Planar electromagmentic sensors for environmental monitoring : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Electricical Engineering at Massey University, Palmerston North, New Zealand
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Date
2011
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Massey University
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Abstract
Water is the essence of life and an important nutrient for every living thing. Therefore, ninety six novel planar electromagnetic sensors based on the combination of meander sensor and interdigital sensor have been designed, fabricated, and tested for the application of water quality monitoring. Experiments were conducted to obtain the impedance characterization for each sensor, and the results were used to estimate the important parameters that influence the performance of the sensors based on the equivalent electrical circuits. The best sensors were selected based on the design with the highest electrical parameters (total effective capacitance and effective inductance). Intensive modelling and simulation of the selected best sensors are also discussed where the results were compared with the simulation results. Furthermore, the best sensors have been tested to detect nitrates contamination in distilled water using sodium nitrate (NaNO3) and ammonium nitrate (NH4NO3) solutions with different concentrations. The sensor that consists of the series combinations of spiral meander planar sensor (with five turns) with the interdigital sensor (with large negative electrode): SECS22_1 is the best sensor to detect the presence of nitrate added into distilled water and can estimate the concentration level. Furthermore, the sensor was tested with various kinds of prepared samples and natural water samples taken from natural sources around New Zealand. The outcomes have shown a very good correlation of contamination level, translated from the qualitative and quantitative results. Using the SECS22_1 sensor, a method to estimate nitrate contamination in natural water sources using Independent Component Analysis (ICA) has been explained and demonstrated. This model can accurately estimate nitrate in a natural water source as shown by the results. A low-cost system has been developed based on SECS22_1, a microcontroller, a waveform circuit, signal conditioning circuits, and LabView. The results from the experiment have shown the low-cost system has the potential to be used as a tool for nitrate detection and water sources quality monitoring in remote places such as farms. Finally, the work and improvement for future consideration are also discussed in this research.
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Water quality, Sensors, Environmental monitoring