Theses & Dissertations

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https://hdl.handle.net/20.500.14170/206

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Browsing Theses & Dissertations by Department "Universiti Malaysia Perlis"
  • Publication
    A modified retinex illumination normalization approach for infant pain recognition system
    ( 2014)
    Muhammad Naufal Mansor
    Pains in newborn babies are monitored in a Neonatal Intensive Care Unit (NICU) for medical treatment. Pain in newborns can be detected by studying their facial appearance. Even though the outcome is acceptable, it is not adequately vigorous to be used in unpredictable, non-ideal situations such as noise and varying illumination environment. First, to improve the noise cancellation robustness an adaptive median filter (AMF) is proposed. Mean and variance of median values are selected to generate a weight for each window part of the images such as 3x3, 5x5 or 7x7. Various linear and nonlinear filters are adopted to eliminate the noise in the images. Quantitative comparisons are performed between these filters with our AMF in terms of Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Image Enhancement Factor (IEF) and Mean Structural SIMilarity (MSSIM) Index. The average results show improvement in terms of 40.63 db for PSNR, 6.01 for MSE, 258.09 for IEF and 0.97 for MSSIM respectively. In this work a novel method of illumination invariant normalization known as Modified Retinex Normalization (MRT) for preprocessing of infant face recognition is proposed. This is based on a modified retinex model that combines with histogram normalization for filtering the illumination invariant. The proposed method is compared to other methods like Single scale Retinex (SSR), Homomorphic method (HOMO), Single Scale Self Quotient Image (SSQ), Gross and Brajovic Technique (GBT), DCT-Based Normalization (DCT), Gradientfaces-based normalization technique (GRF), Tan and Triggs normalization technique (TT), and Large-and small-scale features normalization technique (LSSF) for evaluation with Infant Classification of Pain Expressions (COPE) database. Several experiments were performed on COPE databases. Single PCA, LBP and DCT feature extraction information yielded a good recognition result. However, by summing these three, it gives more robustness to noise and illumination classification rate because the sum rule was the most resilient to estimate errors and gives higher than 90% accuracies of pain and no pain detection. The new illumination normalization and combination of features gives higher results of more than 90% on five different classifiers with various algorithms such as k-nearest neighbors (k-NN), Fuzzy k-nearest neighbors (FkNN), Linear Discriminat Analysis (LDA), Feed Forward Neural Network (FFNN), Probabilistic Neural Network (PNN), General regression Neural Network (GRNN), SVM Linear kernel (SVMLIN), SVM RBF kernel (SVMRBF), SVM MLP kernel (SVMMLP) and SVM Polynomial kernel (SVMPOL) with different performance measurement such as Sensitivity, Specificity, Accuracy, Area under Curve (AUC), Cohen's kappa (k), Precession , F-Measure and Time Consumption .
  • Publication
    An assessment of the orbital elements of RazakSAT for attitude determination using extender Kalman Filter
    ( 2020)
    Mohd Zamri Hasan
    Malaysia has successfully developed and launched RazakSAT, the first mini satellite at the Near Equatorial Orbit (NeqO). The mission was focus on a technology demonstrator and one of the payloads is a high-resolution camera to capture images at the equatorial region. The purpose of RazakSAT’s Attitude Determination System (ADS) is to ensure that the orientation is relative to Earth. Any misalignments or disturbances on the ADS can affect the orientation of the satellite in terms of the orbital position. Therefore, this research focuses on determining the attitude of a satellite in order to determine the orbital position for control requirement purposes. However, conducting experiments in the space environment to determine the accuracy and computation time is impossible due to cost constraints and the fact that facilities are scarce resources. As RazakSAT data is NEqO based orbits, so it proposed to use as reference to the actual data to substitute for the experiments in the space environment. The main aim is to give accurate information and computation time for the attitude estimation of ADS. In this thesis, RazakSAT data are used as a reference to give accurate information and computation time for the attitude estimation of ADS. Keplerian orbit model is implementing as an orbital model and compares with the NEqO of RazakSAT data. Besides that, Satellite Tools Kit (STK) software were used to conduct and validate the reliability analysis for orbital elements of RazakSAT such as the Earth-Centered Inertial (ECI), Earth Centered Earth Fixed (ECEF) and Latitude Longitude Altitude (LLA) based on the Two-Line Element (TLE) provided by Astronautic Technology Sdn Bhd (ATSB). The sun vector and magnetic field vector in the field in the orbit frame were analysed using the sun model, and International Geomagnetic Reference Field (IGRF). The sun vector in the body frame is the measurement from the sun sensor and magnetometer. The result on ECI and ECEF was analysed as well using the STK. The Keplerian orbit model was found to be more accurate than STK for LLA where the error yield is less compared to the Keplerian orbit model. The overall result for ECI, ECEF, and LLA is less than 5%, which also meets the error requirement of ATSB for RazakSAT orbit. For the sun model analysis, due to the difficulties in obtaining information about the RazakSAT sun sensor from ATSB, the analysis for the sun model utilized the results from STK and mathematical model developed in this thesis. The result shows that the percentage error for the sun in the orbit frame and body frame is acceptable, less than 5%. The magnetic field in the body frame and orbit frame from STK is more accurate compared to IGRF model. From the overall orbital results, RazakSAT was found are able to fulfill the requirement of the orbital specification while entering its orbit. For the attitude estimation of the satellite, a recursive approach known as an Extended Kalman Filter (EKF) is used to estimate the attitude. In this thesis, the kinematic and dynamics models for the EKF method are derived and analyzed in terms of controllability, observability, and stability. The result proved that the model could be controllable, observable, and marginally stable condition where it can be used for estimation by using EKF.
  • Publication
    An improved mobile robot based gas source localization with temperature and humidity compensation via slam and gas distribution mapping
    ( 2016)
    Kamarulzaman Kamarudin
    This research is concerned with the problem of localizing gas source in indoor environment using a mobile robot. The problem could be seen as similar to the event of hazardous gas leak in a building. Since the environment is often unknown to the robot, the Simultaneous Localization and Mapping (SLAM) operation is required. Two open source SLAM techniques (i.e. Gmapping and Hector SLAM) were implemented to provide this crucial information. Extensive experiments and analysis on both SLAM techniques yielded that the Hector SLAM is more suitable for gas distribution mapping (GDM) application due to the improved robot pose estimation, less computational requirement and only performs map correction locally. Therefore, the Hector SLAM is combined with Kernel DM+V algorithm to achieve real-time SLAM-GDM for predicting gas source location. Rigorous real-time experiments were conducted to verify the performance of the proposed SLAM-GDM method in an uncontrolled office building with the presence of ethanol emission. The experimental results showed that the prediction of gas source location is often accurate to 0.5 to 2.0m. Furthermore, an Epanechnikov based Kernel DM+V algorithm was also introduced to limit extrapolation range in GDM computations. The observed advantages were lower computational requirement and slightly more accurate prediction on gas source location. More importantly, it was found that the maps produced were able to indicate the areas of unexplored gas distribution and therefore could be used for the robot‘s path planning. The final and the main part of the thesis deals with the effect of ambient temperature and humidity on metal oxide gas sensor (i.e. TGS 2600) response; which could affect the GDM results. Linear regression processes were conducted to create a model to correct the temperature and humidity drift of the gas sensor response. The model (i.e. function) was tested in various configurations and was found to minimize the effects of the two environmental factors on the gas sensor response in different gas concentrations. Finally, two versions of Kernel DM+V/T/H algorithms were proposed and coupled with the drift model to compensate for temperature and humidity variation during the GDM task. The experimental results showed that the Kernel DM+V/T/H algorithms were able to produce more stable gas distribution maps and improve the accuracy of gas source localization prediction by 34%.
  • Publication
    Application of D-STATCOM to mitigate high inrush current during start-up of three-phase induction motor
    ( 2014)
    Ayob Nazmy Nanyan
    This thesis presents the application of Distribution Static Compensator (D-STATCOM) to mitigate inrush current during start up three phase induction motor. Three phase induction motor draws high current during starting period and will from 6 to 7 times of the rated current of the motor. The effect of high starting current will cause severe damage to motor itself, especially overheating and making motor life expectancy short. In addition, the high starting current will cause the voltage of the power supply rapid drop and affect other devices’ running in the same power line. The purpose of this thesis is to demonstrate that a D-STATCOM is capable to mitigate inrush starting current during start up induction motor. The controller circuit of D-STATCOM has been simulated by using Power System Computer Aided Design (PSCAD/EMTDC) software. The research methodology of this project is to design D-STATCOM circuit which consists of Voltage Source Converter as a main circuit. The function of this circuit is to convert AC to DC and then invert DC to AC before transmit to the threephase power line. The circuit’s has a capability to absorb and inject the reactive and active of the power system which is to control the magnitude of the VSC output voltage. To compare the capability of the D-STATCOM, a Soft starter is developed. The Soft starter circuit is controlled by six thyristors. There were three methods which can be used such as starting the induction motor with direct start-up, starting the induction motor by connecting with the D-STACOM and starting the induction motor with Soft starter. The starting currents of these three methods were observed up to 30 milliseconds and compared. The analysis result shows that the D-STATCOM had mitigated inrush current during start-up induction motor up to 74% higher compared to direct start-up and 164 Ampere is the highest inrush current recorded while direct startup was 637 Ampere recorded. The D-STATCOM was compared with Soft starter to determine the ability of reducing inrush current during start-up induction motor. The result shows that the D-STATCOM had mitigated of 54.3% higher inrush current compared with Soft starter. Hence, the conclusion of this research is the D-STATCOM has a higher capability to reduce inrush current during start up the induction motor compared with Soft starter.
  • Publication
    Assessment of cooling photovoltaic-wind hybrid power controller system for AC load application in tropical climate condition
    ( 2015)
    Mohd Irwan Yusoff
    This research looks at the assessment of cooling photovoltaic (PV)-wind hybrid power controller system for alternating current (AC) load application in tropical climate condition. It has four objectives in order to fulfill the requirement of this research. Firstly, the study of the potential PV and wind power generation in Perlis has been discussed. The data of solar radiation and wind speed were measured at the Centre of Excellence for Renewable Energy (CERE), University Malaysia Perlis in Perlis, Malaysia. The average of solar radiation for the past three years (2011 to 2013) is higher than 3 kWh/m2 which indicates that Perlis is suitable for solar power technology application. Secondly, a new model based on wind direction data in order to estimate the wind speed has been proposed. The development of the theory of circular-linear functional relationship model via circular-linear regression model proposed by Mardia (1976) when both variables are subject to errors are presented. The model has fitted the data quite well by assuming that both variables of the unreplicated circular-linear functional relationship model are subject to errors. This indicates that the proposed method is acceptable and applicable. Third, the temperature of PV module increases when it absorbs solar radiation, causing the decrement of efficiency. Therefore, the proposed topology of PV automatic cooling system is designed, constructed and experimentally researched within this study in order to overcome this challenge. To reduce the PV module surface temperature, direct current (DC) cooling system was designed using three methods which are DC brushless fan, DC water pump and DC hybrid brushless fan with DC water pump. They will make the air movement and water flow circulation at the back side and front side of PV module, respectively. Four temperature sensors were installed on the PV module to detect its surface temperature.
  • Publication
    Black-box modeling and adaptive control of hybrid thermoelectric refrigerator systems
    ( 2016)
    Mohd Saifizi Saidon
    Vaccines carrier has been used to keep the temperature within 2–8°C. However, a poorly functioning vaccines carrier may expose the vaccines to freezing temperatures. Hybrid Thermoelectric Refrigerator (H-TER) systems are developed in order to transport sensitive vaccines to hospitals at accurate controlled temperature. The refrigerator use air-to-air and direct thermoelectric heat pumps. This work reports on modeling and control studies carried out for H-TER systems that can control low temperature accurately. Different type of material containers (aluminium and stainless steel) is used and comparisons between them are analyzed. The systems are nonlinear and exhibits varying model parameters and dead-time. The objective of the study is to investigate control strategies that are based on non-priori plant knowledge and yet allowing for continuous adaptations of the controller to changing system dynamics. In fact, the various cooling load also causes a reduction of refrigerator efficiency including the fluctuation of imposed current level due to electronic component performance and varied operating condition of thermoelectric module on cold and hot ends against time. Thus an adaptive control system is considered to handle the problems that are stipulated above. A black box modeling approach is chosen since this is needed for the implementation of adaptive controllers. The H-TER systems have been identified using both Recursive Least Squares (RLS) and Recursive Extended Least Squares (RELS) methods. Since RELS has shown to give biased estimates for filtered data and slow convergence estimates for unfiltered data, RLS has been chosen for the model as its give a better representation of the systems. A second order model of H-TER I and HTER II systems are found to adequately represent the system as it give best fit of 0.0009 and 0.0007 respectively which made the fourth order to be insignificant for implementation. Validation procedures using second order model for online estimation, show that the model is indeed a good representation of the H-TER systems. On-Off and PI controllers are the commonly used in thermoelectric system is applied to this system as case studies. PI controller shows better performance over On-Off controller in term of steady state error.
  • Publication
    Cascaded push-pull and cascaded h-bridge inverter for total harmonic distortion reduction in stand-alone photovoltaic system
    ( 2013)
    Saidatul Shema Saad
    This thesis presents the cascaded Push-Pull and cascaded H-Bridge inverter for total harmonic distortion (THD) reduction in stand-alone photovoltaic (PV) system. This study involves the development of the proposed cascaded Push-Pull inverter and cascaded H-Bridge inverter for stand-alone PV system applications. This study also involves the data collection of solar irradiance, temperature and PV module electrical output. The output of PV module is in direct current (DC) form. However, the power utilisation in Malaysia is mostly in alternating current (AC) form. Therefore, a sophisticated conversion technique is required in converting the DC signal into AC signal which is known as inverter. The output voltage waveform of ideal inverters should be sinusoidal. However, the waveform of practical inverter is non-sinusoidal and contains harmonics. The aim of this research is mainly to study and develop the suitable inverter design that can be applied in stand-alone PV system. Therefore, three inverter designs which are Push-Pull inverter, cascaded Push-Pull inverter and cascaded H-Bridge inverter have been developed for stand-alone PV system and THD has been analyzed over these three inverters. The data collection of solar irradiance and temperature were analyzed in order to know the potential of solar energy application in Perlis. These data were measured using weather station at the Centre of Excellence for Renewable Energy (CERE), in Kangar, Perlis. Solar irradiance and temperature are two important variables to be considered in designing a PV system because these variables will affect the PV module electrical output. Based on the average monthly solar irradiance for the year 2011, the annual total solar irradiance in Perlis is 4715.95 W/m². This shows that solar irradiance intensity was very high and has a potential for PV power generation in Perlis. Meanwhile, the performances of the proposed inverters have been evaluated in terms of output waveform and THD. The Push-Pull inverter, cascaded Push-Pull inverter and cascaded H-Bridge inverter has been simulated using OrCAD software. These three inverter designs are modelled with the resistive load. Based on the simulation results, the performance of cascaded H-Bridge inverter is better compared to cascaded Push-Pull and Push-Pull inverters. The experiment also has been carried out using inductive load of 20 W AC water pump for Push-Pull and cascaded Push-Pull inverter while the cascaded H-Bridge inverter was tested with pure resistive load of 50 Ω. The experimental result shows that the output waveform of cascaded H-Bridge inverter is nearly to sinusoidal shape and the voltage THD is less than cascaded Push-Pull and Push-Pull inverter. A comparative study between output waveform and THD between simulation and experiment has been conducted and validated. The results obtained show that the experimental results are close enough to the simulation results. A comparative study of output waveform and THD between Push-Pull inverter and the proposed cascaded Push-Pull and cascaded H-bridge inverters has been also conducted. The result shows that the proposed cascaded H-Bridge inverter is better than cascaded Push-Pull inverter in terms of output waveform and THD. It also shows that the THD of proposed cascaded Push-Pull is better than Push-Pull inverter. Overall, these three inverter designs are basically suitable for DC source applications and can be applied for PV system applications which are dependent upon the load application.
  • Publication
    Classification of interior noise comfort level of Proton model cars using artificial neural network
    ( 2012)
    Allan Melvin Andrew
    Car interior noise comfort level classification is one of the most promising sub-fields in automotive research. Car interior noise comfort indicator is developed to help the drivers to keep track of the noise comfort level in the car. Determination of car comfort is important because continuous exposure to the noise and vibration leads to health problems for the driver and passengers. In this research, a proton model cars noise comfort level classification system has been developed to detect the noise comfort level in cars using artificial neural network. This research focuses on developing a database consisting of car sound samples measured from different proton make cars in stationary and moving state. In the stationary condition, the sound pressure level is measured at 1300 RPM, 2000 RPM and 3000 RPM while in moving condition, the sound is recorded while the car is moving at constant speed from 30 km/h up to 110 km/h. dB Solo equipment is used to measure the noise level inside the car. Subjective test is conducted to find the jury’s evaluation for the specific sound sample. The data is preprocessed and features are extracted from the signal frames. The correlation between the subjective and the objective evaluation is also tested. The feature set is then feed to the neural network model to classify the comfort level. The respective index is displayed at the designed Graphical User Interface (GUI). Experimental results show that the use of proposed Composite Feature yields a better classification accuracy compared to the conventional feature extraction method. The Spectral Composite Feature gives the highest classification accuracy of 94.21%.
  • Publication
    Compact ingestible planar inverted-F antenna (PIFA) for biotelemetry systems
    ( 2015)
    Muhammad Solihin Zulkefli
    Bleeding from the gastrointestinal (GI) tract is a common medical problem. The GI tract starts at the mouth, going to the oesophagus, stomach, small intestine, colon and end at the rectum and anus. The traditional wired endoscopy made it possible to diagnose the oesophagus, stomach, colon, rectum and anus, but limited by physical reasons, leaving the remaining 20 feet of the small intestines regardless using upper or lower endoscopy procedures. An ingestible wireless biomedical device or wireless capsule endoscope fitted with a mini video camera and small enough to swallow can painlessly examine the parts that wired endoscopy cannot reach for diagnosing unexplained bleeding or other abnormalities. The challenging demand of ingestible wireless biomedical device performance reflects on the difficulties of designing the antenna for those device since the antenna plays a key role for having an abundance of quality communication links and miniaturization of the whole device, compared to the other essential components. In this thesis, a compact planar inverted-F antenna (PIFA) is proposed to be integrated with an ingestible tablet antenna system for biotelemetry application in the 2.4-2.48 GHz industrial, scientific, and medical (ISM) band. By taking the tissue properties and its losses, the design of the proposed antenna was performed inside a phantom box filled with body tissue simulating liquid (BTSL) (εr = 52.7). Besides reducing simulation time, this is mainly due to the practical ease to validate and measure its similar performance within the environment of a human small intestine (εr = 54.4). The proposed antenna is compact and is sized at 859 mm3 (15 mm x 12 mm x 4.7748 mm). It is built using twostacked structures; Taconic TLY-5 (εr = 2.2, tan δ = 0.0009) substrate and Eccostock HiK500F ceramic material (εr = 30, tan δ = 0.002). The resonance characteristic, radiation performance, specific absorption rate (SAR) distribution and communication link of the proposed antenna inside the BTSL is evaluated and compared with its performance inside a four-layer canonical tissue model (skin, fat, muscle and small intestine). Most importantly, the proposed antenna achieved the highest bandwidth per unit volume (BW/Vd) compared to other work in literature for in-body applications.
  • Publication
    Context-aware activity recognition and abnormality detection approaches in smart home environments
    ( 2019)
    Abdul Syafiq Abdull Sukor
    The rising number of elderly population has become a common concern in many countries around the world. The issue has impacted social and economic life of modern societies due to the fact that elderly people are known to suffer from many medical disabilities. As one of the solutions, current technologically-driven approaches, particularly in the area of smart home environments have been developed in recent years to support the independent living and reduce the caregivers’ burden in taking care of elderly individuals. Sensors installed in the environments are used to monitor users’ daily routine to see trends in the behaviour and to be informed of any abnormal activity. However, the accurate interpretation of sensor data in identifying human activities and their abnormal behaviour is still limited. Furthermore, pattern analysis involving these two areas are becoming an increasingly scientific challenge to the real-world environments. This study intends to deal with the issue by investigating appropriate means of pattern recognition and data mining methods within smart home environments. In particular, the study attempts to develop an intelligent reasoning system that can identify residents’ activities and abnormal behaviour of the smart home residents. In this study, two types of activities are identified, i.e., context-related and motion-related activities. The former is classified using the hybrid approach while the latter is performed through the ensemble-based machine learning techniques. The output models produced by these activity recognition approaches are then used as the input for the deep learning networks to produce behavioural model of smart home residents. Experimental procedures are then performed to validate the proposed approach. First, a comparison between the knowledge-driven model and hybrid activity model is carried out to identify the context-related activity. Then, another comparison between the performances of single classifier with multi-classifier system is also performed to identify the motion related activity. Furthermore, for the abnormality detection, several types of reasoning systems are used. These include the case-based reasoning (CBR), deep learning models composed of multi-layer perceptron network (DMLP) and deep recurrent neural network (DRNN) as well as the conventional machine learning algorithms such as naïve Bayes (NB), Support Vector Machine (SVM) and multi-layer perceptron neural network (MLP). The experimental results show that the proposed hybrid approach has better classification rate to identify context-related activity compared to the knowledge-driven model, where the accuracy is obtained at 98.7% ± 0.4. Meanwhile, the multi-classifier system performs better than a single classifier in identifying motion-related activity, with the accuracy of 99.6% ± 0.2. Moreover, DMLP shows higher accuracy rate (98.2%) compared to the DRNN, CBR and other machine learning algorithms for the abnormality detection system. The presented results show that this study can give an impact to the improvement of reasoning process in identifying abnormal situations in smart homes. This can be used in many applications especially in healthcare domains. Furthermore, this study helps to benefit future technologists in order to achieve Society 5.0.
  • Publication
    Deployment of wireless sensor network (WSN) in agricultural environment in northen Malaysia
    ( 2014)
    Azizi Harun
    The advent of Wireless Sensor Networks (WSN) has been fuelled mainly by the advancement in miniaturization of electronic devices and the rise of high volume manufacturing that has been the key supporting factor for the advancement economically. Recent food crises happening over various parts of the world triggered the consciousness over food security and food production capability. For the modern food production to be successful, a thorough understanding and awareness of temporal and spatial crops behaviour is super critical. Thus the use of sensor and wireless sensor networks and proper deployment planning to support modern precision farming is the key to optimum coverage establishment in the farmland. This thesis was written based on the following objectives; assessment energy consumption in WSN nodes as a function of data transmission interval and transmission power level setting; configure a system for short to mid-range link measurement for the study in agricultural environment. The thesis also evaluates existing signal path loss models, identifies or develops new path loss models for WSN system in agricultural environment. Additionally, the thesis also design and model a wide area WSN in agricultural environment. To meet the objectives, propagation path loss measurements were conducted in multiple types of agricultural environments which cover assessment in mixed crop plantation, aquaculture ponds, green houses and mono crop plantations. Path loss models were evaluated and or developed and results were used in WSN simulation. Concurrently, WSN nodes energy consumption assessment was carried out and results used in the WSN simulation. Output from these study and measurements are energy consumption assessment in WSN nodes, path loss models and results from WSN simulation in agricultural environment. Measurement results acquired from the studies show that Log-distance model is the best fit model for measurement in mixed crop plantation while 2-ray model is sufficient to describe the propagation in aquaculture environment. Signal variation in aquaculture is influenced by changes in temperature, humidity and thus refractive index of the medium. Studies in mango greenhouse shows that signal fluctuation varies with vegetation density and Non Zero Gradient model can describe the overall signal propagation while Modified Exponential Decay is more appropriate for lower antenna height. Non Zero Gradient model with specific parameters can be used to describe overhead trellis type grape in greenhouse. For mono-crop plantation, Non Zero Gradient is suitable to describe ISM (Industrial, Scientific and Medical) band frequencies while Modified Exponential Decay is more suitable for frequency 800 MHz to 4.2 GHz in rubber plantation. Modified Exponential Decay is best describe the propagation at branch level while Non Zero Gradient at canopy level. For palm plantation, Modified Exponential Decay best describe signal propagation at trunk while Maximum Attenuation is at canopy level. A deployment model simulation was done at the end of the thesis illustrating the potential coverage based on power consumption in various signal behavior in mixed crop plantation.
  • Publication
    Design and development of autonomous omni-directional mobile robot with mecanum wheel
    ( 2007)
    Jefri Efendi Mohd Salih
    A variety of designs of mobile robot have been developed in recent years in order to improve their omni-directional maneuver and practical applications. Omni-directional mobile robot has vast advantages over conventional design likes differential drive in term of mobility in congested environments. The main purpose of this research is to design, develop and implement an omni-directional mobile robot with custom made mecanum wheel for autonomous navigation. Using these mecanum wheels, the mobile robot is provided with three degree of freedom (DOF) mobility. Attention also paid for the development of kinematics and dynamics model to analyze the mobile platform motion performances. Motor driver and robot controller were also developed. Motion control algorithm using BasicStamp Editor software was developed to test the capabilities of the system’s mobility performance. Experiments were performed to analyze the motion characteristic of the mobile robot motion in Y axis, X axis and differential drive capabilities. Using ultrasonic and line follower sensors, basic autonomous navigation had been develop and tested. Based on the experiment conducted, the autonomous navigation gave satisfactory result. The developed mobile robot will provide a test bed for advanced path planning and navigation projects in the future.
  • Publication
    Design and development of multi-terrain mobile robot in large scale plantation
    ( 2015)
    Mohamad Hanif Abd Hamid
    The wide range applications of mobile robots can be seen from domestic appliances to large scale implementation. One of the possible applications that can benefit from the use of mobile robots is large scale plantations. However such applications, say in oil palm plantations, poses real challenge due to the multi-terrain nature of such environment. Described in this thesis is the development of multi-terrain mobile robot for oil palm plantation. The development of the robot consists of three different of prototypes which test the different design parameters of the mobile robots, and the analysis and results used for the design and development of AGROBOT. Several implementation strategies were tested, such as localizations, power consumption and ability to maneuver. The testing of the mobile robot was a success and able to move along desired preset paths along the oil palm trees. The waypoint navigation will follow the path and recorded the desire route with the capability of avoiding the obstacle. The success in the implementation of a multi-terrain mobile robot, AGROBOT, will benefit the agro industry and may be used for application such as pesticide spraying and weeding.
  • Publication
    Design and development of single phase AC induction motor using copper rotor bars
    ( 2011)
    Syatirah Mohd Noor
    In this thesis, the single phase AC induction motor have been investigated and analyzed in terms of the induction motor parameter, efficiency, power factor and loss segregation of different rotor bar material. A copper rotor bar is fabricated and compared with the existing aluminium rotor bar through out this project. First aspect of comparison is done with software simulation using Opera 2D between aluminium rotor bar and copper rotor bar for the same 1.5HP stator slot design and winding configuration. The Opera 2D is compared in range of power loss, magnetic flux density, torque vs. speed, torque vs. slip, power loss vs. speed and power loss vs. slip. The second aspect is the hardware comparison between the fabricated copper rotor bars with the existing aluminium rotor bar. In this part, the copper rotor bar and aluminium rotor bar are tested using no load, blocked rotor, and DC resistance test to achive the difference of efficiency, losses and power factor improvement. From the overall experiment of software and hardware, results shows that copper rotor bar does increase the efficiency and power factor to 1.07 % and reduce losses to 11 watts compare to aluminium rotor bar. An economical aspect is presented to show the amount of energy and money that can be saved from replacing the aluminium rotor bar with a copper rotor bar. As for the annual energy saving (AES) and total cost saving (TCS), the copper rotor manage to save 124.51kWh per year and utility billing by RM41.76 per year per motor. Finally a rough estimation of 100,000 pieces induction motor that have been replaced with the copper rotor bars is assumed and shows that it will save approximately RM4.2 million.
  • Publication
    Design of a hybrid controller for solar and ocean wave energy harvester
    ( 2017)
    Ahmad Shukri Fazil Rahman
    This thesis presents an approach of hybrid system implementation between Photovoltaic and ocean waves. These renewable energy sources are abundant, clean and beneficial compared to existing fossil fuel. Common method of extracting energy from these sources normally utilized a single energy source for energy production. Through hybrid system, two or more sources integration is possible. Merging of multiples energy sources will complement and support any inadequacy attribute accompanying these sources. However, system complexity will increase as source increases resulting in complicated system. Thus a proper controlling method is required for effective source management. Therefore, this research was initiated to develop a controller for two system harvester modules, Photovoltaic and wave energy converter for hybrid power system. The controller should fully exploit energy potential characteristic by harnessing it to the maximum. This research provides an effective method of harvesting Photovoltaic and ocean waves. Photovoltaic source is dependable toward sun intensity while the ocean waves’ intermittent energy is unsuitable through conventional harvesting method. The established controller will integrate Photovoltaic and ocean waves and compensate power fluctuations. Proper integration was successfully executed through buck and boost converter module. The wave energy converter module was developed using ratchet mechanism and the generator unit was extracted from mini ceiling fan motor. An additional monitoring system was added and performs wireless transmission to operator. The developed Photovoltaic and Wave Energy Converter (WEC) sources progress rapidly with average power produced are 76.91mW and 82.237W respectively. The proposed controller excels in performance and produce effective hybrid energy management with measured with power extraction efficiency at 58%. The hybrid system was successfully executed within the prescribe scope boundaries.
  • Publication
    Design of a portable continuous systolic blood pressure monitoring kit with built-in low and high blood pressure early warnings
    ( 2009)
    Muhamad Khairul Ali Hassan
    About one in three adults in the United States have high blood pressure but high blood pressure itself usually has no symptoms. The prevalence of hypertension in Malaysians aged 30 years and above was 42.6%. The majority of cases (64%) in this country remain undiagnosed. Only 26% of Malaysian patients achieved blood pressure control (<140/90 mmHg). Now days, many people have high blood pressure for years without knowing it. Uncontrolled high blood pressure can lead to stroke, heart attack, heart failure or kidney failure. This is why high blood pressure is often called the "silent killer." The only way to tell if you have high blood pressure is to have your blood pressure checked. Blood pressure is often measured using a device called a sphygmomanometer, a stethoscope and a blood pressure cuff. Almost all the existing manual or automatic measuring techniques of blood pressure are based on this principle, which is not convenient for continuous monitoring of blood pressure. The objective of this study is to develop a portable continuous blood pressure monitoring system using an electrocardiography (ECG) sensor and a pulse sensor. Two methods were used to measure blood pressure continuously. The first method measures blood pressure continuously based on Heart Rate (HR) and the second method is based on Pulse Wave Transit Time (PWTT). Both methods were separately implemented for different techniques to measure systolic blood pressure (SBP). The techniques that were used to model the relationship between the PWTT or HR data to systolic blood pressure are linear regression model, non- linear regression model and neural network model. Neural network model gave the smallest value of mean of error and standard deviation of error for measuring blood pressure based on PWTT or HR. These errors are acceptable and relatively small compared to the standard accuracy, which should have a minimum mean of error value of 6 mmHg with a standard deviation of error of ±10mmHg. The subjects that were involved in portable BP monitoring kit testing are normal blood pressure subjects, low blood pressure subjects and high blood pressure subjects. All the data were taken about five minutes for each subject and the results were monitored by medical cardiologist/doctor or nurses. The accuracy of the SBP data from portable continuous BP monitoring kit was validated using sphygmomanometer. The results indicate that the developed portable BP system is adequate to be used for monitoring or measuring systolic blood pressure continuously. Warning system was developed in this portable BP monitoring kit. The warning system is generated based on blood pressure value and trend of increasing or decreasing of systolic blood pressure values. The warning is given in form of alarm. The alarm will be “on” when the systolic blood pressure value goes more than 140mmHg (High Blood Pressure) or less than 100mmHg (Low Blood Pressure) or if the SBP increasing or decreasing trend in more than 5mmHg for each 30 seconds.
  • Publication
    Design of controller for boost converter to regulate voltage output
    ( 2015)
    Aminudin Anuar
    Capacitor can be used as an energy storage element to supply small power in replacing a battery. The advantage of using capacitor is the charging time is much faster than charging a battery. But the disadvantage is that the capacitor voltage value is not constant to supply a load. From that, a dissertation project has been conducted to design a controller using boost converter to regulate the capacitor voltage output. The boost converter used to control the voltage level. The boost converter circuit is constructed with power switch MOSFET. To generate pulse width modulation (PWM) to the MOSFET, a PIC16F877 used to drive PWM at specific switching frequency. The output voltage will step up from input voltage and use to operate the load. In this project, the complete circuit is designed using Matlab Simulink software with a specific value of parameter components. The design parameter is simulated and implemented into hardware and tested to get the result. There are two experiment has been handled. The first is the measurement of voltage output capacitor when connecting with or without controller and second is the controller design is connected to a load. From the experiment, the output voltage capacitor for circuit without boost converter has the result proportionally to the voltage input and the effect of the load. The circuit with boost converter is maintained at 24V for every voltage input and also connected to various load.
  • Publication
    Design of vibration energy harvester for low voltage power supply using finite element methods (FEM) analysis
    ( 2018)
    Afifah Shuhada Rosmi
    The rapid growth of electronic devices miniaturization attract the researchers interest either to save space or for cost reduction. The main purpose of miniaturization is to implement the concept of portable in order to locate the devices everywhere without connected to a power strip. Therefore, the use of battery as a power supply is the only choice to realizing the concepts. However, the improper battery disposal gives the detrimental effects to the environment and human being. Energy harvesting is proposed as the best solution as it provides more comfort and safety to the device compared to the old-fashioned battery. However, the development of lead-free vibration harvester for low frequency of ambient vibration energy is rarely reported. Thus, energy harvester based on zinc oxide (ZnO) piezoelectric material has been chosen as a vibration energy to electrical power transducer as it is compatible with microelectromechanical systems (MEMS) technologies, which can generate power from μW up to mW level power. Powering the devices using energy harvester is really suggested as it can provide clean energy, no need for frequent battery replacement and long-term solution. This research focus on designing and simulating the four different models of micro scale piezoelectric power generator (PPG) cantilever beam type named as PPG 1, PPG 2, PPG 3 and PPG 4 using COMSOL Multiphysics approach. The models with attached proof mass at the end tip were analyses to investigate the capability in converting the ambient vibration energy which is commonly below than 200 Hz and less than 1 g (1 g = 9.81 m/s2) acceleration amplitudes. Two working conditions are considered for the analyses. The first condition is to mount the PPG model to a machinery, while the second condition is to locate the PPG model close to the ambient sound wave energy sources. FEM simulation was done with two types of analysis taken. In order to obtain the required results which are resonant frequency analysis and evaluation of electrical output power, eigenfrequency and frequency domain modules were used. As a result, the frequency resonance for all models is below than 200 Hz. As a highlight of this work, PPG 4 shows the superior capability than other model since able to generate the highest output power which is 17.11 μW when integrated with voltage multiplier. Meanwhile, PPG 2 is more suitable for harvesting low frequency of vibration energy since able to vibrate at lower frequency compared to other models which is as low as 52.77 Hz. Based on these two findings about PPG 2 and PPG 4, PPG 4 is selected as the better model since capable in generating higher output power at resonant frequency less than 200 Hz.
  • Publication
    Development of a microcontroller-based inverter for photovoltaic application
    ( 2011)
    Sharulnizam Mohd Mukhtar
    Presented in this thesis is the development of a microcontroller-based inverter for photovoltaic systems. A single 8-bit microcontroller generated switching pulses for both stages of the inverter’s dc-dc converter and dc-ac inverter. A simple, effective algorithm suitable for implementation in a single 8051 microcontroller was developed, for control of the inverter’s power stage. The thesis explained details on the PWM and the SPWM switching strategies including calculation to presents their switching pulse widths. An inverter of 500W capacity was built to test the switching pulse generated by the microcontroller. A high frequency (HF) planar transformer raised input voltage to the inverter’s required level and provided isolation and solving difficulties in producing a handmade conventional HF transformer. The experiment were conducted in laboratory environment, where input voltage was taken from DC power supply and the inverter load was purely resistive. The prototype’s performance analysis results were found to be similar to those calculated. The prototype inverter performed well that able to produce a stable 240V output voltage at 50Hz, able to handle loads up to 500W, and had a low THD.
  • Publication
    Development of a swarming algorithm for mobile robots
    ( 2014)
    Humairah Mansor
    Swarming robots basically consist of a group of several simple robots that interact and collaborate with each other to achieve shared goals. It is inspired by social insects, which can perform tasks that are beyond the capability of an individual. In a navigation task, a single robot system is not suitable to be used as an agent for the navigation usually covers a wide range of area. Furthermore, a single robot system is more complicated and requires a higher cost to build since the mobile robots need to be more complex in order to enable their abilities. Therefore, a group of simple robots is introduced. A group of robots can perform their tasks together in a more efficient way compared to a single robot, hence develop a more robust system. This thesis presents an approach for swarming algorithm using autonomous mobile robots. This project implements the swarming algorithm by supplementing the ability of mobile robot platforms with autonomy and odour detection. The work focused on the localization of chemical odour source in the testing environment and the leader and follower swarm formation through wireless communication. The project was developed in stages, namely hardware implementation where the mobile robots were given the ability to detect obstacles. A TGS 2600 Figaro sensor was utilized to provide the ability to detect odour. To enable the mobile robots to communicate with each other and able to perform leader and follower designation once the target has been found, the robots were installed with X-Bee module. The robot which found the odour source first will be the leader and the other will automatically become a follower. The Received Signal Strength Indicator (RSSI) of X-Bee is used as the parameter to estimate the distance between the leader and the follower robots. The algorithm was developed using Arduino development environment. By combining these three algorithm stages, a simple swarming system is tested. In this research, the leader-follower designation has been proposed as the method of swarming searching behaviour. The results show that the searching method provides a centralized communication between all the mobile robots. This communication leads to a better wireless data exchange between mobile robots compared to the distributed communication approach which decision making is based on each agent in the testing environment. The RSSI used in this research shows the reliability as an estimation parameter between mobile robots. The use of RSSI is a new method of estimating the distance between two wireless communication nodes despite the widely use of Bluetooth, ultrasonic sensors and Global Positioning System (GPS). Based on the RSSI value, the swarming system experiment is demonstrated. From the results, future work on the stabilization of the RSSI value during the wireless data transmission can be further investigated.