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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Kosiyanurak, Akkharachai Pothi, Nattachai Prasoetkarn, Natthawut Srisertpol, Jiraphon Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand

ISBN: (纸本)9781643685403

This paper investigates the estimation of a straightforward mathematical model tailored for overseeing and regulating the motion of an AGV (Automated Guided Vehicle) equipped with differential drive systems. The mathematical model delineates the correlation between the input voltage signal of the DC motor and the resultant distance output, empirically tested within an open-loop system. This methodology facilitates the development of precise mathematical models aimed at mitigating errors in powertrains and mechanical motion components, including gears, chains, and ground-contacting tires, along with system friction. Moreover, a P controller system is devised to oversee the AGV motion. The stability and control efficacy are assessed through practical experimentation on the AGV's ability to attain predefined distances. Tests were conducted under two distinct conditions: case 1) AGV operation without any payload and case 2) AGV operation while bearing a 14 kg payload. The system's response to the input distance was meticulously observed. The average distance error is calculated at 1.74% of the designated control distance (2m, 3m, and 4m) across all cases. In the absence of a load (case 1), the average distance error remains consistent at 1.74% of the control distance, showcasing a motor speed response of 23.76 RPM (with a rise time of 2.1 s). Conversely, when subjected to a 14 kg payload (case 2), the average distance error marginally increases to 1.76% of the control distance, with a corresponding motor speed response of 23.71 RPM (and a rise time of 2.2 s). These results show the effectiveness of the control system, facilitated by the estimation of a simplistic mathematical model tailored specifically for AGV operations. Â© 2024 The Authors.

关键词： Closed loop systems

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Exploring Classification, Size, and Quality of Mangifera Indica L. Through Image Processing and AI Techniques 2

Exploring Classification, Size, and Quality of Mangifera Ind...

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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Wanthong, Irin Sri-On, Theeraphat Seangsri, Soontaree Khaengkarn, Sorada Srisertpol, Jiraphon Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology Nakhon Ratchasima Thailand Department of Mechatronics and Robotics Engineering School of Engineering and Innovation Rajamangala University of Technology Tawan-ok Chonburi Thailand

ISBN: (纸本)9781643685403

This paper introduces methods for efficiently classifying mangoes intended for export, a market valued at approximately 4,500 million baht annually. The classification process is divided into two primary components: size categorization and quality assessment. The first phase involves categorizing mango sizes into four distinct categories (M, 1L, 2L, 3L), while the second phase focuses on assessing mango quality, particularly detecting anthracnoseâ€"a prevalent disease affecting mangoes. This detection is achieved through image processing techniques, where images are converted into binary representations and analyzed using both Artificial Neural Networks (ANNs) and Convolutional Neural Networks (CNNs). Comparative analysis reveals that CNN outperforms ANN in size classification, achieving a remarkable train accuracy of 99.16% and a test accuracy of 88.0%. Furthermore, in quality classification, CNN demonstrates a train accuracy of 91.0% and a test accuracy of 88.0%. These findings underscore the effectiveness of CNN techniques in accurately classifying mangoes for export, thereby facilitating improved quality control and market competitiveness. Â© 2024 The Authors.

关键词： Convolutional neural networks

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Efficiency improvement of automated production line by conversion of subroutine configuration

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International Journal of Advanced Manufacturing technology 2023年第7-8期129卷 3537-3547页

作者： Chen, Po-Tuan Cheng, Yu-Lin Department of Vehicle Engineering National Taipei University of Technology Taipei Taiwan Technical and Vocational Program in Mechatronics National Taipei University of Technology Taipei Taiwan

programmable control for automated production is an essential technology for industrial development. In addition, a flexible main control system and scheduling management can significantly improve production efficiency. This study improved a programmable logic controller (PLC) subroutine module and communication methods using the modular production system (MPS) automated workstation developed by Festo to optimize the process of production. First, a simulated production line with feeding, transportation, discrimination, and processing stations was set up in a laboratory. Experiments and tests were performed, and data were collected. Consequently, different program editing and planning methods, such as program modularization, step system, and subroutines of the busbar, were proposed for PLC and automation systems. The design with clearer and more modularized subroutines was used to improve the production line performance and stability and achieve dynamic scheduling to optimize the production line efficiency to meet the demands. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

关键词： programmable logic controllers

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Separation of microalgae from bacterial contaminants using spiral microchannel in the presence of a chemoattractant

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Bioresources and Bioprocessing 2024年第1期11卷 511-525页

作者： Leticia F.Ngum Y.Matsushita Samir F.El-Mashtoly Ahmed M.R.Fath El-Bab Ahmed L Abdel-Mawgood Institute of Basic and Applied Sciences Biotechnology ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Institute of Basic and Applied Sciences Nanoscience ProgramEgypt-Japan University of Science and TechnologyAlexandria 21934Egypt Mechatronics and Robotics Engineering Department Egypt-Japan University of Science and TechnologyAlexandria 21934Egypt.

Cell separation using microfluidics has become an effective method to isolate biological contaminants from bodily fluids and cell cultures,such as isolating bacteria contaminants from microalgae cultures and isolating bacteria contaminants from white blood *** this study,bacterial cells were used as a model contaminant in microalgae culture in a passive microfluidics device,which relies on hydrodynamic forces to demonstrate the separation of microalgae from bacteria contaminants in U and W-shaped cross-section spiral microchannel fabricated by defocusing CO_(2) laser *** a flow rate of 0.7 ml/min in the presence of glycine as bacteria chemoattractant,the spiral microfluidics devices with U and W-shaped cross-sections were able to isolate microalgae(Desmodesmus sp.)from bacteria(***)with a high separation efficiency of 92%and 96%*** the same flow rate,in the absence of glycine,the separation efficiency of microalgae for U-and W-shaped cross-sections was 91%and 96%,*** was found that the spiral microchannel device with a W-shaped cross-section with a barrier in the center of the channel showed significantly higher separation *** microchannel chips with U-or W-shaped cross-sections were easy to fabricate and exhibited high *** these advantages,these devices could be widely applicable to other cell separation applications,such as separating circulating tumor cells from blood.

关键词： W-shaped cross-section CO_(2)laser ablation Glycine Separation efficiency Removal ratio

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Friction Model Parameter Identification of a Servomotor with Genetic Algorithms

Friction Model Parameter Identification of a Servomotor with...

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2023 Advances in Science and engineering technology International Conferences, ASET 2023

作者： Ahmad, Saleh Alhashmi, Ahmad Khan, Najeeb U. Higher Colleges of Technology Mechatronics Engineering Technology Program Dubai United Arab Emirates Mechanical Engineering Technology Program Higher Colleges of Technology Dubai United Arab Emirates

ISBN: (纸本)9781665454742

Friction has been identified as one of the primary contributors to the problems associated with motion control system accuracy. Several approaches have been offered to identify friction parameters, such as direct measurement, trial-and-error, and so on. However, obtaining the proper and exact values for friction model parameters is a challenging task. The aforementioned methods have large time consumption and likely yield experimental errors. In this paper, a Genetic Algorithm is used to identify friction model parameters for a servomotor system, namely, the Quanser QUBE-Servo 2. Both simulation and experiment findings demonstrate that a successful implementation of friction parameter identification can be done in a short amount of time while maintaining high accuracy. © 2023 IEEE.

关键词： Genetic algorithms

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Exploring Techniques for Estimating Distance in Leader-Follower AGV Systems 2

Exploring Techniques for Estimating Distance in Leader-Follo...

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2nd International Conference on Mechanics, Electronics, Automation and Automatic Control, MEAAC 2024

作者： Muenngam, Chetsadakorn Khaewnak, Nopparut Srisertpol, Jiraphon Prasoetkarn, Natthawut Mechatronics Engineering Program School of Mechanical Engineering Suranaree University of Technology 111 University avenue Muang district Nakhon Ratchasima30000 Thailand

ISBN: (纸本)9781643685403

The application of Automated Guided Vehicles (AGVs) for workpiece transportation in production processes is commonplace, particularly in the context of Industry 4.0. However, the high cost associated with AGVs presents a significant challenge. This paper proposes an approach to AGV tracking using a combination of camera-based QR code detection and ultrasonic sensors. The objective is to regulate the distance between leading and following AGVs, thereby addressing the operational costs associated with expensive equipment. Experimental investigations were conducted to assess the performance of QR symbols and color bars under varying lighting conditions, ranging from 200 lux to 650 lux. Accurate distance measurements were achieved within a range of 150 cm. In lower lighting conditions (100 lux to 250 lux), the RGB color bar detection failed at distances below 40 cm, whereas QR Code detection remained robust. Angle measurements demonstrated accurate readings up to 30 degrees from the camera's center, within distances of 50 to 125 cm, with an anticipated deviation of no more than 0.5 degrees. Subsequently, QR code symbols were chosen as the experimental control symbol, complemented by ultrasonic sensors for inter-vehicle distance maintenance. During practical testing, if the measured distance falls below 60 cm. while moving in a straight line, the motor ceases operation. Conversely, if the distance exceeds 80 cm, the motor activates, allowing the follower AGV to uphold the specified distance behind the leader AGV. Â© 2024 The Authors.

关键词： Ultrasonic sensors

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Model Predictive Control for the Level Control Loop of the FESTO MPS PA Compact Workstation

Model Predictive Control for the Level Control Loop of the F...

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2022 Advances in Science and engineering technology International Conferences, ASET 2022

作者： Ahmad, Saleh Higher Colleges of Technology Mechatronics Engineering Technology Program Dubai United Arab Emirates

ISBN: (纸本)9781665418010

Model Predictive Control methods have been utilized in process manufacturing since the early 80s and provide several advantages for the field of process control. This paper presents the design and the experimental implementation of a model predictive control for the FESTO process control station's level control loop. First, utilizing Pseudo-Random Binary Signal input, a dynamic model of the plant is developed. The model will be used for the design of the model predictive control strategy. LabVIEW software was chosen to implement the model predictive control strategy because it can provide a graphic representation of the plant's operation and provides ActiveX controls for interacting with the FESTO process control station. Finally, concluding remarks about the performance and the experiment results of the designed controller and comments were provided. © 2022 IEEE.

关键词： Model predictive control

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The Design of a Drone-Assisted System for Large Wildlife Vaccination Shooting Based on AI Image Identification technology 20

The Design of a Drone-Assisted System for Large Wildlife Vac...

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20th IEEE International Conference on e-Business engineering, ICEBE 2024

作者： Tsai, Yao-Yu Tsai, Yao-Chuan Tai, Chang-Hsien Chen, Chen-Chih Hsu, Uzu-Kuei National Chung Hsing University National Pingtung University of Science and Technology Sustainable Circular Economy R&d Center Department of Bio-Industrial Mechatronics Engineering Pingtung Taichung Taiwan National Chung Hsing University Department of Bio-Industrial Mechatronics Engineering Taichung Taiwan College of Biomedical Engineering and Technology Tzu Chi University Hualien Taiwan Institute of Wildlife Conservation National Pingtung University of Science and Technology Pingtung Taiwan Program of Artificial Intelligence and Mechatronics National Pingtung University of Science and Technology Pingtung Taiwan

ISBN: (纸本)9798350365856

This study designs a UAV -assisted system integrated with AI image recognition technology to alleviate the difficulty for operators in stabilizing the UAV and accurately administering vaccines. The system uses thermal imaging modules and AI recognition systems to lock onto and track target animals in real-time. Utilizing MAVLink, the UAV adjusts its flight path based on the dynamic behavior of the animals, ensuring that the target remains within shooting range for precise vaccine administration. This technology not only improves the efficiency and accuracy of wildlife vaccination but also significantly reduces the workload on operators, providing a forward-looking solution for wildlife management. © 2024 IEEE.

关键词： Thermography (imaging)

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Behavior-Based Control with Learning from Demonstration for Path Following Applied to Mobile Robots Soccer

Behavior-Based Control with Learning from Demonstration for ...

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IEEE Latin American Robotics Symposium, LARS

作者： Matheus de S. Luiz M. A. Pastrana Guilherme Achilles de Oliveira e Aguiar R. B. Costa Luiz F. Rodrigues e Silva Faculty of Gama Electronics Engineering Undergraduate Program Department of Mechanical Engineering Mechatronics Graduate Program Faculty of Technology Mechatronics Engineering Undergraduate Program Faculty of Gama Aerospace Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

Learning from Demonstration (LfD) enables robots to learn new tasks through an imitation process. This methodology can be combined with Behavior-Based Control (BBC), which facilitates the abstraction of behaviors for the robot by dividing them into micro-behaviors. These can be implemented using Artificial Neural Networks trained by bio-inspired algorithms. In this work, a novel methodology based on the LfD and BBC methods is proposed for controlling soccer robots, specifically for the Very Small Size Soccer (VSSS) category, which demands quick and dynamic responses. Simulations using CoppeliaSim were conducted to demonstrate how the proposed methodology can be used for path planning and path-following problems in the IEEE VSSS category.

关键词： Measurement Training Heuristic algorithms Artificial neural networks Turning Robustness Path planning Robots Optimization Sports

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Surface Defects Detection of Cylindrical High-Precision Industrial Parts Based on Deep Learning Algorithms: A Review

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Operations Research Forum 2024年第3期5卷 58页

作者： Wei, Li Solihin, Mahmud Iwan Saruchi, Sarah ‘Atifah Astuti, Winda Hong, Lim Wei Kit, Ang Chun School of Computer Science and Technology (School of Software) Guangxi University of Science and Technology Guangxi 545006 China Faculty of Engineering Technology and Built Environment UCSI University Kuala Lumpur 56000 Malaysia Faculty of Manufacturing and Mechatronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan 26600 Malaysia Computer Engineering Department Automotive and Robotics Engineering Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

High-precision cylindrical parts are critical components across various industries including aerospace, automotive, and manufacturing. Since these parts play a pivotal role in the performance and safety of the systems they are integrated into, they are often subject to stringent quality control measures. Defects on the interior and exterior wall surfaces of these cylindrical parts can severely undermine their function, leading to degraded performance, increased wear, and even catastrophic failures in extreme cases. This article aims to comprehensively summarize the task definition, challenges, mainstream methods, public datasets, evaluation metrics, and other aspects of surface defect detection for high-precision cylindrical parts, in order to help researchers quickly grasp this field. Specifically, the background and characteristics of industrial defect detection are first introduced. Owing to the unique geometric features of cylindrical part surfaces, algorithms and equipment for image data acquisition used in surface defect detection are elaborated in detail. This article presents an extensive overview of state-of-the-art surface defect detection techniques designed for high-precision cylindrical components, all rooted in deep learning. The methods are systematically classified into three main categories: fully supervised, unsupervised, and alternative approaches, based on their data labeling strategies. Additionally, the paper conducts a comprehensive analysis within each category, shedding light on their unique strengths, limitations, and practical use cases. Concluding the discussion, the paper provides insights into future development trends and potential research directions in this field that will lead to manufacturing innovation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Anomaly detection Computer vision Deep learning Defect detection High-precision cylindrical parts Image processing Optical illumination

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