Fuzzy simulation of forest road surface parameters

The problem of construction of forest roads with the use of local low-strength substandard materials and industrial waste is considered. To solve the problem, the primary task is to develop a method for estimating the parameters of road surfaces taking into account the conditions of uncertainties in the data. This technique allows us to reasonably clarify some of the regulatory parameters and improve the technology of construction of forest roads, which was the goal of the work. To formalize the task, experimental studies were performed and on the basis of these results, the statement of the task of fuzzy derivation of the function for estimating the bearing capacity of the coating was performed. The synthesis of the output function is performed by means of Matlab. © 2019 IOP Publishing Ltd. All rights reserved

Plasma sprayed titanium coatings with/without a shroud

Abstract: Titanium coatings were deposited by plasma spraying with and without a shroud. The titanium coatings were then assessed by scanning electron microscopy. A comparison in microstructure between titanium coatings with and without the shroud was carried out. The results showed that the shroud played an important role in protecting the titanium particles from oxidation. The presence of the shroud led to a reduction in coating porosity. The reduction in air entrainment with t he shroud resulted in better heating of the particles, and an enhanced microstructure with lower porosity in the shrouded titanium coatings were observed compared to the air plasma sprayed counterpart

Diseño e implementación de un control difuso de temperatura para microplanta de cocción de cerveza artesanal mediante PLC

In this study, a fuzzy-based PLC temperature control system was designed and implemented on a craft beer production plant. At present, the temperature-related controls of small-scale plants in Colombia are based on On/Off models, which are not very stable in the preparation of craft beer, which generates significant changes in flavor, scent and texture. Therefore, it is intended to incorporate into the craft beer industry, solutions that guarantee repeatability, minimize costs and potentiate production, for this, a three-stage fuzzy control model is carried out: design, implementation and start up; This is how a study of the plant´s dynamics is carried out, the response is determined from the data, a fuzzy controller is designed by using Matlab software, and a graphical interface in LabView for data capture and storage. The controller demonstrates stability in relation to the temperature variable, which provides repeatability and significant energy savings. Finally, it is concluded that the controller proved to be robust against major disturbances and stable at different temperatures, being a useful tool for efficiently controlling the variable.En este estudio se diseñó e implementó un sistema de control difuso de temperatura basado en PLC sobre una planta de cocción de cerveza artesanal. En la actualidad los controles relacionados a temperatura de las plantas a baja escala en Colombia se basan en modelos On/Off, que son poco estables en la preparación de la cerveza artesanal, lo que genera modificaciones significativas en el sabor, el aroma y la textura. Por tanto, se pretende incorporar en la industria de cerveza artesanal, soluciones que garanticen repetibilidad, minimicen los costos y potencialicen la producción, para ello, se realiza un modelo de control difuso en tres etapas: diseño, implementación y puesta en marcha; se realiza un estudio de la dinámica de la planta. A partir de los datos se determina la respuesta, se diseña un controlador difuso mediante software Matlab, y una interfaz gráfica en LabView para captura y almacenamiento de datos. El controlador demostró estabilidad en relación a la variable, lo que proporciona repetibilidad y un ahorro energético significativo. Finalmente se concluye que el controlador demostró ser robusto ante grandes perturbaciones y estable ante diferentes temperaturas siendo una herramienta útil para controlar de manera eficiente esta variable

Distributed Analytics Framework for Integrating Brownfield Systems to Establish Intelligent Manufacturing Architecture

Intelligent manufacturing otherwise called as smart manufacturing concentrates upon optimising production and processes by making full use of data available. It is regarded as a new manufacturing model where the entire product life cycle can be simplified using various smart sensors, data-driven decision-making models, visualisation, intelligent devices, and data analytics. In the Industry 4.0 era, Industrial Internet of Things (IIoT) architecture platform is required to streamline and secure data transfer between machines, factories, etc. When certain manufacturing industry is equipped with this platform, an intelligent manufacturing model can be achieved. In today’s factories, most machines are brownfield systems and are not connected to any IoT platforms. Thus they cannot provide data or visibility into their performance, health, and optimal maintenance schedules, which would have improved their operational value. This paper attempts to bridge this gap by demonstrating how brownfield equipment can be IIoT enabled and how data analytics can be performed at the edge as well as cloud using two simple use cases involving industrial robot on the abrasive finishing process. The focus of this paper is on how a scalable data analytics architecture can be built for brownfield machines at the edge as well as the cloud

Control, optimization and monitoring of Portland cement (Pc 42.5) quality at the ball mill

Thesis (Master)--Izmir Institute of Technology, Chemical Engineering, Izmir, 2006Includes bibliographical references (leaves: 77-78)Text in English; Abstract: Turkish and Englishxi, 89 leavesIn this study, artificial neural networks (ANN) and fuzzy logic models were developed to model relationship among cement mill operational parameters. The response variable was weight percentage of product residue on 32-micrometer sieve (or fineness), while the input parameters were revolution percent, falofon percentage, and the elevator amperage (amps), which exhibits elevator charge to the separator. The process data collected from a local plant, Cimenta Cement Factory, in 2004, were used in model construction and testing. First, ANN (Artificial Neural Network) model was constructed. A feed forward network type with one input layer including 3 input parameters, two hidden layer, and one output layer including residue percentage on 32 micrometer sieve as an output parameter was constructed. After testing the model, it was detected that the model.s ability to predict the residue on 32-micrometer sieve (fineness) was successful (Correlation coefficient is 0.92). By detailed analysis of values of parameters of ANN model.s contour plots, Mamdani type fuzzy rule set in the fuzzy model on MatLAB was created. There were three parameters and three levels, and then there were third power of three (27) rules. In this study, we constructed mix of Z type, S type and gaussian type membership functions of the input parameters and response. By help of fuzzy toolbox of MatLAB, the residue percentage on 32-micrometer sieve (fineness) was predicted. Finally, It was found that the model had a correlation coefficient of 0.76. The utility of the ANN and fuzzy models created in this study was in the potential ability of the process engineers to control processing parameters to accomplish the desired cement fineness levels. In the second part of the study, a quantitative procedure for monitoring and evaluating cement milling process performance was described. Some control charts such as CUSUM (Cumulative Sum) and EWMA (Exponentially Weighted Moving Average) charts were used to monitor the cement fineness by using historical data. As a result, it is found that CUSUM and EWMA control charts can be easily used in the cement milling process monitoring in order to detect small shifts in 32-micrometer fineness, percentage by weight, in shorter sampling time interval

Simulation Model of Servo Motor by Using Matlab

The research aims to develop documented empirical data to obtain a high-accuracy and effective system according to a principal system as a model that represents the system for all expected cases and different working conditions. The current works are simulating a servo motor that works with specifications as a mathematical representation of it down to its representation with a transformation function. The simulation is done for different cases, the first is without a controller, and the other is an operation simulation with a conventional controller that is with a PID controller. The results, through response and accuracy, prove the preference of PID controller systems in the speed of response and high accuracy with the change or different conditions of the system, i.e., working with linear systems. A simulation is being conducted to verify the use of control systems to improve the performance of servo motors. Algorithms of control systems are developed according to designs based on prior experience. Speed and position control are the most common and used in many applications, which created the need to choose them. To overcome fluctuations and obtain a quick response and a high-precision system used, control systems, as the results proved. The research contribution is developing a design for the user control systems also checking them in simulation with the servo motor system using MATLAB. They test them in the servo motor control as well to test their performance experimentally

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques

Simulation Model of Enhancing Performance of TCP/AQM Networks by Using Matlab

Internet networks are becoming more crowded every day due to the rapid development of modern life, which causes an increase in the demand for data circulating on the Internet. This creates several problems, such as buffer overflow of intermediate routers, and packet loss and time delay in packet delivery. The solution to these problems is to use a TCP/AQM system. The simulation results showed that there were differences in performance between the different controllers used. The proposed methods were simulated along with the required conditions in nonlinear systems to determine the best performance. It was found that the use of optimization Department of Electro-mechanical Engineering, University of Technology - Iraq tools (GA, FL) with a controller could achieve the best performance. The simulation results demonstrated the ability of the proposed methods to control the behavior of the system. The controller systems were simulated using Matlab/Simulink. The simulation results showed that the performance was better with the use of GA-PIDC compared to both FL-PIDC and PIDC in terms of stability time, height, and overrun ratio for a network with a variable queue that was targeted for comparison. The results were: the bypass ratio was 0, 3.3 and 21.8 the settling time was 0.002, 0.055, and 0.135; and the rise time was 0.001, 0.004 and 0.008 for GA-PIDC, FL-PIDC and PIDC, respectively. These results made it possible to compare the three control techniques

Damage patterns recognition in dressing tools using PZT-based SHM and MLP networks

Abstract In order to promoting the optimization of the theme: "grinding-dressing", this study intends to contribute to the fill the gap of works completed with the damage diagnostic systems in dressing tools. For this purpose, this work aims to use neural models based on multilayer Perceptron networks (MLP) to improve the damage pattern recognition in diamond dressing tools based on electromechanical impedance (EMI). Thus, experimental dressing tests were performed with a single-point diamond-dressing tool and a low-cost lead zirconate titanate (PZT) transducer to acquire the impedance signatures at different dressing passes. The proposed approach was able to select the optimal frequency range in impedance signatures to determine the dressing tool condition. To achieve this, representative damage indices in several frequency bands were considered as input to the proposed intelligent system. This new approach open the door to effective implementation of future works for a broader situation in grinding process