Jusoh, Mohamad Ashry (2007) Development of a Microwave Technique to Predict Moisture Content in Mortar. Masters thesis, Universiti Putra Malaysia.
This thesis describes a simple microwave nondestructive free space method at 17.2 GHz to determine the moisture content of mortar cement. The method is simple, fast, contactless and accurate way to determine the moisture content in mortar. The measurement system consists of a 17.2 GHz dielectric resonator oscillator (DRO) as a microwave source, Power Meter as the detector, a pair of lens horn antenna to transmit and receive microwave signal. The 17.2 GHz frequency was chosen since the sensitivity to the moisture content is higher at this frequency compared to the low frequency. The Agilent Visual Engineering Environment software was used to control and retrieve data from the Power Meter. The microwave part of the measurement system is setup to determine the amplitude of transmitted wave (received powers). A comparison of the two received powers (with sample and without sample) gives an estimate of the attenuation of the sample. The actual moisture content was found by applying standard oven drying method. The calculation and selection of mixture model were discussed thoroughly and only the best performance of mixture model was selected. The dielectric mixture equation (Lichtenecker Mixture Model) has been chosen to calculate the complex permittivity of sample and also predicted the attenuation of sample due to the smallest mean error compared to other models like Kraszewski and Landau. An optimization technique was used to improve the Lichtenecker model so that the mean error between measured and predicted can be reduced. A calibration equation relating the measured attenuation and moisture content was established and the sensitivity of the sensor is 2.8147 dB/ % moisture content. An empirical model of moisture content was obtained from improved attenuation formula and was tested to the sample. The measured and predicted attenuation were found in good agreement within ±5% of mean relative error.
|Item Type:||Thesis (Masters)|
|Subject:||Mortar - Moisture - Forecasting.|
|Chairman Supervisor:||Zulkifly Abbas, PhD|
|Call Number:||FS 2007 25|
|Faculty or Institute:||Faculty of Science|
|Deposited By:||Rosmieza Mat Jusoh|
|Deposited On:||02 Apr 2010 08:03|
|Last Modified:||27 May 2013 07:19|
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