Self-Diagnosing Structures
by David Pescovitz
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According to graduate student John-Michael Wong, "although a lot of the fundamentals of this project are based in theory, this system could someday help people in making decisions about the structures that they work and live in."
(David Pescovitz photo)
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When the "check
engine" light on your automobile's dashboard flashes on, you
know immediately that the car may not be safe to drive. Now imagine
that your office building was outfitted with similar technology. A
quick look at the building's Web site could notify the property manager
to call in an engineer because a support column is in need of a check-up.
Or a display screen mounted on the front door might warn occupants
about to re-enter the building after an earthquake that the entire
structure is on the verge of collapsing.
John-Michael
Wong, a graduate student in UC Berkeley's Department of Civil
and Environmental Engineering,
is designing precisely this
kind of "dashboard for buildings." The project is sponsored
by the CUREE-Kajima Research Program, a joint venture between
the Consortium of Universities for Research in Earthquake Engineering
(CUREE) and Japanese construction firm Kajima Corporation.
Formally
called a "Framework for Integration and Visualization
of Structural State Data," the system analyzes the raw data
from wireless sensors installed in a structure and translates
those calculations
into easy-to-interpret graphical displays.
"With our
system, you can display data on very different levels," says
Wong, a student of CEE professor Bozidar Stojadinovic. "A
normal user might only be interested in the overall condition
of the building,
while an engineer needs access to more detailed data and analysis
output."
This image links to a Web-based demonstration of a display that a property manager or structural engineer would refer to for information about a building's structural health. (courtesy the researchers)
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The data for
the system comes from a network of tiny wireless sensors installed
in key structural locations
around a building.
The devices
can be outfitted with accelerometers to detect vibration
or strain gauges that measure the bending or twisting of a beam,
for example.
Those numbers are then wirelessly transmitted to a central
computer for processing. Wong's collaborator on the project,
graduate
student Jan Goethals, has spent several years developing
the
structural
sensing system with CEE professor Steven Glaser and others.
The problem though,
Wong says, is that the sensors' flood of data is too raw for efficient
analysis, even by an experienced
structural
engineer.
"A stream
of numbers isn't useful to anyone," Wong says.
To classify
and analyze the data so it can be intuitively displayed, Wong
developed a novel database storage system and metadata
schema. Metadata is literally data about the data.
For example, the metadata
attached to a measurement from a particular sensor
might describe the type of sensor and where in the building it's
located.
Wong's system can also perform calculations on independent
pieces of
data to provide information that's useful for evaluating
the building's health.
For example,
story drift, the rocking motion that occurs between stories in
a building, is determined
by calculating
the difference
in position
between the two stories. Wong's software automatically
performs that calculation on the raw data from two
sensors so that
the story drift
can be taken into account when the system diagnoses
the building's overall structural health. A dangerously
high
amount of drift
might then trigger a "check building" alert
on the property manager's display. He would then
call in an engineer who might drill
deeper
into the data in attempt to identify the cause.
Wong's
system will be put to the shake table test within
the next six months when a twenty-foot-square,
single-story
structure
is
instrumented with sensors and then subjected to
a simulated earthquake on UC Berkeley's
giant shake table. The researchers will then assess
their system's accuracy in diagnosing the specimen's
structural
integrity.
Currently, most
models that predict how a particular building will perform in
an earthquake are based
on data collected
from shake table
experiments and other simulations. Wong's system
will help civil engineers study the effects
of real earthquakes,
windstorms,
and other phenomena
though, hopefully aiding in the design of better
buildings.
"Our system is geared so that the real world can be used as an experimental
test-bed," Wong says. "That way we
can refine our modeling of structures to match
up a building's expected performance with
its actual performance during a quake."
Framework for Integration and Visualization of Structural State
Data
Professor
Bozidar Stojadinovic's home page
"Smart
Buildings Admit Their Faults" by David Pescovitz (Lab Notes, November
2001)
Lab Notes is
published online by the Public Affairs Office of the UC Berkeley
College of Engineering. The Lab Notes mission is to illuminate groundbreaking
research underway today at the College of Engineering that will
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Media contact: Teresa
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Writer, Researcher: David
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© 2004 UC Regents.
Updated 2/19/04.
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