Intelligent Wireless Surveillance of Multirate Induction Motors

Recent advances in the automation field provide a wide range of scope in control and monitoring of the industrial systems. A very accurate automation system is on high demand in recent times. This paper mainly deals about remote monitoring and control of the induction motor. The main objective is to develop an embedded system to prevent the occurrence of line fault in a three phase system (say induction motor) and to display and control the parameters voltage, speed and temperature of the three phase system using Zig-bee communication technology. An ARM microcontroller is used in this project, which controls the entire operation of the system, which also communicates various parameters from one part of the system to other through Zig-bee technology. To prevent the issues of poor blunder elements and commotion affectability emerging in functional applications, the plan issue is changed into a proportional Linear Matrix Inequality (LMI) structure to understand a vigorous state criticism roughly by quick yield testing .The control objective is encircled with rise time, overshoot and settling time particulars. Subsequent to arriving at the consistent express the controller ought to look after solidness. To fulfill the above prerequisites a quick yield inspecting control calculation is planned with the end goal that the ideal shut circle conduct and shut circle soundness is accomplished. The exhibition of the framework is broke down for controlling the speed through wireless networks

5G Network in Content Based Emotion Detection by Sentimental Analysis Integrated with Opinion Mining and Deep Learning Architectures

The rapid growth of social networking sites in the Internet era has made them a necessary tool for sharing emotions with the entire world. To extract emotions from text, a variety of tools and approaches are available in fields of opinion mining as well as sentiment analysis. These researches propose novel technique opinion mining based emotion detection from the input social content using deep learning architectures. Here the input has been obtained as social media content based on opinion miningby 5G networks. The input has been processed for noise removal, smoothening and normalization. This processed input has been segmented using Markov model based convolutional neural networks (MMCNN). The segmented data has been classified using Canonical Correlation AnalysisBayesian neural network.An opinion mining method that analyzes statements regarding computer programming and predicts or recognizes their polarity was implemented, along with an earlier module that was integrated into an intelligent learning environment. These three steps made up the creation of the module. We assessed the corpus, text polarity precision, and emotion recognition. Experimental analysis has been carried out for various social media content collected by opinion mining in terms of accuracy, precision, recall, F-1 score, AUC.Proposed technique attained accuracy of 99%, precision of 96%, recall of 96%, F-1 score of 95%, AUC of 89%

Analysis and Realization of CAN Bus Technology in Industrial Conveyors

Automation industry has undergone a drastic development in recent years. In this busy world human intervention in very high critical industrial processes are compensated by the enormous growth of the automation industries. Due to the advancement there is no need for a person to continuously monitor the system instead by implementing automation through latest technologies, a very high efficient operation of the system is possible. Conveyor system plays an important role in automation for material handlin       g and packaging. For the movement of the material, that is transportation, in any processing, the lack of safety factor leads to many limitation in the automation, due to the unachievable efficiency, that is operational efficiency. For that variable speed drive are used for the purpose of modeling the conveyor belt speed, which is controlled through programmable logic controller. The main objective is to develop an embedded system that will automate the boiler control system by monitoring and controlling the temperature and pressure using the CAN bus communication technology. A PIC microcontroller is used in the project to control the entire operation of the embedded system

Performance and Emissions of Nanoadditives in Diesel Engine: A review

Nowadays, the demand for energy and fossil fuels has widely increased as a result of the continuous growth of the population. However, the continued use of traditional fuels as the primary source of energy has resulted in various environmental challenges related to climate change and global warming. This has prompted researchers to look for more eco-friendly and sustainable fuel alternatives with a minimal amount of engine modification and emission treatment techniques. Amongst the suggested alternative fuels, biofuels, biofuel/diesel blends, and the incorporation of nanoparticles into fuels. The nanoparticle diesel additives played a vital role in increasing engine performance as well as retarding harmful emissions such as nitrogen oxides (NOx), carbon monoxide (CO), unburned hydrocarbon (UHC), and particulate matter (PM). Metal-oxides nanoadditive such as aluminum oxide (Al2O3), ceric oxide (CeO2), and titanium dioxide (TiO2) act as oxygen catalysts and promote proper mixing of fuel and air, resulting in more efficient combustion and decreased emissions. The incorporation of nanometal-based additives, including iron (Fe), copper (Cu), and aluminum (Al) accelerated the fuel evaporation rate and increased the probability of fuel ignition. Carbon-based nanoparticles such as carbon nanotubes (CNTs), graphene nanoplatelets (GNPs), and graphene oxide (GO) are promising fuel nanoadditives owing to their metal-free composition. In addition, carbon-based additives enhanced the thermal conductivity of fuel and increased active sites available for chemical reactions, which led to improved engine performance

Determination of Noise Caused by Ventilated Brake Disc with Respect to the Rib Shape and Material Properties Using Taguchi Method

Ventilated brake discs may have various configurations of ribs and can be manufactured from different materials. In order to improve the performance in extreme exploitation conditions, it is necessary that they heat up and wear as little as possible, and that they have good heat dissipation capacity and generate low noise. To achieve this, optimization of the influential parameters is required. In this study, the optimization and the analysis of the frequency value were made on the basis of the influential parameters, such as brake disc vane shape, density, Young’s modulus, and Poisson\u27s coefficient. A numerical investigation was conducted using the ANSYS software package in the MODAL module. In order to better understand which parameter has the greatest influence on the noise formation, the Taguchi method was applied. By applying the Analysis of Variance – ANOVA, the influence of each parameter on frequency, expressed as a percentage, was determined. The obtained results show that the most influential parameter is the shape of the ribs (90.82%), followed by Young’s modulus (8.26%) and density (0.89%)

Performance and Emissions of Nanoadditives in Diesel Engine: A review

Nowadays, the demand for energy and fossil fuels has widely increased as a result of the continuous growth of the population. However, the continued use of traditional fuels as the primary source of energy has resulted in various environmental challenges related to climate change and global warming. This has prompted researchers to look for more eco-friendly and sustainable fuel alternatives with a minimal amount of engine modification and emission treatment techniques. Amongst the suggested alternative fuels, biofuels, biofuel/diesel blends, and the incorporation of nanoparticles into fuels. The nanoparticle diesel additives played a vital role in increasing engine performance as well as retarding harmful emissions such as nitrogen oxides (NOx), carbon monoxide (CO), unburned hydrocarbon (UHC), and particulate matter (PM). Metal-oxides nanoadditive such as aluminum oxide (Al2O3), ceric oxide (CeO2), and titanium dioxide (TiO2) act as oxygen catalysts and promote proper mixing of fuel and air, resulting in more efficient combustion and decreased emissions. The incorporation of nanometal-based additives, including iron (Fe), copper (Cu), and aluminum (Al) accelerated the fuel evaporation rate and increased the probability of fuel ignition. Carbon-based nanoparticles such as carbon nanotubes (CNTs), graphene nanoplatelets (GNPs), and graphene oxide (GO) are promising fuel nanoadditives owing to their metal-free composition. In addition, carbon-based additives enhanced the thermal conductivity of fuel and increased active sites available for chemical reactions, which led to improved engine performance

Optimization of robust and LQR control parameters for half car model using genetic algorithm

To test the performance of the half car system, two types of controller are used, namely Robust H-infinity control and LQR control. Robust H-infinity and LQR controller is designed to control the suspension system and to reduce the vibrations in the car and to improve handling. A half car model is considered in this research to study the effects in passenger owing to different road profiles. The weights of Robust H-infinity and LQR controller are obtained using Genetic Algorithm on a half car model with two different types of usually existing road disturbance.The design parameters of both the active controller varies with various road profiles. This proves that particular design parameters in Robust and LQR controller do not have the ability to adapt to the variations in road surface. Furthermore, active controllers significantly improve the performance of the system in all aspects when compared to passive system. © 2019 SERSC

EFFECT OF MULTIMEDIA ACTIVITIES IN BLENDED LEARNING ON LISTENING SKILLS AND SATISFACTION IN A COLLEGE ENGLISH LANGUAGE COURSE

This study aimed to investigate the effect of proposed multimedia activities in blended learning on students’ listening skills and satisfaction in a college English language course at the Royal University for Woman (RUW) in Bahrain. The study attempted to assess the effects of the proposed strategy on the students’ listening skills and satisfaction with the multimedia listening activities in the OPL (Orientation Program Lower). Results indicated that experimental group students scored higher level in their listening post-test than those in the control group. Experimental group students were satisfied with the courses designed.KEYWORDS: multimedia activities, interactive multimedia, listening comprehension, blended learning

Thermal analysis of both ventilated and full disc brake rotors with frictional heat generation

In automotive engineering, the safety aspect has been considered as a number one priority in development of a new vehicle. Each single system has been studied and developed in order to meet safety requirements. Instead of having air bags, good suspension systems, good handling and safe cornering, one of the most critical systems in a vehicle is the brake system. The objective of this work is to investigate and analyze the temperature distribution of rotor disc during braking operation using ANSYS Multiphysics. The work uses the finite element analysis techniques to predict the temperature distribution on the full and ventilated brake discs and to identify the critical temperature of the rotor. The analysis also gives us the heat flux distribution for the two discs