Citation
Alsayed, Abdallah S.Z.
(2015)
Robust position encoding and velocity deduction for real time water level monitoring.
Masters thesis, Universiti Putra Malaysia.
Abstract
Precision Farming is concept that emphasis on optimization of input for maximum output. In rice production, Precision Farming has been gradually implemented to improve the rate of production. One of the activities is in the management of water usage,
for better sustainability. Otherwise an uncontrolled water management leads to excessive use and in the long run may cause the soil to be damped and too soft for machinery to travel without sinking. Motivated by the problems related to irrigated water management
for rice production, this research was conducted as a proposed method to measure the level of water, deducing the rate of rising, and at the same time establishing a wireless connectivity for possible use of remote monitoring.
Specifically, this research presents a proposed technique for linear motion parameters measurement system. The measurement system contains linescan transducer with built in illumination system, grating scale, and ultrasonic sensor. Once the linescan transducer scans the grating scale optically, the displacement of the transducer is measured based on pixel differential method. However, if the time of the travelling is known, then it is possible to deduce the velocity and the acceleration of the transducer movement. Additionally, an ultrasonic sensor is added to the transducer to provide the initial position in proximity.
The design of the linescan transducer basically included the illumination source and the division of grating scale. The accuracy of the measurements were compared to white and infrared lights. Then, the comparison was based on three scale divisions which are 0.5 mm, 1 mm, and 2 mm. Finally, the accuracy was also compared to different travelling ranges of motion. Moreover, the linescan transducer measurements were evaluated comparatively to reference devices. Two ZigBee modules were incorporated into the device, which allowed remote data communication between the transducer to a monitoring station. The wireless connection was tested over different transmission distances with a view to inform the accuracy of the measurements through ZigBee technology.
The linescan module had low errors, if the grating scale division was 2 mm and the used illumination was infrared LEDs. In this case, the average error was 0.9% and the standard deviation was 11.63 mm over travelling range of 500 mm. However, after adding an ultrasonic sensor to the transducer, the integration of linescan sensor and ultrasonic sensor could measure the displacement over 1 meter with average error of 1.18% and standard deviation of 783 mm. The remote monitoring system could successfully send the data over different transmission distances (1.5m-10m) based in ZigBee modules. As
a result, the output of this research is a contribution to knowledge in novel, robust, and simplified method for measurement of displacement, velocity, and acceleration of object in linear horizontal motion.
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