Structural Health Monitoring Using Smart Sensors - ideals ...

anges from 10 to 20. If 50 percent overlap is employed in the spectral density estimation
with 2,048 FFT data points, 20 time number of averages needs 21,504 data points.
There are other factors to be considered when the number of data points is
determined. One of them is the sampling frequency. The sampling frequency typically
ranges from 100 to 256 Hz for civil infrastructure. These sampling frequencies are high
enough considering the dominant modes of bridges, buildings, and towers. The
frequencies of dominants modes are usually lower than 10 Hz. The reasons why the
sampling frequency is much higher than the minimum frequency to capture vibrations
below 10 Hz include that higher modes may also be influential to the response, that a
periodic wave consists of multiple frequency components, that transient signal may have
high frequency components, and that ground motion, whose peak values are often utilized
in earthquake engineering, usually has higher-frequency components. A sampling
frequency of 256 Hz is a reasonable assumption for SHM system with smart sensors.
When a 0.1 Hz component of a signal sampled at 256 Hz is analyzed with an FFT of
length 1,024, only less than a half of the natural period fits in one window; the resolution
of FFT is too coarse. In such cases, the sampling frequency is lowered or the number of
FFT points is increased. Increasing the number of FFT points results in an increase in the
total number of data points.
The data type also affects the amount of memory required to store a measured signal.
The most often utilized are 16- and 32-bit integers, and double precision data. The sizes of
these data types are 2, 4, and 8 bytes, respectively. The effective number of bits of
resolution in the measured data determines the requirements on the data type. For
example, an acceleration signal with a resolution of 20 effective bits needs to use either a
32-bit integer or double precision data. Considering that many ADCs on smart sensors has
resolution poorer than 16-bit, 16-bit integers are most likely able to represent measured
sensor data.
The combination of 21,504 data points and 16-bit integer yields 43 kB of data per
sensing channel. Though this number will vary with changes in the number of data points
or the data type, 43 kB is used from here on as a typical amount of data generated per
sensing channel.
The number of sensing channels also depends on the applications. For example, one
of the bridges in Hong Kong famous for its densely instrumented sensors, Ting Kau
Bridge, has 67 channels to measure acceleration and 132 channels to measure strain.
These channels are normally sampled at 25.6 Hz. As such, hundreds of sensor nodes are
considered herein. One sensor node may have multiple sensing channels; for example,
acceleration measurement in three directions needs three channels. In total, this research
has a target of approximately a thousand channels.
A thousand sensing channels, each of which generates 43 kB of data, produce 43 MB
of data per measurement. Centrally collecting such a large amount of data is not practical.
Mechitov et al. (2004) reported that communication at the sink node is the bottle neck and
that collection of 480 kB of data from 16 Mica2s required more than 6,000 seconds. If
smart sensors with limited hardware resources, especially battery and RF components, are
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