A Lightweight Wireless Overpressure Node Based Efficient Monitoring for Shock Waves

Shang Gao; Guiyun Tian; Xuewu Dai; Qing Zhang; Zhiling Wang; Xinge Yang; Qiaomu Wang; Naishu Jia

doi:10.1109/TMECH.2020.3025955

A Lightweight Wireless Overpressure Node Based Efficient Monitoring for Shock Waves

Shang Gao^*, Guiyun Tian, Xuewu Dai, Qing Zhang, Zhiling Wang, Xinge Yang, Qiaomu Wang, Naishu Jia

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

Overpressure measurement is an important approach to evaluate the power of shock wave (SW) monitoring. Traditional wired monitoring systems exhibit the limitations of high-cost, heavyweight, troublesome maintenance, and big-data transmission in SW monitoring. In this article, a new lightweight FPGA-based wireless overpressure node (LFWON) with the resistance to higherature and high-pressure environment for SW monitoring. The proposed LFWON is based on the Spartan-6 XC6SLX9-2TQG144C FPGA circuit, via a serial peripheral interface to the RF transceiver and data bus to the NAND flash chip for data management. To validate the LFWON, experimental tests in terms of dynamic parameters and network quality are performed in a real blast testing with 8-kg trinitrotoluene. This article is conducted to provide new insights into how the antishocking structure and sensing algorithm of wireless sensor node is designed in SW monitoring for acquiring overpressure accurately. The results show that the errors of Δ P(7 m-12m), td(>6 m), and I + (3m-24 m) from proposed LFWON are below 20% in comparison with wired system. In addition, the RSSI value of LFWON should be set above-70 dBm for stable communication quality.

Original language	English
Article number	9206070
Pages (from-to)	448-457
Number of pages	10
Journal	IEEE/ASME Transactions on Mechatronics
Volume	26
Issue number	1
Early online date	25 Sept 2020
DOIs	https://doi.org/10.1109/TMECH.2020.3025955
Publication status	Published - Feb 2021

Keywords

Dynamic parameter
network quality
overpressure
shock wave (SW) monitoring
wireless sensor network (WSN)

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10.1109/TMECH.2020.3025955

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title = "A Lightweight Wireless Overpressure Node Based Efficient Monitoring for Shock Waves",

abstract = "Overpressure measurement is an important approach to evaluate the power of shock wave (SW) monitoring. Traditional wired monitoring systems exhibit the limitations of high-cost, heavyweight, troublesome maintenance, and big-data transmission in SW monitoring. In this article, a new lightweight FPGA-based wireless overpressure node (LFWON) with the resistance to higherature and high-pressure environment for SW monitoring. The proposed LFWON is based on the Spartan-6 XC6SLX9-2TQG144C FPGA circuit, via a serial peripheral interface to the RF transceiver and data bus to the NAND flash chip for data management. To validate the LFWON, experimental tests in terms of dynamic parameters and network quality are performed in a real blast testing with 8-kg trinitrotoluene. This article is conducted to provide new insights into how the antishocking structure and sensing algorithm of wireless sensor node is designed in SW monitoring for acquiring overpressure accurately. The results show that the errors of Δ P(7 m-12m), td(>6 m), and I + (3m-24 m) from proposed LFWON are below 20\% in comparison with wired system. In addition, the RSSI value of LFWON should be set above-70 dBm for stable communication quality.",

keywords = "Dynamic parameter, network quality, overpressure, shock wave (SW) monitoring, wireless sensor network (WSN)",

author = "Shang Gao and Guiyun Tian and Xuewu Dai and Qing Zhang and Zhiling Wang and Xinge Yang and Qiaomu Wang and Naishu Jia",

note = "Funding Information: Manuscript received January 9, 2019; revised May 5, 2019, March 16, 2020, and August 11, 2020; accepted September 18, 2020. Date of publication September 25, 2020; date of current version February 16, 2021. Recommended by Technical Editor X.-T. Yan and Senior Editor I.-M. Chen. This work was supported in part by the Nanjing University of Science and Technology under Research Start-Up Funds under Grant AE89991/032; in part by the Fundamental Research Funds for the Central Universities under Grant 309181A8804 and Grant 30919011263, in part by the Natural Science Foundation of Jiangsu Province, China under Grant BK20190464, in part by the Jiangsu Planned Projects for Postdoctoral Research Funds under Grant 1003-YBA20012, in part by the Chinese Postdoctoral Science Foundation under Grant 2020M671481, and in part by the National Natural Science Foundation of China under Grant 61527803, Grant 51905242, Grant 61960206010, and Grant 61903193. (Corresponding author: Shang Gao.) Shang Gao and Qing Zhang are with the College of automation engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China (e-mail: [email protected]; [email protected]).",

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AU - Gao, Shang

AU - Tian, Guiyun

AU - Dai, Xuewu

AU - Zhang, Qing

AU - Wang, Zhiling

AU - Yang, Xinge

AU - Wang, Qiaomu

AU - Jia, Naishu

N1 - Funding Information: Manuscript received January 9, 2019; revised May 5, 2019, March 16, 2020, and August 11, 2020; accepted September 18, 2020. Date of publication September 25, 2020; date of current version February 16, 2021. Recommended by Technical Editor X.-T. Yan and Senior Editor I.-M. Chen. This work was supported in part by the Nanjing University of Science and Technology under Research Start-Up Funds under Grant AE89991/032; in part by the Fundamental Research Funds for the Central Universities under Grant 309181A8804 and Grant 30919011263, in part by the Natural Science Foundation of Jiangsu Province, China under Grant BK20190464, in part by the Jiangsu Planned Projects for Postdoctoral Research Funds under Grant 1003-YBA20012, in part by the Chinese Postdoctoral Science Foundation under Grant 2020M671481, and in part by the National Natural Science Foundation of China under Grant 61527803, Grant 51905242, Grant 61960206010, and Grant 61903193. (Corresponding author: Shang Gao.) Shang Gao and Qing Zhang are with the College of automation engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China (e-mail: [email protected]; [email protected]).

PY - 2021/2

Y1 - 2021/2

N2 - Overpressure measurement is an important approach to evaluate the power of shock wave (SW) monitoring. Traditional wired monitoring systems exhibit the limitations of high-cost, heavyweight, troublesome maintenance, and big-data transmission in SW monitoring. In this article, a new lightweight FPGA-based wireless overpressure node (LFWON) with the resistance to higherature and high-pressure environment for SW monitoring. The proposed LFWON is based on the Spartan-6 XC6SLX9-2TQG144C FPGA circuit, via a serial peripheral interface to the RF transceiver and data bus to the NAND flash chip for data management. To validate the LFWON, experimental tests in terms of dynamic parameters and network quality are performed in a real blast testing with 8-kg trinitrotoluene. This article is conducted to provide new insights into how the antishocking structure and sensing algorithm of wireless sensor node is designed in SW monitoring for acquiring overpressure accurately. The results show that the errors of Δ P(7 m-12m), td(>6 m), and I + (3m-24 m) from proposed LFWON are below 20% in comparison with wired system. In addition, the RSSI value of LFWON should be set above-70 dBm for stable communication quality.

AB - Overpressure measurement is an important approach to evaluate the power of shock wave (SW) monitoring. Traditional wired monitoring systems exhibit the limitations of high-cost, heavyweight, troublesome maintenance, and big-data transmission in SW monitoring. In this article, a new lightweight FPGA-based wireless overpressure node (LFWON) with the resistance to higherature and high-pressure environment for SW monitoring. The proposed LFWON is based on the Spartan-6 XC6SLX9-2TQG144C FPGA circuit, via a serial peripheral interface to the RF transceiver and data bus to the NAND flash chip for data management. To validate the LFWON, experimental tests in terms of dynamic parameters and network quality are performed in a real blast testing with 8-kg trinitrotoluene. This article is conducted to provide new insights into how the antishocking structure and sensing algorithm of wireless sensor node is designed in SW monitoring for acquiring overpressure accurately. The results show that the errors of Δ P(7 m-12m), td(>6 m), and I + (3m-24 m) from proposed LFWON are below 20% in comparison with wired system. In addition, the RSSI value of LFWON should be set above-70 dBm for stable communication quality.

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A Lightweight Wireless Overpressure Node Based Efficient Monitoring for Shock Waves

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Keywords

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