Advancements in sensing technology have improved the practice of structural health monitoring in different aspects. One of the distinguished developments introduced to the monitoring systems is deployment of wireless technology for data communication in a sensing network. While researchers have shown the effective role of wireless sensor networks in improving the affordability of structural monitoring systems, their possible impact on the reliability and accuracy of the results is still a research question. Some challenges in the design of wireless sensor units, such as the trade-off between the functionality and the power consumption, and also attempts for minimizing the cost, have caused limitations in their architecture which do not necessarily exist in the design of wired systems. On the other hand, depending on the subsequent application of the results of sensing and monitoring, the accuracy of measurements and the level of uncertainty in results can be very important. Therefore, it is necessary to carefully investigate the impact of sensor quality on monitoring results. As an effort towards understanding the effects of sensor quality on the results of structural monitoring, this paper presents and validates a metric, called Physical Contribution Ratio (PCR), which can be used to investigate the influence of measurement noise on modal parameter identification. This parameter in applied for quantification of measurement noise effects on the quality of modal identification of a steel bridge structure. Bridge’s vibration is measured through use of wired and wireless sensors with different sensing qualities and the obtained results are compared through the use of the developed metric.
Wireless sensor network (WSN) is recently emerged as a powerful tool in the structural health monitoring (SHM). Due
to the limitations of wireless channel capacity and the heavy data traffic, the control on the network is usually not real
time. On the other hand, many SHM applications require quick response when unexpected events, such as earthquake,
happen. Realizing the need to have an agile monitoring system, an approach, called sandwich node, was proposed.
Sandwich is a design of complex sensor node where two Imote2 nodes are connected with each other to enhance the
capabilities of the sensing units. The extra channel and processing power, added into the nodes, enable agile responses of
the sensing network, particularly in interrupting the network and altering the undergoing tasks for burst events. This
paper presents the design of a testbed for examination of the performance of wireless sandwich nodes in a network. The
designed elements of the network are the software architecture of remote and local nodes, and the triggering strategies
for coordinating the sensing units. The performance of the designed network is evaluated through its implementation in a
monitoring test in the laboratory. For both original Imote2 and the sandwich node, the response time is estimated. The
results show that the sandwich node is an efficient solution to the collision issue in existing interrupt approaches and the
latency in dense wireless sensor networks.
Over the past several years, wireless network systems and sensing technologies have been developed significantly. This
has resulted in the broad application of wireless sensor networks (WSNs) in many engineering fields and in particular
structural health monitoring (SHM). The movement of traditional SHM toward the new generation of SHM, which
utilizes WSNs, relies on the advantages of this new approach such as relatively low costs, ease of implementation and
the capability of onboard data processing and management. In the particular case of long span bridge monitoring, a WSN
should be capable of transmitting commands and measurement data over long network geometry in a reliable manner.
While using single-hop data transmission in such geometry requires a long radio range and consequently a high level of
power supply, multi-hop communication may offer an effective and reliable way for data transmissions across the
network. Using a multi-hop communication protocol, the network relays data from a remote node to the base station via
intermediary nodes. We have proposed a data-transmission pipelining algorithm to enable an effective use of the
available bandwidth and minimize the energy consumption and the delay performance by the multi-hop communication
protocol. This paper focuses on the implementation aspect of the pipelining algorithm on Imote2 platforms for SHM
applications, describes its interaction with underlying routing protocols, and presents the solutions to various
implementation issues of the proposed pipelining algorithm. Finally, the performance of the algorithm is evaluated based
on the results of an experimental implementation.
There has been a rapid advancement in wireless sensor network (WSN) technology in the past decade and its application
in structural monitoring has been the focus of several research projects. The evaluation of the newly developed hardware
platform and software system is an important aspect of such research efforts. Although much of this evaluation is done
in the laboratories and using generic signal processing techniques, it is important to validate the system for its intended
application as well. In this paper the performance of a newly developed accelerometer sensor board is evaluated by using
the data from a beam-column connection specimen with a local damage detection algorithm. The sensor board is a part
of a wireless node that consists of the Imote2 control/communication unit and an advanced antenna for improved
connectivity. A scaled specimen of a steel beam-column connection is constructed in ATLSS center at Lehigh University
and densely instrumented by synchronized networked systems of both traditional piezoelectric and wireless sensors. The
column ends of the test specimen have fixed connections, and the beam cantilevers from the centerline of the column.
The specimen is subjected to harmonic excitations in several test runs and its acceleration response is collected by both
systems. The collected data is then used to estimate two sets of system influence coefficients with the wired one as the
reference baseline. The performance of the WSN is evaluated by comparing the quality of the influence coefficients and
the rate of convergence of the estimated parameters.
Application of wireless sensor network (WSN) for structural health monitoring (SHM), is becoming
widespread due to its implementation ease and economic advantage over traditional sensor
networks. Beside advantages that have made wireless network preferable, there are some concerns
regarding their performance in some applications. In long-span Bridge monitoring the need to transfer data
over long distance causes some challenges in design of WSN platforms. Due to the geometry of
bridge structures, using multi-hop data transfer between remote nodes and base station is essential. This
paper focuses on the performances of pipelining algorithms. We summarize several prevent pipelining
approaches, discuss their performances, and propose a new pipelining algorithm, which gives consideration
to both boosting of channel usage and the simplicity in deployment.