarios.
机译:传统的有线监测系统在爆炸波监测中表现出巨大的局限性。为了满足长距离,成本低,减重,安装维护方便的易于易用程度的要求,以及爆发波监测的大数据传输,基于低功耗的新型分布式线性空间阵列(D-LSA)传感系统本文提出了广域网(LPWAN)。该方法采用多通道LORA和NB-IOT AIR-BLAST网关(M-CLNAG)和多个基于FPGA的无线压力LORA节点(FWPLNS)来构建大规模的LPWAN进行爆频监测。基于D-LSA传感系统的动态参数计算(峰值过压,正相和脉冲持续时间)的经验模型,还重新设计了BLOST波监测。此外,我们已经在D-LSA感测系统和来自重新设计的经验模型的数据中评估了测量数据之间的错误。最后,还验证了用于接收信号强度指示(RSSI)和分组接收率(PDR)的无线质量性能。进行本文以提供新的见解,进入LPWAN的传感系统在爆炸波监测中设计了如何精确地获取动态参数并有效地进行远程网络通信,并进一步打开用于无线传感器网络(WSN)的门更频繁波监控场景。

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