Journal of Advances in Science and Engineering
Not a member yet
74 research outputs found
Sort by
Design and Fabrication of a Plastic Film Granulating Machine
Get PDFPlastic film granulating machine is an industrial machine used for reducing plastic materials, mostly for grinding plastic into granules of uniform sizes for further processing either into new plastic shapes or recycled back to its parental source. This paper presents the use of locally sourced materials for realising the same machine; reducing its size and cost, while maintaining high efficiency, as well as decrease in vibration and increased shear efficiency with uniform size of granules. The machine consists of the hopper, the grinding chamber in which contains the shaft and cutting blades with a discharge unit. The plastic film granulator has a capacity of granulating 1kg of recycled plastic in 1h at 75% efficiency, a working revolution of 3000rpm, and power rating of 5.5hp engine. The machine works by principle of shearing, power is transferred from the motor to the granulating shaft with the aid of a transmission coupler that connects them. The inlet plastics are granulated until the desired size is achieved, small enough to pass through the discharge screen
Developed Automated Vehicle Traffic Light Controller System for Cities in Nigeria
Get PDFThis paper presents a research work that was carried out to resolve challenges of traffic light system. This work employs the use of a microcontroller, an inductive loop which acts as the vehicle detector and LED’s (light emitting diodes) for simulating the red, yellow and green light in a traffic light. The inductive loop is embedded in pavement along the road which senses the presence of vehicle. When a vehicle passes across the loop, the magnetic field changes and the inductance of the coil is decreased resulting in a frequency change of the oscillator which is detected by the controller. The interrupt is set to make the traffic light allow the movement of vehicles on the lane with many vehicles on it according to information on the counter. This means that when the system discovers the lane with many vehicles by the number on the counter, the interrupt function comes into operation by interrupting the counting process and allowing the system to allow movement in that lane. Then the system resumes back to counting after this process is done. The test results show that the system can be physically and successfully implemented
Identification of Radar Signals Based on Time-Frequency Agility using Short-Time Fourier Transform
Get PDFWith modern advances in radar technologies and increased complexity in aerial battle, there is need for knowledge acquisition on the abilities and operating characteristics of intercepted hostile systems. The required knowledge obtained through advanced signal processing is necessary for either real time-warning or in order to determine Electronic Order of Battle (EOB) of these systems. An algorithm was therefore developed in this paper based on a joint Time-Frequency Distribution (TFD) in order to identify the time-frequency agility of radar signals based on its changing pulse characteristics. The joint TFD used in this paper was the square magnitude of the Short-Time Fourier Transform (STFT), where power and frequency obtained at instants of time from its Time-Frequency Representation (TFR) was used to estimate the time and frequency parameters of the radar signals respectively. Identification was thereafter done through classification of the signals using a rule-based classifier formed from the estimated time and frequency parameters. The signals considered in this paper were the simple pulsed, pulse repetition interval modulated, frequency hopping and the agile pulsed radar signals, which represent cases of various forms of agility associated with modern radar technologies. Classification accuracy was verified using the Monte Carlo simulation performed at various ranges of Signal-to-Noise Ratios (SNRs) in the presence of noise modelled by the Additive White Gaussian Noise (AWGN). Results obtained showed identification accuracy of 99% irrespective of the signal at a minimum SNR of 0dB where signal and noise power were the same. The obtained minimum SNR at this classification accuracy showed that the developed algorithm can be deployed practically in the electronic warfare field for accurate agility classification of airborne radar signals
Performance Evaluation of Medium-Term Load Forecasting Approaches: A Case Study of Ogun State, Nigeria
Get PDFThe place of electrical energy in enhancement of this computer age cannot be over-emphasised. Its forecast plays a significant functions in energy industry, helps the government and private sectors in making the precise decision regarding energy management practices. This paper presents performance evaluation of medium-term load forecasting techniques: a case study of Ogun State, Nigeria. Two different approaches were used using the previous load consumption in 2017 for the forecast. Least square approach compared with regression exponential approaches gave the least value of Mean Average Percentage Error (MAPE) and Root Mean Square Error (RMSE), which are 1.8212% and 0.004472 respectively. The anticipated percentage load growth for the months of July-December, 2018 forecasted with least square approach were 34.06%, 33.54%, 36.10%, 31.10%, 32.23% and 30.15% respectively, acute gas supply caused by pipeline vandalisation and theft of distribution/sub-station materials could be held responsible for low load growth in the month of December. The results of this analysis will assist the Regional Headquarters, Ibadan Electricity Distribution Company (IBEDC), Abeokuta, Ogun State in making effective planning, operation and management of energy across the state