Investigation of Sonar Stabilisation Method for Improved Seafloor Image Quality - Geoinformatics for Intelligent Transportation - page 10

gyroscope is connected to the system, frequency drops to 20 Hz. The differences
between the maximum operating frequency of sensors and the frequency of the
measurement systems occur since the system performance is limited by the con-
troller Arduino Duemilanove computing power. The gyroscope

sends
the data to the controller which converts signals into degrees, additional processing
of the signal is not required. The data from the accelerometer is sent by signals in
which 1 g (9.81 m/s 2 ) is 256 bytes. If the accelerometer is not moved, the value of
axis Z is

“ ITG-3200 ”

256 bites. That is because the accelerometer senses earth gravitation pull.
In order to properly provide the axis Z accelerations it adds 256 to the value of the
received signal. The result is to be divided by 256 and multiplied by 9.81.
The resulting units of acceleration are m/s 2 . Accelerometer data is converted in the
same way.
The main parts of the algorithm that were used/programmed within the controller
are shown in Fig. 7 . The

—

first step was to integrate drivers for all sensors, including
calibration. Reading the data from the sensors is the first part of the actual program.

Here it is very important to get first part is to combine the data

form the g-sensor and the accelerometer. The second part is to use a virtual

' smooth ' data. The

lter
proposed by Koseeyaporn and Koseeyaporn [ 16 ]. For system testing we used the
mentioned virtual

cations for our case
study. Vessel heave motion was calculated using the acquired raw data. Calcula-
tions were done to determine how the speed of the electric motor and the direction
of spinning affected the heave motion compensation. Finally, we examined the
sending signal to the electric motor. On our small scale testing model we used a low
power stepper motor. Our model was functioning properly and ef

filter with some simple adjustment modi

ciently com-
pensated the heave motion. Also alternative data collection system is now being
prepared, using the same sensors and the new National Instruments (NI) software
and hardware components in Klaipeda University research laboratories.

Fig. 7 Algorithm scheme

Drivers for
sensors

Electric motor
controler

Reading data
from sensors

Calculating changes
of electric motor
speed and spinning
direction for heave
motion
compensation

Interpreting data and
calculating ship heave
motion speed and
direction