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Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Kojima, Manabu Otsuki, Kazuma Suzuki, Masato Abe, Masajiro Baba, Masaaki Yokota, Kazuya Master's Program in Mechanical Engineering Nagaoka University of Technology Nagaoka Japan Nagaoka University of Technology Department of System Safety Engineering Nagaoka Japan Nagaoka University of Technology Department of Mechanical Engineering Nagaoka Japan

ISBN: (纸本)9798350373332

With the development of machine learning, numerical analysis using neural networks has been devised. Remarkably, physics-informed neural networks (PINNs) enable physically consistent numerical analysis by introducing a loss function that conforms to relevant governing equations. Moreover, research is rapidly advancing for the application of PINNs to inverse analysis in areas such as physical property identification. For a PINN to learn governing equations, the weights of the loss functions should be properly determined because they have different roles in components such as boundary conditions, initial conditions, and governing equations. However, weight setting is generally challenging. We propose a loss balancing method considering the procedure for solving partial differential equations. The proposed method is validated through comparisons with conventional solvers. © 2024 IEEE.

关键词： Partial differential equations

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Frequency-Domain Modeling-Free Iterative Learning Control for Point-To-Point Motion 32

Frequency-Domain Modeling-Free Iterative Learning Control fo...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Maeda, Yoshihiro Iwasaki, Makoto Nagoya Institute of Technology Electrical and Mechanical Engineering Program Department of Engineering Nagoya Japan

ISBN: (纸本)9798350399714

The data-driven autonomous feedforward (FF) control design technique known as frequency-domain modelling-free iterative learning control (MFILC) has gained attention for its ability to achieve fine motion control performance without excessive labor. However, the existing frequency-domain MFILC methods that rely on empirical transfer function estimation are not suitable for point-to-point (PTP) motion due to the leakage error that occurs in frequency response function (FRF) estimation. To address this issue, this study proposes an improved frequency-domain MFILC method that employs the differential filtering-based empirical transfer function estimation for FRF estimation. This enhancement enables the proposed method to learn the FF compensation in both reciprocating and PTP motion. Simulations were conducted to evaluate the effectiveness of the proposed method in achieving fast and precise motion control of a galvano scanner. © 2023 IEEE.

关键词： Motion control

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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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Energy consumption simulation for tool path using model of feed drive system 38

Energy consumption simulation for tool path using model of f...

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38th Annual Meeting of the American Society for Precision engineering, ASPE 2023

作者： Kawamura, Naru Hayashi, Akio Morimoto, Yoshitaka Graduate School of Engineering Mechanical Engineering Program Kanazawa Institute of Technology Ishikawa Nonoichi Japan

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Performance analysis on mechanical and machinability attributes of Al6061-B4C-T6 composites processed via hot extrusion

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Proceedings of the Institution of mechanical Engineers, Part B: Journal of engineering Manufacture 2024年第9期238卷 1386-1400页

作者： Tinga, Sibel Karakoç, Halil Yağmur, Selçuk Saravana Kumar, M. Şeker, Ulvi Çıtak, Ramazan Department of Metallurgy and Materials Engineering Gazi University Ankara Turkey Department of Mechanical Program Hacettepe University Ankara Turkey Department of Manufacturing Engineering Gazi University Ankara Turkey Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei Taiwan

In this study, composite materials with Al6061 alloy matrix and B4C particles reinforcement were produced by hot extrusion process. Fabricated composites were examined for the mechanical and machinability attributes. Al6061 alloy powders (4C particles (4C (3%, 6%, and 9% by weight) of and then cold pressed under 200 MPa pressure. The cold pressed powder metal block was extruded hot after preheating at 550°C for 1 h. Further, the composites were subjected to T6 aging heat treatment after hot extrusion. Microstructure, density, hardness, tensile strength, and wear properties were examined. The effects of cutting speed and cutting force on the machinability were also investigated. In addition, surface roughness and chips formation were examined. High density (99.6%) values were achieved with the extrusion process. With increasing B4C particles ratio, the hardness and tensile values were increased which was substantiated by the fracture morphology of the tensile specimens. It has been observed that tool smearing was high in the machining of the low-reinforced (3% B4C) composite. The highest cutting force was measured as 236 N at a feed rate of 0.27 mm/rev and a cutting speed of 250 m/min. It has also been observed that the average surface roughness decreased with increasing cutting speed and it increased with increasing feed rate. © IMechE 2023.

关键词： Microstructure

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An innovative acid-resistant elephant dung biochar powder for fermentative biohydrogen production improvement from food waste slurry

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International Journal of Hydrogen Energy 2025年 138卷 1263-1270页

作者： Pomdaeng, Prakaidao Chu, Chen-Yeon Masa-ad, Anchalee Ngamnurak, Phonsini Setthapun, Worajit Sintuya, Hathaithip Program of Mechanical and Aeronautical Engineering Feng Chia University Taiwan Institute of Green Products Feng Chia University Taiwan Chiang Mai Rajabhat University Thailand Department of Biology Technology Faculty of Technology Khon Kaen University Thailand

This research investigates the innovative application of elephant dung biochar derived from pyrolysis process as an enhancer for biohydrogen production from food waste by dark fermentation process. In this study, batch fermentation experiments have been performed with elephant dung biochar concentrations from 0 to 20 g/L. The highest yields of biogas and biohydrogen achieved were 83.33 and 12.41 mL/g COD, respectively, with the maximum hydrogen concentration reaching 21.79% at the biochar concentration of 10 g/L. Additionally, the total volatile fatty acids produced after fermentation amounted to 2204 mg/L. This study found that biochar can be used for buffering pH and enhancing metabolic processes on the pathway of VFAs to hydrogen, thereby contributing to improved hydrogen yields. This study has demonstrated that biochar produced from elephant dung can significantly improve hydrogen yield from food waste, while higher concentration of biochar may have inhibitory effects. © 2024 Hydrogen Energy Publications LLC

关键词： Biochar Dark fermentation Elephant dung Food waste Hydrogen production

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Multi-criteria decision model for selection of a material suitable to lightning strike protection in aerospace applications

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Materials Today: Proceedings 2022年 59卷 725-733页

作者： Himagireesh, Ch. Ramji, K. Durga Prasad, K.G. Hari Kiran, V. Department of Mechanical Engineering Engineering and Technology Program GayatriVidyaParishad College for Degree & P.G.Courses Andhra Pradesh Visakhapatnam India Department of Mechanical Engineering Andhra University Visakhapatnam India Department of Mechanical Engineering Avanthi Institute of Engineering and Technology Andhra Pradesh India

In order to protect the aerospace structures against electromagneticinterference (EMI) caused by lightning strikes, metallic meshes or foils are currently being used. But the additional weight of metallic meshes cause counterbalance of weight saving imparted by the composite materials. In this context, Al6061 hybrid metal matrix composite specimens with different proportions of SiC, Al2O3 and fly ash particulates as reinforcement materials have been prepared and tested their characteristics suitability to lightning strike protection (LSP). As there is a conflicting nature among these properties a multi-criteria decision model using AHP, Entropy and TOPSIS techniques with a view to select appropriate specimen to meet the objective. The results of the proposed decision model are compared with that of the other methods VIKOR and PROMETHEE so as to validate the results. The same weightages for the properties are used in all the three methods. The proposed decision model is the robust one for ranking of the materials. © 2021

关键词： Aluminum oxide

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Performance analysis of an Injera baking machine by using solar energy

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Materials Today: Proceedings 2022年 56卷 3285-3293页

作者： Suresh, P. Ali, M.D. Irfan Rao, P. Govind Rudrapati, Ramesh Mechanical Engineering Department Bharat Institute of Engineering and Technology Mangalpally Telangana Sagar road Ibrahimpatnam RR Dist India Thermal & Aerospace Program School of Mechanical Chemical and Materials Engineering Adama Science and Technology Ethiopia Mechanical Engineering Department Avanthi Research and Technology Bhogapuram India School of Mechanical Industrial Engineering Bulehora University Bulehora Ethiopia

The majority of Ethiopia's population, primarily women, is susceptible to smoke inhalation during cooking, and they spend the majority of their time striving to collect firewood. Biomass deforestation for cooking harms the rural household economy and contributes to national and global environmental change, such as pollution and health issues. The effort should aim to integrate the Scheffler concentrator with a thermal storage system via the secondary solar cooking reflector in order to stimulate indoor cooking while avoiding concerns associated by carbon inhalation and deforestation. As a result, the Injera bakery system powered by solar thermal energy is born. There is a primary (Scheffler), secondary (reflective), and thermal storage device incorporated, as well as a cooking (pan) mounts. Solid works software was utilized for Scheffler focus and secondary reflector modeling and simulation. The thermal retention capacity of a storage device is determined using heating and cooling curves generated by software modeling and simulation. The findings gained would aid in the development of any comfortable indoor cooking system specifically for rural areas without a grid connection, and as a result of this study, carbon inhalation and deforestation difficulties would be mitigated. Through automation, the output rate would also increase the amount and efficiency of injera. This analysis focuses on the Injera baker concept for domestic applications. © 2021

关键词： Solar energy

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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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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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