Efficient time synchronization for structural health monitoring using wireless smart sensor networks

Jian Li, Kirill A. Mechitov, Robin E. Kim, B F Spencer

Research output: Contribution to journalArticle

Abstract

Summary Wireless smart sensor networks (WSSNs) have shown great promise in structural health monitoring (SHM), because of their advantages of low cost, higher flexibility, robust data management, and ability to provide better understanding of structural behavior through dense deployment of sensors. However, implementation of wireless SHM systems poses many challenges, one of which is ensuring adequate synchronization of the collected data. This issue arises in WSSNs because each smart sensor in the network having an independent processor with its own local clock, and this clock is not necessarily synchronized with the clocks of other sensors. Moreover, even though the clocks can be accurately synchronized by exchanging time information through beacon messages, the measured data may still be poorly synchronized because of random delays from both software and hardware sources; that is, synchronized clocks do not necessarily yield synchronized sensing. Various algorithms have been proposed to achieve both synchronized clocks and sensing. However, these protocols still lack the desired performance for SHM applications for reasons of extended data collection time, temperature variations resulting in nonlinear clock drift, requirement for prompt response, and so on. In this paper, the unique features and challenges of synchronized sensing for SHM applications are discussed, followed by a numerical investigation of the effect of nonlinear clock drift on data synchronization accuracy. A new synchronized sensing strategy considering nonlinear clock drift compensation is proposed with two different implementations to meet various application requirements. Experimental results show that the proposed time synchronization approach can compensate for temperature effects on clock drift and provide efficient and accurately synchronized sensing (<50 μs maximum error) for SHM, even for long sensing duration.

Original languageEnglish (US)
Pages (from-to)470-486
Number of pages17
JournalStructural Control and Health Monitoring
Volume23
Issue number3
DOIs
StatePublished - Mar 1 2016

Fingerprint

Smart sensors
Structural health monitoring
Sensor networks
Clocks
Synchronization
Sensors
Thermal effects
Information management
Hardware
Network protocols

Keywords

  • nonlinear clock drift
  • structural health monitoring
  • synchronized sensing
  • time synchronization
  • wireless smart sensors

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanics of Materials

Cite this

Efficient time synchronization for structural health monitoring using wireless smart sensor networks. / Li, Jian; Mechitov, Kirill A.; Kim, Robin E.; Spencer, B F.

In: Structural Control and Health Monitoring, Vol. 23, No. 3, 01.03.2016, p. 470-486.

Research output: Contribution to journalArticle

@article{daa34cb5ae3a48c8accc601c91813eef,
title = "Efficient time synchronization for structural health monitoring using wireless smart sensor networks",
abstract = "Summary Wireless smart sensor networks (WSSNs) have shown great promise in structural health monitoring (SHM), because of their advantages of low cost, higher flexibility, robust data management, and ability to provide better understanding of structural behavior through dense deployment of sensors. However, implementation of wireless SHM systems poses many challenges, one of which is ensuring adequate synchronization of the collected data. This issue arises in WSSNs because each smart sensor in the network having an independent processor with its own local clock, and this clock is not necessarily synchronized with the clocks of other sensors. Moreover, even though the clocks can be accurately synchronized by exchanging time information through beacon messages, the measured data may still be poorly synchronized because of random delays from both software and hardware sources; that is, synchronized clocks do not necessarily yield synchronized sensing. Various algorithms have been proposed to achieve both synchronized clocks and sensing. However, these protocols still lack the desired performance for SHM applications for reasons of extended data collection time, temperature variations resulting in nonlinear clock drift, requirement for prompt response, and so on. In this paper, the unique features and challenges of synchronized sensing for SHM applications are discussed, followed by a numerical investigation of the effect of nonlinear clock drift on data synchronization accuracy. A new synchronized sensing strategy considering nonlinear clock drift compensation is proposed with two different implementations to meet various application requirements. Experimental results show that the proposed time synchronization approach can compensate for temperature effects on clock drift and provide efficient and accurately synchronized sensing (<50 μs maximum error) for SHM, even for long sensing duration.",
keywords = "nonlinear clock drift, structural health monitoring, synchronized sensing, time synchronization, wireless smart sensors",
author = "Jian Li and Mechitov, {Kirill A.} and Kim, {Robin E.} and Spencer, {B F}",
year = "2016",
month = "3",
day = "1",
doi = "10.1002/stc.1782",
language = "English (US)",
volume = "23",
pages = "470--486",
journal = "Structural Control and Health Monitoring",
issn = "1545-2255",
publisher = "John Wiley and Sons Ltd",
number = "3",

}

TY - JOUR

T1 - Efficient time synchronization for structural health monitoring using wireless smart sensor networks

AU - Li, Jian

AU - Mechitov, Kirill A.

AU - Kim, Robin E.

AU - Spencer, B F

PY - 2016/3/1

Y1 - 2016/3/1

N2 - Summary Wireless smart sensor networks (WSSNs) have shown great promise in structural health monitoring (SHM), because of their advantages of low cost, higher flexibility, robust data management, and ability to provide better understanding of structural behavior through dense deployment of sensors. However, implementation of wireless SHM systems poses many challenges, one of which is ensuring adequate synchronization of the collected data. This issue arises in WSSNs because each smart sensor in the network having an independent processor with its own local clock, and this clock is not necessarily synchronized with the clocks of other sensors. Moreover, even though the clocks can be accurately synchronized by exchanging time information through beacon messages, the measured data may still be poorly synchronized because of random delays from both software and hardware sources; that is, synchronized clocks do not necessarily yield synchronized sensing. Various algorithms have been proposed to achieve both synchronized clocks and sensing. However, these protocols still lack the desired performance for SHM applications for reasons of extended data collection time, temperature variations resulting in nonlinear clock drift, requirement for prompt response, and so on. In this paper, the unique features and challenges of synchronized sensing for SHM applications are discussed, followed by a numerical investigation of the effect of nonlinear clock drift on data synchronization accuracy. A new synchronized sensing strategy considering nonlinear clock drift compensation is proposed with two different implementations to meet various application requirements. Experimental results show that the proposed time synchronization approach can compensate for temperature effects on clock drift and provide efficient and accurately synchronized sensing (<50 μs maximum error) for SHM, even for long sensing duration.

AB - Summary Wireless smart sensor networks (WSSNs) have shown great promise in structural health monitoring (SHM), because of their advantages of low cost, higher flexibility, robust data management, and ability to provide better understanding of structural behavior through dense deployment of sensors. However, implementation of wireless SHM systems poses many challenges, one of which is ensuring adequate synchronization of the collected data. This issue arises in WSSNs because each smart sensor in the network having an independent processor with its own local clock, and this clock is not necessarily synchronized with the clocks of other sensors. Moreover, even though the clocks can be accurately synchronized by exchanging time information through beacon messages, the measured data may still be poorly synchronized because of random delays from both software and hardware sources; that is, synchronized clocks do not necessarily yield synchronized sensing. Various algorithms have been proposed to achieve both synchronized clocks and sensing. However, these protocols still lack the desired performance for SHM applications for reasons of extended data collection time, temperature variations resulting in nonlinear clock drift, requirement for prompt response, and so on. In this paper, the unique features and challenges of synchronized sensing for SHM applications are discussed, followed by a numerical investigation of the effect of nonlinear clock drift on data synchronization accuracy. A new synchronized sensing strategy considering nonlinear clock drift compensation is proposed with two different implementations to meet various application requirements. Experimental results show that the proposed time synchronization approach can compensate for temperature effects on clock drift and provide efficient and accurately synchronized sensing (<50 μs maximum error) for SHM, even for long sensing duration.

KW - nonlinear clock drift

KW - structural health monitoring

KW - synchronized sensing

KW - time synchronization

KW - wireless smart sensors

UR - http://www.scopus.com/inward/record.url?scp=84956766520&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84956766520&partnerID=8YFLogxK

U2 - 10.1002/stc.1782

DO - 10.1002/stc.1782

M3 - Article

AN - SCOPUS:84956766520

VL - 23

SP - 470

EP - 486

JO - Structural Control and Health Monitoring

JF - Structural Control and Health Monitoring

SN - 1545-2255

IS - 3

ER -