ABSTRACT
Among all civil
engineering structures, bridges & tunnels are two of the leading types that
should be monitored by sensors due to their critical fatigue and creep
behavior. Especially natural events such as earthquakes, floods, storms
increase the importance of monitoring. A number of different types of instruments
and sensors should be combined in health monitoring of railway/highway bridges,
tunnels, tube crossings and subways. Although customization has a big
importance in a specific health monitoring instrumentation project of a bridge
or tunnel, accelerometers, strain/crack gauges, tilt, wind and temperature
sensors are the most generally preferred sensors.
Accelerometers are
used for operational modal analysis, which reveals 2 important issues about the
health of the structure. First, the real modal frequencies measured from the
real structure shows how close it behaves in parallel with its design project.
Secondly whether this characteristic behavior changes in time or after a
specific event indicating a potential damage in the structure.
Similarly,
strain/crack gauges provide direct information about the deformations along the
bridge. This is important for realizing excessive unexpected deformations and
locating the neutral axis. Furthermore strain gauges directly monitors the dead
loads along the structure measured in specific cross-sections in a tunnel.
TESTBOX™ / eQUAKE™
series DAQs provide different solution opportunities for different projects
needs. In this study key, parameters affecting an instrumentation project are
explained in detail. Furthermore, wireless/wired monitoring, different sensor
sensitivities, real-time or short-term monitoring are discussed. The discussion
is extended to combining dynamic and static measurements. A robust alternative
from fiber optic sensors are also included in the study strengthening the
solution. In this way, a turn-key and integrated approach for real-time
structural health monitoring of bridges & tunnels is presented.
Keywords Real-Time Structural Health
Monitoring • Bridge Monitoring • Operational Modal Analysis • Wireless GPS
Synchronization • Ultra Low Noise Accelerometer • Strain Gauge • Simultaneous
Sampling • 24 Bit Data Acquisition
A Real-Time Instrumentation Approach for Structural Health
Monitoring of Bridges
S. Dinçer1, E. Aydın2 and H. Gencer3
ABSTRACT
Bridges &
tunnels are the two leading types of structures that should be monitored by
sensors due to their critical fatigue and creep behavior. A number of different
types of instruments and sensors should be combined in health monitoring of
railway/highway bridges, tunnels, tube crossings and subways. Accelerometers, strain/crack
gauges, tilt, wind and temperature sensors are the most generally preferred
sensors. Accelerometers are used for operational modal analysis, which reveals
2 important issues about the health of the structure. First, the real modal
frequencies measured from the real structure shows how close it behaves in
parallel with its design project. Secondly whether this characteristic behavior
changes in time or after a specific event indicating a potential damage in the
structure. Similarly, strain/crack gauges provide direct information about the
deformations along the bridge. This is important for realizing excessive
unexpected deformations and locating the neutral axis. Furthermore strain
gauges directly monitors the dead loads along the structure measured in
specific cross-sections in a tunnel. TESTBOX™ / eQUAKE™ series DAQs provide
different solution opportunities for different project needs. 7/24 real-time
monitoring, wireless/wired monitoring opportunities, different sensor
sensitivities are discussed in this study. The discussion is extended to
combining dynamic and static measurements. A robust alternative from fiber optic
sensors are also suggested in the study strengthening the solution. In this
way, a well-combined (dynamic-static) and integrated approach for real-time
structural health monitoring of bridges & tunnels is proposed.
Keywords Real-Time Structural Health Monitoring • Bridge Monitoring
• Operational Modal Analysis • Wireless GPS Synchronization • Ultra Low Noise Accelerometer
• Strain Gauge • Simultaneous Sampling • 24 Bit Data Acquisition
Introduction
History of civil engineering is full of examples of sudden and
unexpected failures of bridges and tunnels. Only two examples of this
disastrous collapses are shown in Fig. 1. One is from 1940, Tacoma Narrows
Bridge collapse (on the left), and the other one is a very recent disaster in
Çaycuma, Turkey, in year 2012(on the right). Tacoma Bridge collapsed less than
1 year after its construction, and the bridge in Çaycuma was 61 years old when
it collapsed. The reason for the collapse of these bridges are still being
discussed. At least 3 theories are still available for the collapse of Tacoma
Bridge, and neither one has been agreed on yet.
Bridges are
generally designed to carry vehicle traffic. Due to this natural design
philosophy, they are exposed to intensive and continuous dynamic loading during
their lifetime. Naturally, a fatigue behavior should generally be expected for
a bridge. Nakazawa et al. conducted an experimental study on 2 aged reinforced
concrete bridges, and showed that aging caused reduction of rigidity for these
bridges.[1] Similarly tunnels are exposed to huge static loads during their
lifetime, again due to their design nature. For tunnels creep behavior may be
considered as a more common cause of failure.
Figure 1. Two
examples of disastrous bridge collapses. Right-Çaycuma, Turkey, 2012.
Left-Tacoma Narrows Bridge, 1940.
Structural health monitoring of bridges and tunnels always attracted
attention of engineers and administrators of these structures. Since these
structures always includes a potential risk of sudden failure, monitoring them
is important for providing the necessary time for taking precautions and not
facing the unexpected disasters. A second important result of monitoring is to
get real data to understand the phenomenon and conduct research studies and
modify future designs accordingly. Two detailed and well categorized studies on
this area are, Study and Application of Modern Bridge Monitoring Techniques [2]
and Lessons Learned in Structural Health Monitoring of Bridges Using Advanced
Sensor Technology[3].
In parallel with
the technological developments, it is possible to apply much precise sensors
and systems for a considerably less cost. Developments in MEMS
(microelectromechanical systems) technology, digitizers, data transfer lines
and options, and fiber optic sensor technology are all the main components of
these more reachable and more efficient monitoring possibilities. This
situation causes the electronics and instrumentation technology to intersect
with Civil Engineering discipline. At this point of intersection, designing a
correct monitoring system by selecting the right instruments among a big batch
of alternatives becomes more important.
The scope of this
study is focusing on the instrumentation part of the structural health
monitoring for bridges and tunnels, rather than discussing the results of the
analysis from structural engineering point of view.
7/24 Real Time Monitoring
All the instrumentation proposed in this study is based on 7/24 real
time monitoring. Fig. 2 shows the general flowchart of the suggested approach. Suitable
types and numbers of the sensors and should be decided individually regarding
the design of the bridge and the main target of the monitoring project.
However, two main types of sensors are used in general in each monitoring
project, static and dynamic. The instrumentation approach in this study
suggests an Ethernet compatible data line for the dynamic measurements and
fiber optic sensor line for the static measurements. The reasons and details of
this suggestion is given at the following sections.
 |
| Figure 2. The general diagram of the suggested 7/24 real-time instrumentation approach. |
Both static and dynamic data lines are connected to the main data
acquisition center at the bridge site. This data center works on 7/24- 365 days
a year principle and is at least capable of acquiring all the data together,
synchronizing and transferring it to any remote location over an internet
gateway. The data center has the capability of recording the data locally,
based on preset trigger conditions, as well.
All the data
incoming from the sensors located at the bridge is monitored continuously at
one or more than one remote locations. A real-time and continuous, software
based analysis is carried out at the remote monitoring center. This software
based real-time analysis works as a decision support system for the
administrators and engineers at charge. Warning messages are reported to the
bridge administration immediately. More than this, periodical structural health
reports are prepared and presented based on the mid/long-term changes of the
structural behavior. It is also possible to prepare structural health reports
after events such as major, earthquakes, storms or floods.
A real-time
analysis and reaction module is optional for the bridge site, which should be
planned with great attention and care. If this module is installed at the site,
a real-time and continuous analysis is carried out at the bridge site. Any
possible instabilities resulting from this analysis is reported to the bridge
administration immediately. Another function of this module is starting
different levels of preset alarm and reaction scenarios at the bridge. The
possible scenarios maybe preventing further approach of the traffic to the
bridge, or starting audio visual warnings for the people, to inform them to
abandon the bridge shortly. Certainly the scenarios should be decided by the
bridge administration carefully, and a detailed study should be carried out for
linking the module outputs to the automation system of the bridge.
Dynamic Instrumentation and Monitoring
According to the instrumentation approach proposed in this study
both dynamic and static measurements should be taken from the bridge for a
healthy structural monitoring process. Dynamic measurements are primarily based
on accelerometers. The main purpose is monitoring the dynamic behavior of the
bridge. In this way it is possible to carry out an operational modal analysis
study of the bridge. Although a detailed modal analysis study should be carried
out as a post process, it is possible to analyze some important values such as
natural frequency and vertical displacements at real time, automatically, by
the online analysis software. A solid example of post process modal analysis
and damage detection study has been carried out by Brincker et al. on Z24
Highway Bridge [4]. ARTEMIS™ Modal Analysis tool has been used at this study.
It is possible to find many similar modal analysis studies for bridges.
Accelerometer Selection (for Operational Modal Analysis)
Before discussing the selection criteria for the correct
accelerometer, ambient vibration vs. forced vibration testing and modal
analysis should be explained. In forced vibration testing a well-defined action
is applied on the structure. This force is generally comparably in higher
amplitudes and the reactions can easily be measured even by low-resolution
accelerometers. However, in 7/24 monitoring it is not possible to apply
well-defined forces on the structure continuously. Instead a simpler
methodology is preferred. Operational modal analysis under ambient vibration.
The structures are continuously excited by ambient vibrations, such as wind, or
little seismic movements. For a structure like bridge, the traffic load itself
(such as a train or truck passing through) creates a higher amplitude
excitation on the structure.
This ambient
vibration is assumed to be very close to a white noise. A typical and ideal
white noise in presented in Fig. 3. As it can be seen from the figure although
the time domain do not reveal much about the characteristic of the excitation, no
specific peak frequency is observed in the frequency domain, a Gaussian
distribution can be followed at the histogram. As the excitation is assumed to
be close to a white noise, in ambient vibration tests, the modal analysis is
carried out depending only on the measured reactions of the structure and
therefore it is called an output-only modal analysis, which simplifies the
measurement stage.
 |
| Figure 3. Operational modal analysis (output only), white noise excitation. |
Anyhow, this simplification is only possible with the correct choice
of both the accelerometers and the digitizers (sometimes also called as data
acquisition systems).
If a dynamic
analysis will be carried out under ambient vibration, a general rule of thumb
is selecting 24-bit, simultaneous sampling digitizers which at least have 120
dB dynamic range combined with ultra-low noise accelerometers which at most
have ±3g input range. However, even with these guidelines in hand, the
selection sometimes can still be confusing.
For the
accelerometers, good matches can be listed as FBAs(force balance accelerometers),
ultra low noise MEMS(microelectromechanical sensors), METs(molecular electronic
transducers) and IEPE type piezo accelerometers.
-Conventional
FBAs: best for long period signals, close to DC.
-MEMS/METs: also
including force-feedback, best for 0.1 to 100 Hz signals.
-IEPE type
piezo-electric: best for high frequency measurement
A cost -
performance chart of low-noise, high precision, low frequency accelerometers
are presented in Fig. 4. In general, correctly selected MEMS/MET sensors
provide enough performance at considerably lower costs for ambient vibration
studies. These types of sensors are often used in dynamic monitoring of
bridges. A monitoring study conducted on Golden Gate Bridge is one of the solid
examples for the use of MEMS sensors in bridge monitoring. [5]
 |
| Figure 4. Cost-performance chart of high precision, low frequency accelerometers. |
The RMS noise density may be the most important parameter at the
selection of the correct accelerometer. A value lower than 10µg/√Hz down to 300nano-g/√Hz
is generally acceptable. However, this is still a large range for the
selection. Roughly it is possible to say 300-500 nano-g/√Hz is essential for
relatively rigid structures such as buildings. Meanwhile, about 5µg/√Hz is
generally acceptable for a bridge.
Digitizer Selection
In this study, a series of combined accelerometers and digitizers
are preferred for the proposed solution. These combined devices should include
5µg/√Hz or 150nano-g/√Hz accelerometers inside, and produce a direct digital
output that can easily be transferred digitally over ethernet line or any other
data line. 100-200 Hz sampling speed per channel will be enough to analyze
lower structural frequencies.
Full wireless
data transfer will be a potential problem cause for a permanent monitoring
system on a bridge, due to communication failures. On the other hand, using one
central multi-channel digitizer, and connecting the accelerometers to the
device with analog cables will create 2 potential problems. First one is the
electrical noise and signal loss on analog cables especially in long span
bridges. And the second one is the difficulties in and cost of analog cabling
compared to digital cabling. So, the third way, which is, digitizing the analog
data locally at measuring locations and transferring the digital data with
cables seems to be the best alternative.
The preferred devices
should also have local storage capability for temporary communication failures.
The most important feature of this solution is that, the digitizers should have
a synchronization method between them in order to provide suitable data for the
modal analysis, although located separately from each other.
TESTBOX™/e-QUAKE™
series devices are one of the best fits for the dynamic part of the health
monitoring instrumentation of bridges. This series also provide different
solution opportunities for different monitoring projects. TESTBOX™/e-QUAKE™
series have already been used in the health assessment of a number of steel and
concrete bridges.[6],[7],[8],[9].
GPS Based Wireless Solutions
As stated in the previous section, the digitizers should have a
synchronization method between them in order to provide suitable data for the
modal analysis, although located separately from each other. One way of
providing this synchronization is using a GPS module on each digitizer. In this
way, all the digitizers will perform the analog to digital conversions being
synchronized at 1 micro-second resolution of UTC. The special solution of
TESTBOX™/e-QUAKE™ series devices for synchronization of separate devices is
presented in Fig. 5. One very important specialty in this solution is that, the
satellite connected timing signal directly drives the analog to digital
convertors, providing the synchronization at the most precise level. As it is
impossible to start all the independent digitizers at the same time, the time
gap between the devices is corrected by adding the correct time stamp to each
individual data.
 |
| Figure 5. GPS based wireless synchronization method |
Quasi -Static Instrumentation and Monitoring
As well as dynamic monitoring, quasi-static monitoring -primarily based
on strain gauges- provide a lot of information regarding the structural health
and integrity of the structure. This static instrumentation part is essential
for measuring directly the deformations, the position of the neutral axis and
sometimes the tilt movement of the structure.
In this study a
fiber optic solution is suggested for the quasi-static part. The suggested
fiber-optic solution is based on fiber bragg grating(FBG) technology.[10] The
main advantages of this technology can be summarized as high multiplexing
capability, long-distance transmission, EMI/RFI immunity, electric isolation,
signal integrity and long-term stability. This technology especially fits best
for the monitoring of long distance spans such as bridges and tunnels.
Another advantage
of fiber-optic technology is the wide range of opportunities for the
installation of the strain gauges. FBG strain gages are designed to be bonded,
spot welded to structures and components (metallic, concrete, etc.) or directly
cast into concrete wet mix. These sensors are fiber optic versions of the
conventional resistance strain gages but completely passive, offering inherent
insensitivity to environmental induced drift. The alternatives are presented in
Fig. 6.
 |
| Figure 6. Different versions of Fiber Bragg Grating strain gauges. |
A good practice of health monitoring on a steel railway bridge using
fiber bragg grating weldable strain gauges is presented by Barbosa et al. [11]
Well-Combined
(Dynamic-Static) Integrated Monitoring Approach
A successful and efficient health monitoring instrumentation on
bridges can be achieved by a good combination of dynamic and static systems.
Especially in long span bridges one of the best and most robust way of static
monitoring is using fiber bragg grating based strain gauges and tilt sensors.
On the other hand
dynamic measurements should be taken by force-balance, MEMS or MET
accelerometers. When the cost performance ratio is considered, MEMS
accelerometers are generally the best fitting solution for bridges. However
carrying all the analog outputs to a central data acquisition unit is not
feasible for long spans. Instead a distributed approach should be followed. The
solution of integrated digitizers and accelerometers are considered as the
better alternative. In this way it would be possible to distribute the
measurements and only transfer the digital data to the central acquisition
unit. Certainly the vibration data must be synchronized for modal analysis. GPS
based distributed synchronization solves this problem.
The central data
acquisition unit should support both fiber bragg grating based static sensors
and acceleration based dynamic part. The software should be capable of integrating
these two different technologies successfully. Both static and dynamic data
should be transferred to remote locations in a well-organized manner. Real-time
calculations and analysis should be carried out both separately and sometimes
combining the static and dynamic measurements together. Trigger functions in
some cases must support the outcomes of both static and dynamic readings.
Monitoring of Tunnels
For tunnels, it is possible to monitor deformation and convergence
by fiber optic sensors. A solid case study for this solution was carried out by
Barbosa et al. in 2009 for Rossio train tunnel in Lisbon, Portugal[12]. The
monitoring system was a complete solution that comprises measurements of strain
and temperature with more than 850 fiber Bragg grating sensors, data
acquisition, processing, storage and easy access through a web platform. The
applied sensing technology has several advantages such as fiber Bragg sensors
being immune to electrical interferences and suited to harsh environments. The
used method for convergence monitoring (MEMCOT) makes it possible to determine
tunnel convergences based on strain measurements around the tunnel contour. An
optoelectronic measurement unit and optic switch are deployed at the entrance
of the tunnel and remotely connected to a server that saves and displays
information to authorized users in web interface. Strain gauge placements and
the monitoring system installed at the tunnel, is presented in Fig.7.
 |
| Figure 7. Rossio railway tunnel monitoring by fiber optic strain sensors, strain gauges placed in tunnel cross-sections(right), monitoring system installed at the tunnel(right) |
Conclusions
The structural health monitoring instrumentation solutions for
bridges and tunnels in parallel with recent technological developments are
discussed in detail in this study. For tunnels a completely fiber-optic based
solution is possible for to monitor deformation and convergence.
A well-defined
combined approach is suggested for the monitoring of bridges. In this approach
MEMS or MET based accelerometers are used for dynamic measurements, and fiber
optic strain gauges and tilt sensors are used for static measurements. There
will be no problem for connection of fiber optic sensors to the central
acquisition unit with fiber optic cable. However, for the dynamic part carrying
all the analog outputs to a central data acquisition unit is not feasible for
long spans. Instead a distributed approach should be followed. The solution of
integrated digitizers and accelerometers are considered as the better alternative.
In this way it would be possible to distribute the measurements and only
transfer the digital data to the central acquisition unit. Certainly the
vibration data must be synchronized for modal analysis. GPS based distributed
synchronization solves this problem. A 24-bit, GPS enabled digitizer, including
a ±2-3 g range MEMS accelerometer which has a noise density figure of
5-10µg/√Hz should be acceptable. Two different data lines
are considered along the span of the bridge. One fiber optic line for fiber optic
sensors, second ethernet compatible line for the digital data transfer of
dynamic acceleration signals. The central data acquisition unit should support
both fiber optic static sensors and acceleration based dynamic part. The
software should be capable of integrating these two different technologies
successfully.
References
1. Takao Nakazawa,
T., Imai, F., Shinnishi, N., Edamoto, H., Zhang, R. Dynamic Assesment of the
Reduction of Rigidity of Aged RC Bridges. Proceedings of the Twelfth World
Conference on Earthquake Engineering 2000; 0734
2. González, I., Study
and Application of Modern Bridge Monitoring Techniques. M.Sc. Thesis, Department
of Civil and Architectural Engineering, the division of Structural Engineering
and Bridges, at KTH Royal Institute of Technology in Stockholm 2011
3. Enckell, M.,
Lessons Learned in Structural Health Monitoring of Bridges Using Advanced
Sensor Technology. Ph.D. Thesis, Division of Structural Engineering and
Bridges, Department of Civil and Architectural Engineering at the Royal
Institute of Technology (KTH) 2011
4. Brincker, R.,
Andersen, P., Cantieni, R., Identification and Level 1 Damage Detection of the
Z24 Highway Bridge by Frequency Domain Decomposition, Experimental Techniques
2001; 25 (6): 51-57
5. Kim, S., Wireless
Sensor Networks for Structural Health Monitoring. M.Sc. Thesis, Department of
Electrical Engineering and Computer Sciences, University of California at
Berkeley 2005
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