Structural Health Monitoring Using Smart Sensors - ideals ...

(2004) indicated that this accelerometer is suitable for SHM applications. Users need to be
aware of the sensing characteristics of smart sensors.
Characteristics of accelerometers need to be well-examined, especially in the low
frequency range, because major vibration modes of civil infrastructure appear in this
frequency range. Natural frequencies of tall buildings, towers, or long bridges can be as
low as 0.1 Hz. In terms of vibration amplitude, acceleration in the low frequency range is
small, underlining the importance of high resolution and sensitivity of a sensing system.
Ruiz-Sandoval (2004) and Ruiz-Sandoval et al. (2006) calibrated their sensor board with
special emphasis in the low frequency range. Though many smart sensors with
accelerometers have been proposed, only a limited number of acceleration sensor boards
can measure low frequency vibration accurately.
In addition to the sensor itself, the ADC, AA filter, and supply voltage regulator also
influence the quality of measurement signals. A low resolution ADC degrades measured
signals by introducing large quantization errors. The ADC on the Mica2, for example, has
only a 10-bit resolution, limiting the dynamic range of sensors. Appropriate lowpass
filters are essential to obtain digital signals free of aliasing. The sensor’s supply voltage
needs to be regulated so that current drawn by the microprocessor, radio device, or flash
memory does not destabilize current flow to sensing components. These components need
to be carefully designed. Otherwise, the structural information submerged in the
measurement signals may not be extracted. Because all of these issues affect signal
quality, smart sensor users cannot simply assume the sensing characteristics of a sensor
node are the same as those of a sensor component.
Even a dense array of smart sensors is not a rich information source for SHM if
physical quantities needed cannot be measured precisely by each smart sensor.
Development of sensor boards for SHM applications is still an important research issue as
well as calibration of these sensor boards.
2. Data aggregation
Data aggregation for SHM applications often encounters the following three issues:
(a) data size is too large, (b) data may be lost during wireless communication, and (c)
communication range is limited. Each of these problems is summarized below.
Smart sensors in general are not designed to collect a large amount of data, while
SHM applications benefit from data acquired from numerous sensors with high sampling
frequencies. Early applications of smart sensors, such as habitat monitoring, handled only
a small amount of data on an infrequent basis. On the other hand, SHM applications
typically acquires tens of thousands data points, each of which is represented as two- or
four-byte data. Sampling frequencies higher than 100 Hz and total sampling time longer
than a minute are quite common. In view of the need to handle a large amount of data,
SHM applications with smart sensors can be categorized into two groups, neither of which
has fully exploited the smart sensor’s capability.
In the first group, the smart sensors are employed in the same manner as traditional
wired sensors, with all data being collected for processing at a centralized location (see
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