School of Electrical Engineering and Technology (SEET)

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School of Electrical Engineering and Technology (SEET)

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    Harmonic Reduction Using Fractional Pitch Winding
    (3rd Biennial Engineering Conference, Federal University of Technology, Minna. Nigeria, 2013-05-16) Enesi Asizehi Yahaya; Mark Nwohu; Henry Ohize; O. Imoru; Usman N. Galadima
    The power source and the nonlinear loads on transmission line are major sources of harmonics and if these harmonics are not controlled, they could lead to heat loss, break down of machines and reducing the efficiency of any machine connected to the supply. The non-sinusoidal currents from the power source increase harmonic contents in the air gap of electrical machines with pole pitch winding which will lead to excessive losses, vibration and noise. This paper presents the use of fractional pitch winding technique for the stator of three phase motor for the purpose of suppressing harmonics. This is investigated between two windings of pole pitch and short-pitch and the results simulated using Emetor Electric Motor software.
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    Electromagnetic field analysis of a single-phase induction motor based on finite element method
    (3rd International Engineering Conference (IEC 2019) Federal University of Technology, Minna, Nigeria, 2019-05-06) Omokhafe J. Tola; Edwin A. Umoh; Enesi A. Yahaya; Chika Idoko; Ayo Imoru
    Electric motors are critical components of Electric drives systems, and their performance efficiency has consequences for the fidelity of electric drives and control. This paper presents an analysis of the electromagnetic field of a single-phase induction motor based on two-dimensional finite element method. The developed model of the machine was used to study its performance characteristics at different speed conditions, a view to affirm the accuracy of the specifications of the motor. The motor losses were analyzed and the transient results revealed the losses and a start-up time of 0.07 second with low pulsation at steady state. This implies the specifications are accurate. Therefore, the developed model has possibilities of applications in power system generating systems and industrial plants.
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    Permanent Split Capacitor (PSC) alternating current induction motor
    (Leonardo Electronic Journal of Practices and Technologies, 2015-06-26) Yahaya Asizehi ENESI; Tola J. OMOKHAFE; James G. AMBAFI; Eugene O. AGBACHI
    Single phase induction motors are found in various applications in which having correct value of the capacitor connected to the auxiliary winding enables the motor to function efficiently. This research aim is to investigate and obtain the value of the capacitor of a given input parameters of a specified permanent split capacitor (PSC) induction motor using MATLAB, which will in turn provide easy computation of the output parameters for the motor optimum efficiency. Electrical and mechanical characteristics of the PSC induction motor where obtained and analysed of which the study shows that the motor was reliable due to the absence of centrifugal switch. With the aid of MATLAB program the results were easily obtained, PSC induction motor capacitor value at optimum efficiency was also easily determined. The motor proved to have low starting torque, low starting current, higher efficiency, high pull out torque and high power factor. The characteristics of PSC induction motor analysed was limited to where higher starting torque is required only.
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    Split-phase motor running as capacitor starts motor and as capacitor run motor
    (Leonardo Electronic Journal of Practices and Technologies, 2016-06-28) Yahaya Asizehi ENESI; Jacob TSADO; Mark NWOHU; Usman Abraham USMAN; Odu Ayo IMORU
    In this paper, the input parameters of a single phase split-phase induction motor is taken to investigate and to study the output performance characteristics of capacitor start and capacitor run induction motor. The value of these input parameters are used in the design characteristics of capacitor run and capacitor start motor with each motor connected to rated or standard capacitor in series with auxiliary winding or starting winding respectively for the normal operational condition. The magnitude of capacitor that will develop maximum torque in capacitor start motor and capacitor run motor are investigated and determined by simulation. Each of these capacitors is connected to the auxiliary winding of split-phase motor thereby transforming it into capacitor start or capacitor run motor. The starting current and starting torque of the split-phase motor (SPM), capacitor run motor (CRM) and capacitor star motor (CSM) are compared for their suitability in their operational performance and applications
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    Intelligent Railway Cross Level Gates and Signaling System using Fuzzy Logic Control Technique
    (Convenant University, 2016-05-09) Olaniyi, O. M., Abdullahi, I. M., Maliki, D., & Lasore, T. M.
    Current manually operated gates at the railway cross levels of developing countries are stressful and time wasting. This has exposed pedestrians to high rate of accident resulting to loss of lives and drastic reduction of the country’s economy. Different systems have been developed to prevent rail accidents at the level crossing but they are not effective and in most cases are too expensive to implement. This study presents a prototype model of an intelligent railway cross level gates and signaling system using Mamdani fuzzy logic control technique. The intelligent system has the ability to detect the arrival/departure of a train and close/open the cross level gates respectively. The system response was evaluated with respect to time. The results after the evaluation of the developed system showed that the system with fuzzy intelligent control technique has a high response with respect to time compared to a system without an intelligent technique. The large scale implementation of the developed intelligent railway cross-level gate and signaling system can be used to prevent avoidable accident occurrence at the level crossings and thus, reduces loss of lives as well as improvement of the nation’s economy through efficient delivery of goods and services in Africa.
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    Abdullahi, I. M., Salawu B. T., Maliki D., Nuhu B K., & Aliyu, I. (2017). Development of an Artificial Neural Network Model for Daily Electrical Energy Management. Proceedings of the 2nd International Engineering Conference, (IEC 2017), Federal University of Technology Minna, Nigeria, pp 120-125.
    (Federal University of Technology Minna, 2017-05-07) Abdullahi, I. M., Salawu B. T., Maliki D., Nuhu B K., & Aliyu, I
    Efficient monitoring and control of electrical energy do not only prevent fire out-breaks caused by electrical appliances, but can also reduce excessive billings and prevent electrical installations. Most Energy Management Systems (EMS) for remote controlling of electrical appliances rely mostly on sensors, data and GSM networks which are un-reliable or even un-available in most part of developing world, this makes them less reliable. Therefore, there is need for an intelligent system that can manage electrical consumption intelligently using user-appliance interactive pattern over a period of time for intelligent control of users’ appliances in his/her absence. The model parameters (number of neurons and training algorithms) that affects its performance were first investigated and adopted. The performance of the developed model was evaluated using Regression analysis (R) and Mean Square Error (MSE) using ANN and Simulink tool boxes in Matlab R2015b. A good model can be used for real time control when deployed. Also, Scale Conjugate Gradient (SCG) training algorithm should also be used because of its high performance for pattern recognition problems. This work will go a long way in efficiently controlling household electrical appliances in the absence of the users thereby preventing fire disasters caused by electrical appliances, reducing the tariffs of consumers while increasing lifespan of electrical installations.
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    Fingerprint Based Driver’s Identification System.
    (Federal Univesity of Technology Minna, 2018-09-06) Inalegwu, O. C., Maliki, D., Agajo J., Ajawo, L. A., & Abu, A. D
    This design work presents a proposed replacement to the current system used by the Federal Road Safety Commission (FRSC) for checking licensed/unlicensed drivers. It gives a faster and less tedious way of identifying registered and licensed road users using biometric captures. The system employs the use of an Arduino board to control and process the functioning of other peripherals: the fingerprint scanner and the Organic Light Emitting Diode (OLED) screen connected to it to achieve its purpose. The prototype system developed was able to displays driver’s information on the OLED screen (Age, Name, Sex and License ID); the average response time of the system was also calculated to be 1.41 seconds, which is a good response time considering the system in question. The false Accept rate and false reject rate were relatively low (after a sample test with 25 individuals); at 4% and 8% respectively. Also, for its implementation, the components are readily available, relatively cheap and the system is on that can be easily adopted by the FRSC if access to their already existing database is granted. Consequently, it is safe to say that the developed system measured up to the design expectations; it meets the aim of a proposed replacement for the present analogue and easy to beat system employed by the FRSC.
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    Parameter Investigation and Analysis for Elite Opposition Bacterial Foraging Optimization Algorithm
    (Federal University of Technology Minna, 2019-04-22) Maliki, D., Muazu, M. B., Kolo, J.G., & Olaniyi, O. M
    The investigation and analysis of algorithm parameters is an important task in most of the global optimization techniques. However, finding the best set of parameter value for the optimum performance of an algorithm still remain a challenging task in a modified Bacteria Foraging Optimization Algorithm (BFOA) since most toe the existing research focuses on the application o the algorithm and likewise it benchmarking with the global test function. The Elite Opposition Bacterial Foraging Optimization Algorithm (EOBFOA) is a modified nature inspired optimization algorithm from BFOA which focuses on the generation of an elite solution from the opposition solution for an optimization process. This research is focuses on the investigation of such parameters population size, probability of elimination dispersal, step size and number of chemotaxis so as to determine the extent to which they affect the optimal solution from the EOBFOA with respect to global minimum or least minimum standard deviation. From the results obtained, it was observed that the global minimum in EOBFOA depend on the exploitation ability of the bacteria in the search space.
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    Development of a cost-friendly home-range TV transmitter to provide safe TV content to underage unsupervised Kids
    (Engineering Conference, School of Engineering and Engineering Technology, 2011) Michael Okwori; Oyewobi S. Stephen; M Saidu; U Abdulahi
    The security of a nation is directly linked to the moral conduct of her citizens, and this is affected by the kind of upbringing such citizens received as kids. Direct access of kids to video players and satellite TV receivers can lead to unwholesome programs being watched by the Kids especially when they are unsupervised, which can lead to character degradation and deformation. As a solution to this problem, this work is aimed at restricting unsupervised access of underage persons to programs on these electronics devices. Therefore, a low cost home range TV transmitter with pre-select channel-transmit capability, and auto timed turn-on and turn-off was designed. The designed Transmitter powers a Video player or Satellite TV Decoder at a preset time and transmits pre-selected programs on a Video player or Satellite TV Decoder in a restricted region in the house to a Television Set in an unrestricted region in the House that kids have access to for a preset duration. The Transmitter was tested, and it powered the Decoder and transmitted pre-selected programme at the preset time and for the preset duration.
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    Web-Based Decision Support System for Diagnosis of Ebola Virus Disease Using Bayesian Networks
    (2016) Dogo, E. M.; Kolo, J. G.; Aror, O.; Rahman, A. T.
    The recent epidemic of the Ebola Virus Disease (EVD) left many dead in West Africa and in other parts of the world. A major problem faced was late diagnosis or diagnostic error of the disease; this was due to largely unavailability of medical professionals familiar with the disease and low doctor to patient ratio. An accessible method for reliable diagnosis is required to offset the low ratio of doctors to population. This paper presents the application of Bayesian networks for diagnosis of EVD. A general procedure for implementing a Bayesian network model is proposed; thereafter we demonstrate how the resulting Bayesian network can be applied in a medical diagnostic decision support system. The system uses the questionnaire method to elicit symptoms and is accessible through web browsers over the internet and mobile phones to potential patients and medical practitioners. The system developed is able to provide diagnosis in the form of probabilities, for the presence or absence of EVD in an individual. The probability of an individual infected by the disease depends on present or absent of particular symptoms according to the gathered disease pathology. The system was successfully developed, and had a diagnostic accuracy of 77% when compared to the World Health Organization (WHO) algorithm, but refinements of the conditional probability distribution would provide the most accurate sensitivity to symptoms and also improve the accuracy of diagnosis. Finally, web functionality, performance and usability test on the developed web application is carried out by simulating various load patterns and the result was generally acceptable.