UTEHY Journal of Applied Science and Technology

APPLICATION OF SIMULATION SOFTWARE IN DESIGN AND CONTROL RESEARCH

Le Thi Minh Tam — 2024-02-25

Simulation is a modern technique widely applied in the field of research, especially in the process of designing and manufacturing robots. When researching robot control, you can perform direct control of the robot or simulation control. Simulation control is to use computational models of the robot’s kinematics and dynamics combined with computer graphics methods to describe the structure and operation of the robot arm. Research on simulating robot movement trajectories on computers helps designers shorten the time to build robots, test the robot’s ability to operate on the screen, and check the robot’s coordination. with other devices in the production process automation system. Within the scope of this article, the presented content includes: general assessment of current robot control and simulation software; Design a model of a 4-degree-of-freedom robot on Solidworks software. Simulating the forward and reverse kinematics of the manipulator using the Simmechanics library in Matlab/Simulink software verifies the accuracy, utility and role of robot simulation software in research, design and manufacturing of robots.

ANALYZING AND CONTROL DESIGN FOR MAGNETIC LEVITATION SYSTEM

Nguyen Thi Luyen — 2024-01-10

This paper focuses on understanding and analyzing a magnetic levitation system consisting of an electromagnet, a permanent magnet sphere, and a sensor. This is an unstable nonlinear system, so we need to build a mathematical model to design a PID controller and a sliding controller for the system. The PID control method is a simple but very useful method, while the sliding control method is more stable, meeting the requirements of fast control. Finally, the study will focus on testing and comparing the effectiveness of these two control methods.

CONTROLLING AND MONITORING PRODUCT CLASSIFICATION SYSTEM USING HMI, PLC S7-1200 VIA PROFINET PROTOCOL

Dam Thi Huong — 2024-02-05

This paper presents the research and construction of a control and monitoring model for a product classification system via the Profinet communication network using two S7-1200 PLCs and an HMI to simulate a real-life industrial automation system. Starting and stopping the system as well as monitoring information about product quantity and status of the field device is done via the HMI screen. Experimental results have been proven by real equipment models located at the Faculty of Electrical and Electronics Engineering, Hung Yen University of Technology and Education. The model supplements the system of teaching equipment for the practical part of the Industrial Information Systems and Production Process Automation module for students majoring in Control and Automation Engineering Technology.

PROPOSED SOLUTIONS FOR MONITORING AND CONTROL OF CASTING STATION USE PLC-WINCC

Nguyen Viet Ngu — 2024-06-10

The monitoring and control system is a system with a wide range from small to large scale. In addition to general standard monitoring and control functions, It also provides many optional functions and can build systems to suit customer needs. In this article, the author proposes a control and monitoring plan for the NEX80IIIT-12E molding machine station of Sews Component Vietnam company to make monitoring and installation more convenient so that when problems arise or adjustments can be made. Adjust parameter settings remotely. These are monitoring and control systems covering from small-scale to large-scale plants. Monitoring of remote place facilities is effectively performed by combining various communication networks including analog dedicated line, IP networks and mobile phone networks, etc. It supports open network systems such as FL-net and enables to build the monitoring and control systems in a flexible manner.

APPLICATION OF FACIAL RECOGNITION USING CONVOLUTIONAL NEURAL NETWORK MODEL IN DORMITORY MANAGEMENT

Pham Tien Quyen — 2024-04-05

Nowadays, Convolutional Neural Networks (CNNs) are widely applied in various fields to help humans detect surface defects, product errors, and perform facial recognition. They are particularly utilized in security surveillance through cameras, such as identifying crimes in law enforcement, image recognition, and monitoring at airports. In this article, the author’s team utilizes a CNN model for security surveillance at the dormitory of the Hung Yen University of Technology and Education to enhance residential security. The results show that the machine learning model developed achieves a facial recognition performance of over 97%. Based on this research outcome, security monitoring at the student dormitory will be implemented through a camera system. This device will send images to a computer, identify and detect individuals not residing in the dormitory, and subsequently issue warnings while storing the images as data for further processing. The findings of this study will contribute to making security monitoring within the dormitory more rigorous, efficient, and convenient compared to traditional security surveillance methods.

A REVIEW OF INTERNET OF SMART INTERNET OF MEDICAL THINGS APPLICATIONS

Dang Van Anh — 2024-05-10

The robust development of smart medical applications and the powerful connectivity of next-generation mobile networks posed significant challenges concerning data accessibility, security, privacy, and e-health data collection for the Internet of Medical Things (IoMT) applications. This work offers a comprehensive vision of the stage-of-the-art IoMT applications on aspects of architecture, applications, and processing challenges of large-scale medical data. Then, we highlight the advantages of fusing edge computing into IoMT applications. Finally, we discuss ongoing issues, challenges, and feasible study directions for future smart IoMT applications.

EXPLORING THE EFFECTIVENESS OF DATA AUGMENTATION TECHNIQUES IN MACHINE LEARNING AND DEEP LEARNING: APPLICATION TO IMAGE RECOGNITION

Dao Thi Le Thuy — 2024-06-05

In this study, we explore data augmentation techniques aimed at enhancing the accuracy of image recognition models in machine learning and deep learning. By applying methods such as rotation, scaling, flipping, and advanced techniques like GAN-based augmentation, we address challenges related to data scarcity and imbalance. Experimental results on the Dogs vs. Cats dataset show significant improvements in model performance, with combined data augmentation techniques achieving the highest accuracy of 90.83%. This study underscores the critical role of data augmentation in improving model robustness and generalization, especially in scenarios with limited data. We also discuss the implications of these findings for future research in the field of image recognition.

SIMULATING THE DIGITAL SIGNATURE PROCESS BASED ON THE RSA-PSS DIGITAL SIGNATURE SCHEME

Dam Duc Trung — 2024-06-20

RSA-PSS is a Probabilistic Sign Scheme based on the RSA digital signature, proposed by Mihir Bellare and Phillip Rogaway. This digital signature scheme is an update of their results for industry standards. RSA-PSS has recently been included in RSA Security’s software tools, RSA BSAFE Crypto-C and Crypto-J toolkits. In addition, the RSA-PSS schema can be extended to add message recovery functionality. Based on this idea, the authors have developed an application to digitally sign text content according to the RSA-PSS digital signature scheme with a length to ensure safety as recommended by NIST.

PERFORMANCE COMPARISON BETWEEN HIVE AND SPARK IN STRUCTURED BIG DATA ANALYSIS

Do Thi Dao — 2024-06-24

With the explosion of IoT devices, the massive amount of data generated has rendered traditional data analysis platforms inadequate. Big data analytics platforms have emerged, enabling organizations to uncover hidden values within the data and make swift business decisions. Among these, Apache Hive and Apache Spark have risen as two modern data analysis platforms commonly used for analyzing structured big data. Several studies have compared these two platforms and found that in most cases, SparkSQL in Spark is faster than Hive on MapReduce. However, in some cases involving queries with lots of joins operations among large data tables, SparkSQL is slower than Hive on MapReduce. Recently, SparkSQL has undergone numerous optimization techniques that could lead to better query performance, such as upgrading the query processing scheduler optimizer. In this paper, we present the performance comparision between Hive on MapReduce and SparkSQL. To achieve this, we study the implementation of performance evaluation for big data queries using BigBench and the performance analysis tool PAT. We aggregate and analyze important performance parameters, including query execution time, disk usage, memory usage, CPU usage, and the amount of data read/written over the network. The experimental results show that Spark SQL outperforms Hive on MapReduce with all 20 query sets of BigBench.

APPLYING ENSEMBLE LEARNING FOR IMBALANCED DATA

Ngo Thi Lan Anh — 2024-06-26

Nowadays, the application of machine learning methods for data analysis has become a significant trend, unlocking great potential in extracting information from data. However, in practice, many datasets exhibit class imbalance, such as problems related to predicting errors in banking transactions or classifying cancer patients, which poses challenges in building accurate predictive models. This imbalance often degrades the performance of machine learning models, especially in predicting events related to minority classes. In this study, we focus on applying the Ensemble Learning method, which combines multiple predictive models to improve performance, for imbalanced datasets.

We approach this problem by using some common techniques such as Bagging, Boosting, and Stacking from the Ensemble Learning method to harness the strengths of different models. This method not only aims to enhance the model’s accuracy but also to minimize the impact of data imbalance on the prediction process. The results of experiments on real-world datasets have demonstrated the effectiveness of the proposed method in addressing the issue of data imbalance. This proposal not only opens the door for the deployment of machine learning models in fields where data imbalance is common but also contributes to the ongoing development of machine learning and data mining.

DESIGN, ASEMBLE AND PROGRAM AUTOMATED GUIDED VEHICLES NAVIGATION WITH DIGITAL COMPASS

Nguyen Thi Tham — 2024-04-10

Automated guided vehicles (AGVs) are considered as an enabling technology to realize smart manufacturing in the Industrial 4.0 era. Indoor navigation was one of the most important tasks for the mobile systems as they were often designed to move from one location to another location autonomously without contacting the surrounding objects along the moving path in a usually dynamic and complex indoor environment. The article presented the design of a self-driving car model with electrical equipment - control based on simple and cheap components such as digital compass, Arduino Nano microcontroller, stepper motor. The numerical results on the manufacturing model show that the automated guided vehicle operates stably and moves according to the preset route. This result can open up the direction of applying digital compass in navigating autonomous vehicles moving in production workshops.

RESEARCH ON THE APPLICATION AND EVALUATION OF THE EFFICIENCY OF STATCOM IN VOLTAGE STABILITY FOR 22KV DISTRIBUTION NETWORK IN VAN GIANG DISTRICT, HUNG YEN PROVINCE

Nguyen Thi Van Anh — 2024-06-25

Flexible Alternative Current Transmission System (FACTS) devices are controllers based on power electronics. They have been demonstrated to improve transient stability and help damp electromechanical oscillations in distribution power systems. This article presents the results of using a Distribution Static Compensator (D-STATCOM) with a voltage source inverter (VSC) to enhance stability and improve voltage quality in the 22kV distribution grid of Van Giang District. D-STATCOM compensator, using PI control, is applied to stabilize and improve voltage at load busbars in the distribution power system. Simulation results using Matlab-Simulink software demonstrate the effectiveness of the D-STATCOM compensator in stabilizing amplitude and improving voltage quality during small disturbances in steady state as well as increasing amplitude and reducing voltage fluctuations in the distribution network.

DESIGN AND STABILIZATION CONTROL OF ELECTRIC HEATING FURNACE TEMPERATURE USING DIGITAL PID CONTROLLER

Nguyen Thi Luyen — 2024-06-26

The electric heating furnace is a nonlinear system, making traditional methods for identifying and finding parameters for the temperature stabilization controller time-consuming and prone to errors. This paper introduces the integration of Arduino with Matlab to facilitate the identification process and parameter finding for the controller more effectively, making temperature stabilization control more convenient and accurate. First, the paper describes the hardware construction of the system, including the design of the furnace with LM35 temperature sensors and the use of Arduino to read temperature data. Subsequently, the connection between Matlab and Arduino is illustrated for data processing and parameter determination of the PID controller. Two main methods used for finding PID parameters are the Ziegler-Nichols method and the tuning method. The results indicate that the digital PID controller not only helps minimize temperature fluctuations but also improves the system’s energy efficiency. Practical experiments and simulations have demonstrated that integrating Arduino and Matlab in the heating furnace control system is an effective solution, yielding more optimal results compared to traditional methods.

CFD SIMULATION ANALYSIS OF THERMAL COMFORT IN A SMALL OFFICE

Nguyen Ba Chien — 2024-06-05

This study presents the model and results of thermal comfort assessment for a small office in Vietnam. Using CFD simulation, the effect of temperature field, airflow, wind speed and radiation on thermal comfort in a office was analyzed. The results show that, with the current design, 50 % of users are satisfied with the thermal comfort conditions in areas near the air supply, while this is only 20 % in areas far from the air supply. In addition, the arrangement of equipment in the room, the layout and the supply air flow all have a significant influence on temperature distribution, air flow distribution and thermal comfort index.

OPTIMIZATION AND STANDARDIZED POST-PROCESSOR DEVELOPMENT FOR NC MACHINING PROGRAMS ON CNC MACHINE TOOLS

Trinh Thi Mai — 2024-05-22

The research focuses on developing a process using Mastercam software to create a post-processor supporting the generation of machining programs for the CNC milling machine X.mill M640. The objective is to handle the unique program structure of the machine into a post-processor generated from available software, ensuring smooth operation during machining without errors. This is a crucial task in the field of mechanical machining, aiming to optimize manufacturing accuracy, surface quality, and streamline the technological process. Additionally, integrating with CAD/CAM/CNC technology, creating a standardized post-processor will enhance productivity and reduce production costs.