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. 2018 Jan 17;18(1):262.
doi: 10.3390/s18010262.

Development of a High-Sensitivity Wireless Accelerometer for Structural Health Monitoring

Li Zhu  1 , Yuguang Fu  2 , Raymond Chow  3 , Billie F Spencer  4 , Jong Woong Park  5 , Kirill Mechitov  6
Affiliations

Development of a High-Sensitivity Wireless Accelerometer for Structural Health Monitoring

Li Zhu et al. Sensors (Basel). .

Abstract

Structural health monitoring (SHM) is playing an increasingly important role in ensuring the safety of structures. A shift of SHM research away from traditional wired methods toward the use of wireless smart sensors (WSS) has been motivated by the attractive features of wireless smart sensor networks (WSSN). The progress achieved in Micro Electro-Mechanical System (MEMS) technologies and wireless data transmission, has extended the effectiveness and range of applicability of WSSNs. One of the most common sensors employed in SHM strategies is the accelerometer; however, most accelerometers in WSS nodes have inadequate resolution for measurement of the typical accelerations found in many SHM applications. In this study, a high-resolution and low-noise tri-axial digital MEMS accelerometer is incorporated in a next-generation WSS platform, the Xnode. In addition to meeting the acceleration sensing demands of large-scale civil infrastructure applications, this new WSS node provides powerful hardware and a robust software framework to enable edge computing that can deliver actionable information. Hardware and software integration challenges are presented, and the associate resolutions are discussed. The performance of the wireless accelerometer is demonstrated experimentally through comparison with high-sensitivity wired accelerometers. This new high-sensitivity wireless accelerometer will extend the use of WSSN to a broader class of SHM applications.

Keywords: high-sensitivity accelerometer; structural health monitoring; wireless smart sensor.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Lateral acceleration response at the midspan of the deck on the Xihoumen Bridge in China [5].
Figure 2
Figure 2
Xnode Smart Sensor: (a) 3-board stack; (b) Enclosure.
Figure 3
Figure 3
RemoteSensing application structure and its implementation in FreeRTOS.
Figure 4
Figure 4
M-A351 accelerometer.
Figure 5
Figure 5
Design concept of high-sensitivity sensor board.
Figure 6
Figure 6
PCB design of high-sensitivity sensor board. (a) Top side; (b) Bottom side.
Figure 7
Figure 7
Flowchart of driver of M-A351AS [27].
Figure 8
Figure 8
Shaking table test.
Figure 9
Figure 9
Shaking table test results: (a) time history data (b) PSD data (c) zoomed view of time history data (d) zoomed view of low-frequency PSD data.
Figure 10
Figure 10
Ambient vibration test in basement.
Figure 11
Figure 11
Test results in the basement: (a) time history data (b) PSD data (c) zoomed view of time history data (d) zoomed view of low-frequency PSD data.
Figure 12
Figure 12
Ambient vibration test on country road.
Figure 13
Figure 13
Test results on country road: (a) time history data (b) PSD data (c) zoomed view of time history data (d) zoomed view of low-frequency PSD data.
Figure 14
Figure 14
Ambient vibration test in an optical table.
Figure 15
Figure 15
Test results on an optical table: (a) time history data (b) PSD data (c) zoomed view of time history data (d) zoomed view of low-frequency PSD data.
Figure 15
Figure 15
Test results on an optical table: (a) time history data (b) PSD data (c) zoomed view of time history data (d) zoomed view of low-frequency PSD data.
See this image and copyright information in PMC

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