Papers by Keyword: MATLAB

Abstract: This paper is devoted to the derivation of material indices using the finite element method. Material indices take into account material properties such a Young’s modulus and density are a powerful tool for material selection for various applications since they allow a quick comparison of suitability of different materials. Until now material indices were developed analytically for rather simple textbook-like examples. However, by implementing the finite element method and data fitting tools material indices can be developed for more complicated problems where the analytical solution cannot be obtained. The current paper describes derivation of material indices using ANSYS software. It is used as a simulator of a physical phenomenon. The simulation generates output data which is used to derive the material index.

Abstract: Numerical analysis of distribution of resistive heat source in two-phase conducting medium (copper electrode – biological tissue) was carried out. Axisymmetric two-dimensional elliptic problem, with boundary conditions of the first and second kind was solved in the environment of MATLAB mathematical package, using the method of finite differences. Analysis results show that heat source concentration and other parameters are determined by skin effect. This fact should be taken into account in development of new effective methods of surgical treatment and respective instruments. This mathematical model can be applied in a wide frequency range for conducting materials with different conductivities.

Abstract: As the heart of generator, stator bar’s production quality will directly influence the whole generator’s quality. We researched heating and solidification process of stator bar at the beginning to clarify the relationship between heating time and temperature. BP neural network toolbox in MATLAB platform was used to build neural network model which will relatively accurate estimate bar’s resistance with four process parameters. Through the resistance, people can find out the best technological parameters before actually production. We used some data collected from one factory as learning data. Others were test data, used to illustrate the rationality of the model, which can forecast insulation resistance value in later production, finding the optimal process parameters.

Abstract: In order to obtain a real-time interlaminar crack fracture behavior of the laminate composites, in this paper we propose a method of extracting and measuring of interlaminar crack of laminated composite materials based on 2D image analysis via the Matlab software. Extracting the main crack image were conducted using the Matlab script including four different algorithms: the binarization, region growing, morphological, and skeleton thinning, and then a main interlaminar crack image with 1 pixel width were obtained. The length of the main crack was calculated through the sum of pixels of the skeletonized object. The calculated result was closed to the measured result, and the difference between the calculated value and measured value was 0.2%, which can prove the accuracy of the method in present work. The proposed method is of high precision, with strong anti-inference ability and experimental data is stable and reliable, which is helpful to study the crack propagation behavior of laminated composite materials.

Abstract: This research work has been carried out to investigate the application of the Model Predictive Control Toolbox contained in MATLAB in controlling a reactive distillation process used for the production of a biodiesel, the model of which was obtained from the work of Giwa et al.¹. The optimum values of the model predictive control parameters were obtained by running the mfile program written for the implementation of the control simulation varying the model predictive control parameters (control horizon and prediction horizon) and recording the corresponding integral squared error (ISE). Thereafter, using the obtain optimum value of 5 and 15 for control horizon and prediction horizon respectively as well as a manipulated variable rate weight of 0.025 and an output variable rate weight of 1.10, various steps were applied to the setpoint of the controlled variable and the responses plotted. The results given by the simulations carried out by varying the model predictive control parameters (control horizon and prediction horizon) for the control of the system revealed that optimizing the control parameters is better than arbitrary choosing. Also, the simulation of the developed model predictive control system of the process showed that its performance was better than those used to control the same process using a proportional-integral-derivative (PID) controller tuned with Cohen-Coon and Ziegler-Nichols techniques. It has, thus, been discovered that the Model Predictive Control Toolbox of MATLAB can be applied successfully to control a reactive distillation process in order to obtain better performance than that obtained from a PID controller tuned with Cohen-Coon and Ziegler-Nichols methods.

Abstract: Reactive distillation is a process that combines chemical reaction and separation in a single piece of equipment (distillation column). The process has a lot of benefits especially for those reactions occurring at conditions suitable for the distillation of the process components, and these result in significant economic advantages. However, owing to the complexities resulting from the integration of reaction and separation, its control is still a challenge to process engineers because it requires a control method that is robust enough to handle its complexities. Therefore, in this work, model predictive control (MPC) has been applied to a reactive distillation process used for developing a renewable energy known as biodiesel. The control algorithm of the MPC was formulated with the aid of MPC toolbox of MATLAB/Simulink in which the closed-loop models of the process were developed and simulated. The analysis of the results obtained from the simulations carried out for the optimization of the tuning parameters revealed that, among the tuning parameters considered, integral absolute error of the control system was less affected by the control horizon because its p-value was greater than 0.05 based on 95% confidence level. Furthermore, the simulation of the closed-loop system of the process using model predictive control tuned with control horizon of 11, prediction horizon of 18, weight on manipulated variable rate of 0.05 and weight on output variable of 2.17, which were the optimum parameters obtained using Excel Solver, showed that the system was well handled by the controller under servo control because it was able to get settled at desired mole fractions within 60 min. However, the settling time recorded in the case of regulatory control system of the process with the same controller was found not to be encouraging. Therefore, it is recommended that further work should be carried out on this subject matter in an attempt to obtain tuning parameters that will make the settling time of the closed-loop system of the process under regulatory control simulation very reasonable.

Abstract: Optimally placing the sensors without compromising the performance is a challenge and its application is found in Structural Health Monitoring, Load Monitoring, Vibration Control and other areas. Every sensor has predefined region within which the source of disturbance is detected if it is present. This paper examines the use of fminimax concept on simple discretized plate using Genetic Algorithm to optimally place the sensors. This has been achieved by introducing maximum non detection probability in the objective function and the fitness of objective is minimized through genetic algorithm solver in MATLAB. The effectiveness of the present algorithm is then checked by comparing the solution with the solution obtained by implementing this concept on a continuous unit square plate using fminimax solver in MATLAB. The solution obtained in both the methods matched to that in the literatures. The study shows that the algorithm developed can be effectively adopted in discredited structures to optimally place the sensors.

Abstract: Vibration has a great influence on the cutting process and it can be detected by many signals. In this work, a set of experiments are conducted on Mikron UCP810 DURO high speed milling center with Fraisa carbide end mill for milling 2A12 aluminum workpiece, an acoustic method is used to detect the milling signals. The captured sound signals are analyzed using Matlab Daubechies5 wavelets with six levels of decomposition, the detail and approximation of the sound signal components are obtained. The analysis results demonstrate the relationship between the signal and the vibration.

Abstract: Changes in the climate over the past decades have caused weather extremes that bring numerous unwanted phenomena. Many of these irregularities cause unusually high and low temperatures, intense droughts and devastating floods. All of the listed natural disasters caused by weather extremes affect a wide range of fields which are crucial for our everyday life and its quality. The most affected areas are health and safety, agriculture, industry, transportation. It is therefore evident that the effect of extreme weather in any form can bring not only financial loses, but also a loss of human lives. Based on these facts it is of great interest that the effects of these natural forces are minimised or totally eliminated. This paper deals with the performance of a newly designed mobile flood barrier in real simulated field test conditions. Construction of the barriers was designed solely by the Slovak University of Technology at its Faculty of Mechanical Engineering with the intention of providing effective, economic and safe flood barriers system with a short assembly time. The undertaken testing was focused on the performance of the flood barriers under static pressure by the deflection measurements. The testing consisted of the following steps: experiment design, on sight mounting and fine-tuning of the whole measuring apparatus and evaluation of the gathered data. To simulate real conditions which the barrier will experience during its use, a life size model of the flood barrier segment was constructed and tested. The measurement setup, measurement procedures, the outcomes of the deformation testing together with the resulting deflection model are presented in the following pages of this paper.

Abstract: Data compression is the process of reducing the number of bits required to represent a data. Vector quantization is a method to deal with this operation of compression and is used to compresses the data which arise in wide range of applications and it can achieve better compression performance than any conventional coding techniques which is based on the encoding of scalar quantities. This article presents a test data that will be produced on testing the rocket engines in Liquid Propulsion Systems Centre using Fuzzy C-Means (FCM) based vector quantization. In this proposed vector quantization technique, Fuzzy C Means algorithm used to generate a fine initial codebook and then compress the data without loss. Experimental analyses were carried out and the final result concluded that the data compressed successfully without loss when 300 data were applied.