A Wireless Structural Health Monitoring System with Multithreaded
Sensing Devices: Design and Validation
Yang Wang
a
, Jerome P. Lynch
b
, Kincho H. Law *
a
a
Dept. of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305
b
Dept. of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109
* Correspondence Author:
Kincho H. Law
Department of Civil and Environmental Engineering
Stanford University
Stanford, CA 94305-4020
USA
Email: law@stanford.edu
Tel: 1-650-725-3154
Fax: 1-650-725-9755
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ABSTRACT
Structural Health Monitoring (SHM) has become an important research problem which has the potential to
monitor and ensure the performance and safety of civil structures. Traditional wire-based SHM systems
require significant time and cost for cable installation. With the recent advances in wireless communication
technology, wireless SHM systems have emerged as a promising alternative solution for rapid, accurate and
low-cost structural monitoring. This paper presents a newly designed integrated wireless monitoring system
that supports real-time data acquisition from multiple wireless sensing units. The selected wireless
transceiver consumes relatively low power and supports long-distance peer-to-peer communication. In
addition to hardware, embedded multithreaded software is also designed as an integral component of the
proposed wireless monitoring system. A direct result of the multithreaded software paradigm is a wireless
sensing unit capable of simultaneous data collection, data interrogation and wireless transmission. A reliable
data communication protocol is designed and implemented, enabling robust real-time and near-synchronized
data acquisition from multiple wireless sensing units. An integrated prototype system has been fabricated,
assembled, and validated in both laboratory tests and a large-scale field test conducted upon the Geumdang
Bridge in Icheon, South Korea.
Keywords: Structural monitoring, wireless sensing, sensor networks, data acquisition, on-board data
processing, vibration tests.
1. INTRODUCTION
The safety and reliability of civil infrastructure systems are essential for supporting the economic vitality of
our society. As civil structures are continuously subjected to loads and other environmental effects, the
structural condition of many civil infrastructures in the U.S. is deteriorating. For example, more than half of
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the bridges in the United States were built before 1940’s, and nearly 42% of them were reported to be
structurally deficient and below established safety standards (Stallings et al., 2000). To protect the public
from unsafe bridge structures, current U.S. federal requirements necessitate local transportation authorities to
visually inspect the entire inventory of well over 580,000 highway bridges biannually (Chase, 2001). An
inherent drawback of visual inspections is that they only consider damage that is visible on the surface of the
structure; damage located below the surface often remains elusive to the inspectors. Furthermore, bridge
inspections can be highly subjective. For example, a recent study by the U.S. Federal Highway
Administration (FHWA) quantified the reliability of visual inspections with wide variability discovered in
the condition ratings assigned by trained inspectors to a bridge intentionally damaged as part of the study
(Moore et al., 2001). With visual inspections both costly and labor intensive, low cost sensing systems that
can quantitatively assess the integrity and remaining life of a structure are needed (Liu et al., 2003).
As a complimentary approach and promising alternative to visual structural inspections, structural health
monitoring (SHM) systems have been proposed to predict, identify, and locate the onset of structural damage
(Sohn et al. 2001, Chang et al. 2003, Elgamal et al. 2003). SHM systems employ smart sensor technologies
to assist in identifying subtle structural abnormality based on measured structural response parameters
(Farrar et al. 2003, Spencer et al. 2004). Various types of structural sensors, including accelerometers,
displacement transducers, strain gages, and thermometers, can be deployed to provide valuable real-time
information about the behavior of a structure or environmental conditions. A necessary element of a SHM
system is the data acquisition (DAQ) system used to collect sensor measurements and to store the data in a
centralized location. Current commercial DAQ systems designed for permanent installation or for short-term
vibration tests employ cables to directly transmit sensor data to the central data repository. By running
cables between sensors and the data server, traditional DAQ systems suffer from high installation costs in
terms of both time and money. Installing extensive lengths of cables can consume over 75% of the total
SHM system installation time (Straser and Kiremidjian, 1998). In the U.S., the cost of installing a typical
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structural monitoring system in buildings can exceed a few thousand dollars per sensing channel (Celebi,
2002).
Recent developments in the fields of microelectromechanical systems (MEMS) and wireless communications
have introduced new opportunities to reduce the installation costs of structural monitoring systems (Min et
al. 2001, Warneke et al. 2002, Lynch et al. 2004b). MEMS technology has led to the development of
sensors that are low cost, low power, compact, and easy to install; while wireless technology allows for
transmitting sensor measurements without the need for cables. The use of wireless communications as a
means for eradicating cables within a structural monitoring system was illustrated by Straser and Kiremidjian
(1998). Their work demonstrated both the feasibility and the cost-effectiveness of wireless SHM systems.
With respect to the architectural design of wireless SHM systems, Kottapalli et al. (2003) proposed a two-
tiered wireless sensor network topology that especially addresses the power consumption, data rate, and
communication range limitations of current wireless monitoring systems. Lynch et al. (2004a) explored
further the concept of embedding damage identification algorithms directly into wireless sensing units,
harnessing the computational resources of these devices to execute data interrogation algorithms. The
embedment of engineering algorithms within the wireless sensing units serves as a means of reducing power-
consuming wireless communications, and thereby largely improves the scalability of the system. Many other
research efforts in developing wireless sensing platforms for structural health monitoring have been reported
(Hill 2003, Kling 2003, Arms et al. 2004, Callaway 2004, Culler et al. 2004, Glaser 2004, Mastroleon et al.
2004, Ou et al. 2004, Shinozuka et al. 2004, Spencer et al. 2004).
Compared to traditional wire-based systems, wireless structural monitoring systems have a unique set of
technical challenges (Wang et al., 2005b). First, wireless sensing units will most likely employ batteries that
have a limited supply of energy for the near future. Batteries are probable in the short-term because current
power harvesting techniques cannot yet provide a reliable, convenient, and low-cost solution for powering
typical wireless structural sensors (Churchill et al. 2003, Roundy 2003, Sodano et al. 2004). In terms of
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power consumption, wireless transceivers often consume the greatest amount of energy than any of the other
components in the wireless sensor design (Lynch et al., 2004a). Local data processing targeted to balance
data transmission and energy consumption is desirable. Second, the transmission of data in a wireless
network is inherently less reliable than in cable-based networks; reliability decreases as the communication
range becomes farther. Third, the limited amount of wireless bandwidth usually impedes high-speed real-
time data collection from multiple sensors. Fourth, time delays encountered during data transmission
between different wireless sensing units due to sensor blockage or clock imprecision needs to be thoroughly
considered (Lei et al., 2003).
The wireless structural monitoring system proposed in this paper attempts to address some of the technical
challenges described above. The design of this new system was especially oriented for large-scale and low-
power wireless SHM applications in civil structures (Wang et al., 2005a). Some of the main features of this
new wireless SHM system are: 1) low power consumption while achieving long communication ranges with
robust communication protocols for reliable data acquisition, 2) accurate synchronized wireless data
collection from multiple analog sensors at a reasonable sampling rate suitable for civil structural applications,
3) high-precision analog-to-digital conversion, 4) considerable local data processing capability at the wireless
sensing units to reduce energy consumption and to enhance system scalability, and 5) accommodation of
peer-to-peer communication among wireless sensing units for collaborative decentralized data analysis. An
integrated wireless SHM system has been developed, fabricated and assembled. Furthermore, the SHM
system has undergone laboratory and large-scale field tests to validate the system performance within the
complex environment posed by civil structures. The field tests were conducted at Geumdang Bridge in
Icheon, South Korea by simultaneously employing 14 wireless sensing units on the bridge for continuous
real-time data acquisition using a single data server (Lynch et al., 2005).
This paper presents in detail the hardware organization of this new wireless SHM system. Major circuit
components of the wireless sensing units are introduced, with key hardware performance features of the