Prediction of ammonia and iron concentrations in water based on complementary double split-ring resonator (DSRR)

Ning Ting, Josephine Ong (2022) Prediction of ammonia and iron concentrations in water based on complementary double split-ring resonator (DSRR). Masters thesis, Universiti Tun Hussein Onn Malaysia.


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Ammonia and iron are water contaminants that are of concern in water quality monitoring. According to World Health Organization (WHO), the maximum level of ammonia and iron that can be absorbed by human body from drinking water were about 1.5 mg/L. The excessive ammonia and iron may affect public health, as excessive ammonia and iron will cause health issues, such as skin burn, ingestion problems, and liver damage. Compared with conventional water contaminant testing techniques, microwave sensing is an attractive solution in detecting ammonia and iron, since it is accurate and sensitive without demanding bulky, costly equipment and time�consuming sample preparation. This project aimed to design and develop a rectangular microstrip patch antenna with a complementary double split-ring resonator (DSRR) at 2.38 GHz as preliminary work for the detection of ammonia and iron concentrations. The dimension of the proposed design was calculated based on theoretical equations and simulated using CST MICROWAVE STUDIO®. Based on the simulated results, the resonance frequency and Q-factor of the proposed design were 2.379 GHz and 396.5, respectively. In order to present the functionality of the sensor, both the simulation and measurement of ammonia and iron are presented in the concentration range from 0 mg/L to 53 mg/L. The resonance frequency of the sensor shifted from 2.337 GHz to 1.952 GHz in iron measurement, meanwhile the resonance frequency of the sensor shifted from 2.3904 GHz to 2.3924 GHz in ammonia measurement. The average and minimum measured sensitivity for iron were 0.007 GHz/mg/L and 0.037 GHz/mg/L, respectively. Based on the results, predictive models were proposed to estimate ammonia and iron concentrations in water. It was found that the first-order of the polynomial model and the second-order of the Fourier model were the best models for the prediction of ammonia and iron concentrations, respectively. The models introduced 0.9965 and 0.9953 of R-squared values, and 0.9698 and 1.36 of Root�Mean-Square-Error (RMSE), for ammonia and iron, respectively.

Item Type: Thesis (Masters)
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Electrical and Electronic Engineering > Department of Electrical Engineering
Depositing User: Mrs. Sabarina Che Mat
Date Deposited: 07 Feb 2023 03:42
Last Modified: 07 Feb 2023 03:42

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