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IEEE International Conference on Systems, Man and Cybernetics

作者： Marcelo Contreras Christian Flores Javier Andreu-Perez NODE lab at the Mechanical Engineering University of Alberta Edmonton Canada Department of Mechatronics Engineering UTEC Lima Peru Centro BIO UTEC and Department of Electrical and Mechatronic Engineering UTEC Lima Peru DSPCom Laboratory from the Department of Electrical Engineering University of Campinas Campinas Brazil Centre for Computational Intelligence University of Essex Colchester United Kingdom

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The Steady-State Visual Evoked Potential (SSVEP) is a robust method for creating a fast Brain-Computer Interface (BCI); however, the time window of Electroencephalography (EEG) trials has to be reduced to improve the BCI's speed. This reduction leads to a decrease in the Signal-to-noise ratio (SNR), making it more difficult to classify these signals accurately. Conversely, combining Fuzzy Neural Block (FNB) that includes Type-l Fuzzy (T1F) in deep learning architecture has improved classification accuracy over data obtained in noisy environments. However, T1F has limitations in accurately modeling uncertainty and handling complex systems compared to Interval Type-2 Fuzzy (IT2F), which is particularly suitable for applications where robustness, adaptability, and accuracy are crucial. In this work, we proposed a deep learning framework that integrates the FNB using IT2F called FNB- IT2F. It is included parallel to the linear and final layers to assess their effectiveness. Thus, this study presents a unification of EEG- TCNet-LSTM with FNB-IT2F, which we call EEG- TCNet-LSTM-FNB-IT2F (i.e. EEG- TCF2Net). Our results reported a maximum recog-nition accuracy of 51.0% to 76.5% using the proposed method of EEG- TCF2N et in a subject-independent classification across all 10 subjects for 0.2 to 0.5 s time window. Overall, including FNB- IT2F in this deep learning architecture outperformed those without it, as well as baseline methods such as Filter-Bank Canonical Correlation Analysis (FBCCA) [1] and Task-related component analysis (TRCA) [2].

关键词： Visualization Accuracy Uncertainty Brain modeling Electroencephalography Brain-computer interfaces Decoding Steady-state Complex systems Signal to noise ratio

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Batch constrained multi-objective Bayesian optimization using the example of ultrasonic wire bonding

Batch constrained multi-objective Bayesian optimization usin...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent mechatronics

作者： Fabian Reiling Christian Henke Matthias Hunstig Stefan Gröger Ansgar Trächtler department Scientific Automation Fraunhofer Institute for Mechatronic Systems Design Paderborn Germany Deputy Head of Research at Hesse GmbH Paderborn Germany Head of Chair of Control Engineering and Mechatronics Paderborn Germany

ISBN: (数字)9798350355369

ISBN: (纸本)9798350355376

Setting optimum process parameters for complex manufacturing processes such as ultrasonic wire bonding is already challenging for one target variable. Due to numerous influencing physical factors, such processes often lack the necessary detailed physical models. Due to the lack of these models, such processes cannot be adjusted to an optimum using classic optimization methods. In manufacturing processes in particular, the process must be optimized with regard to several objectives such as process time or quality. A popular method for optimizing such processes without models is multi-objective Bayesian optimization. For this purpose, surrogate models in the form of Gaussian processes are used in combination with a multi-objective acquisition function. In real processes, parallel function evaluation offers advantages in terms of trial efficiency and scalability. In this paper, we present a new algorithm for batch-constrained Bayesian multi-objective optimization. With this algorithm, an arbitrary number of function evaluations per iteration can be specified, whereby a more efficient determination of the Pareto front approximation can be achieved in real applications. For this purpose, the Expected Hypervolume Improvement is extended by a term to consider a quality criterion. Using the ultrasonic wire bonding process as an example, we experimentally prove that the proposed framework is able to approximate the Pareto front of the system with only a few function evaluations. For this purpose, the process capability index should be maximized and the process time minimized.

关键词： Manufacturing processes mechatronics Scalability Optimization methods Predictive models Approximation algorithms Acoustics

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Strong-Weak Digital Twins: A New Technique for Constructing Manufacturing Equipment Agents in Cloud-Edge Collaborative Manufacturing

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SSRN 2024年

作者： Guo, Liang Li, Yuantong Xu, Xun Luo, Longkun Wan, Changcheng School of Mechatronic Engineering Southwest Petroleum University Chengdu China Sichuan Shared Platform for Oil and Gas Equipment Technology Chengdu China Department of Mechanical and Mechatronics Engineering The University of Auckland Auckland New Zealand School of Mechanical Engineering Xihua University Chengdu China University of Guelph Canada

To address the challenges of encapsulating and integrating distributed heterogeneous manufacturing equipment in cloud manufacturing, the heavy reliance of manufacturing service systems on cloud computing power, and the lack of autonomy in executing cloud services, a novel networked service manufacturing model called Cloud-edge Collaborative Manufacturing (CeCM) has been proposed. This model utilizes cloud service platform and edge IoT devices to form an intelligent manufacturing system, utilizing big data and other advanced information technologies to closely coordinate cloud systems with underlying manufacturing resources, thereby providing efficient and convenient manufacturing services to users. To resolve the issue of the lack of intelligent collaborative vehicles for cloud-edge collaboration and business collaboration among various geographically distributed and networked manufacturing equipment within CeCM system, the concept of Strong-Weak digital twins (SWDTs) is introduced. Based on cloud-edge collaboration and digital twin technology, a framework for constructing manufacturing equipment agents based on SWDTs is proposed. This framework includes the manufacturing equipment layer, strong twin layer, weak twin layer, and agent layer. The six major features, eight synergy modes, and four categories of enabling technologies for SWDTs are summarized, and the application of SWDTs to collaborative interaction between multiple agents in CeCM is investigated. Finally, using a 3D printer as a case study, the construction of a 3D printing agent based on SWDTs is demonstrated, validating the feasibility of the proposed technology. This technique provides a new method for realizing the autonomy, networking, intelligence, and collaboration of manufacturing equipment in CeCM © 2024, The Authors. All rights reserved.

关键词： Smart manufacturing

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A review for design,mechanism,fabrication,and application of magnetically responsive microstructured functional surface

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International Journal of Extreme Manufacturing 2025年第1期7卷 96-128页

作者： Jian Wang Xingyi Song Chaochao Wang Yumei Zhou Ri Chen Yong Yang Bin Liu Yihao Zheng Hui Li Wei Zhou Lelun Jiang Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument School of Biomedical EngineeringShenzhen Campus of Sun Yat-sen UniversityShenzhen 518107People’s Republic of China School of Mechatronic Engineering Guangdong Polytechnic Normal UniversityGuangzhou 510665People’s Republic of China School of Mechanical and Electrical Engineering Guangdong Polytechnic of Industry and CommerceGuangzhou 510550People’s Republic of China Mechanical&Materials Engineering Department Worcester Polytechnic InstituteWorcesterMA 01609United States of America Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control EngineeringShenzhen UniversityShenzhen 518060People’s Republic of China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005People’s Republic of China

Magnetically responsive microstructured functional surface(MRMFS),capable of dynamically and reversibly switching the surface topography under magnetic actuation,provides a wireless,noninvasive,and instantaneous way to accurately control the microscale engineered *** the last decade,many studies have been conducted to design and optimize MRMFSs for diverse applications,and significant progress has been *** review comprehensively presents recent advancements and the potential prospects in *** first classify MRMFSs into one-dimensional linear array MRMFSs,two-dimensional planar array MRMFSs,and dynamic self-assembly MRMFSs based on their ***,an overview of three deformation mechanisms,including magnetically actuated bending deformation,magnetically driven rotational deformation,and magnetically induced self-assembly deformation,are *** main fabrication strategies employed to create MRMFSs are summarized,including replica molding,magnetization-induced self-assembly,laser cutting,and ferrofluid-infused ***,the applications of MRMFS in droplet manipulation,solid transport,information encryption,light manipulation,triboelectric nanogenerators,and soft robotics are ***,the challenges that limit the practical applications of MRMFSs are discussed,and the future development of MRMFSs is proposed.

关键词： functional surfaces microstructures magnetic actuation manipulation

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Multi-Response Optimization of M2 Steel Coatings Deposited by Co-Axial Laser Cladding on A2 Steel Tool Surfaces

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SSRN 2023年

作者： Geng, Heran Alfano, Marco Yuan, Junfeng School of Mechatronic Engineering China University of Mining and Technology Xuzhou221116 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Laser cladding is a highly effective technique used in additive manufacturing to enhance the surface properties of workpieces. It is employed to improve wear resistance, corrosion resistance, and high-temperature resilience of materials. This study explores the utilization of laser cladding technology to repair the surface of AISI A2 tool steel by applying a coating of M2 steel. Sixteen experiments were designed using an orthogonal methodology to investigate the intricate relationship between various processing parameters, including laser power, scan speed, powder feed rate, and overlapping ratio. These parameters were examined in conjunction with key mechanical properties of the coating, such as micro-hardness, friction-wear characteristics, and shear bond ***, analytical techniques such as Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and X-ray Diffraction (XRD) were employed to gain insights into the microstructure of the coatings and elucidate the underlying failure modes. The results reveal that laser power significantly influences the friction and wear performance of the coating, while the overlapping ratio has a notable impact on both frictional performance and bond strength. Furthermore, all the process variables exhibited a considerable effect on the micro-hardness of the coatings. Shear testing of the coatings indicated a tendency towards a brittle fracture mode within the coating, with the dominant wear mechanism involving a combination of abrasive and oxidative ***, a TOPSIS-Grey Relational Analysis (GRA) method was utilized to identify the optimal process parameters. These optimal parameters were determined to be a laser power of 1200 W, a scan speed of 5 mm/s, a powder feed rate of 14 g/min, and an overlapping ratio of 30%. Subsequent validation experiments carried out with these parameters demonstrated superior performance compared to the optimal group identified in the orthogonal experiment. © 20

关键词： Laser cladding

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PIEZOELECTRIC SHUNT DAMPING IN CRYOGENIC CONDITIONS: APPLICATION TO A FLEXURE-BASED MECHANISM 36

PIEZOELECTRIC SHUNT DAMPING IN CRYOGENIC CONDITIONS: APPLICA...

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36th Annual Meeting of the American Society for Precision engineering, ASPE 2021

作者： Ambaum, N. Vermeulen, J.P.M.B. Mokrani, B. Department of Mechanical Engineering Control Systems Technology group – Mechatronic Systems Design Eindhoven University of Technology Eindhoven Netherlands Mechatronics Department ASML Netherlands Veldhoven Netherlands

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Experimental and Numerical Investigation on Thermal Characteristics of 2×3 Designed Battery Module

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SSRN 2023年

作者： Choudhari, Vivek G. Dhoble, Ashwinkumar S. Panchal, Satyam Fowler, Michael Fraser, Roydon Department of Mechanical Engineering Visvesvaraya National Institute of Technology Nagpur India Department of Mechanical and Mechatronics Engineering University of Waterloo ON Canada Chemical Engineering Departments University of Waterloo 200 University Avenue Wes WaterlooON Canada Mechanical and Mechatronic Engineering Department University of Waterloo 200 University Avenue West WaterlooON Canada

This paper demonstrates an extensive study on the thermal impacts of Lithium-ion battery module in an electric vehicle. The Li-ion battery module is arranged in a 2×3 pattern in which all six cylindrical cells are arranged in parallel. Temperature characteristics at different locations like the bottom, top, and side of the battery surface at distinct discharge rates are examined. It is observed that maximum temperature occurred at the side of the battery surface. Subsequently, a numerical analysis is carried out to examine the thermal behaviour of a 2×3 battery module. Further, attempts are made to improve the thermal behaviour of the existing battery module at different discharge rates using PCM. It is observed that PCM based battery module reduces the maximum temperature by 5.12% and 7.17% at 3C and 4C discharge rates respectively as compared with a conventional battery module. Results also illustrate that variation in fin spacing inside the battery module helps to provide an optimized PCM based battery module. © 2023, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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Data Acquisition System for Web-based Multi-modal Data Repository 7

Data Acquisition System for Web-based Multi-modal Data Repos...

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7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021

作者： Rushambwa, Munyaradzi Charles Mukherjee, Anirban Maity, Maitreya Palaniappan, Rajkumar Vijean, Vikneswaran Ghulam Nabi, Fizza Harare Institute of Technology Electronic Engineering Harare Zimbabwe Indian Institute of Technology-KGP Electrical Engineering Kharagpur India Ama International University College of Engineering Department of Mechatronics Engineering Salmabad Bahrain University of Malaysia Perlis Mechatronic Engineering Perlis Malaysia Lahore Pakistan

ISBN: (纸本)9781665441261

The multimodal medical data with annotation helps to build different automated algorithms. Each reported work has used a specific disease database and developed a CAD based on the considered database. Therefore, the availability and quality of medical database play the most crucial role in developing any CAD. However, it has been observed that most of the reported studies used public database (created by foreign universities/centers) or private database. Unfortunately, the availability of a national medical database in India is negligible. However, development of such medical database is possible. Such medical database can encourage new research activity and help a large research community. The proposed study focuses on developing an online public medical multimodal database platform. Here, the data acquisition software is build for collecting various information. © 2021 IEEE.

关键词： Database systems

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Cloud based analysis and classification of EEG signals to detect epileptic seizures 7

Cloud based analysis and classification of EEG signals to de...

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7th IEEE International Conference on Bio Signals, Images and Instrumentation, ICBSII 2021

作者： Rushambwa, Munyaradzi Charles Gezimati, Mavis Govindaraj, P. Palaniappan, Rajkumar Vijean, Vikneswaran Ghulam Nabi, Fizza Institute of Technology Electronic Engineering Harare Harare Zimbabwe Aj Institute of Engineering and Technology Information Science Department Manglore India Ama International University College of Engineering Department of Mechatronics Engineering Salmabad Bahrain University of Malaysia Perlis Mechatronic Engineering Perlis Malaysia University of the Punjab Institute of Quality and Technology Lahore Pakistan

ISBN: (纸本)9781665441261

Epileptic seizures are explained as the abnormal electrical activity occurring in the brain due to an internal or external triggering factors. EEG (Electroencephalograph) is used to record brain activity and can be used to detect the seizures before, during or after they occur. These signal characteristics, however differ from patient to patient due to the different emotional and physical wellbeing of the various individuals. In normal circumstances, anti-epileptic medication is used to treat patients but very few systems have been developed to manage and track the seizures. In most extreme and rare cases, some patients undergo invasive surgery to treat the seizures and this is common in seizures that are caused by tumors or physical brain damage. Non-invasive surface electrode EEG measurement gives an estimate of the seizure onset but more invasive intracranial electrocorticogram (ECoG) are required at times for precise localization of the epileptogenic zone. This project aims at designing and implementing a device that can be used to detect and monitor the attention and meditation values of a person in real time. The system measures the EEG waves of the brain, performs feature extraction, classification and sends the control command over wireless to a remote controller. The remote controller in turn issues commands with corresponding brain wave frequency and sends it to the cloud for remote analysis and classification. © 2021 IEEE.

关键词： Brain

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Design, Fabrication, and Characterisation of a Novel Piezoimpedal Tactile Sensor for use in Soft-Prosthetic Devices

Design, Fabrication, and Characterisation of a Novel Piezoim...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent mechatronics

作者： Thomas Searle Vitor Sencadas Gursel Alici Applied Mechatronics and Biomedical Engineering Research (AMBER) Group School of Mechanical Materials Mechatronic and Biomedical Engineering ARC Centre of Excellence for Electromaterials Science University of Wollongong New South Wales Australia Materials and Ceramic Engineering Department CICECO- Aveiro Institute of Materials University of Aveiro Aveiro Portugal

Enabling the robotic ability to sense tactile interactions is a complex and interdisciplinary challenge, as traditional pressure sensors made of hard and rigid materials struggle to replicate the soft and compliant interactions of mammalian somatosensory networks. This study investigates a novel matrixed contact sensor designed for use in soft robotics and biomedical prosthesis applications. The sensor is a coupled piezocapacitive-piezoresistive tactile sensor, optimized for scalability over various mechanical stimuli, including touch, pressure, bend, stretch, and proximity. By modifying the bulk geometry to include dielectric artifacts and integrating electroactive elastomeric composites, the soft and flexible sensor is fully mechanically compliant and conforms to skin behavior. The sensor has a maximum sensitivity of 0.028kPa -1 , a resolution of 1.3%, and a bandwidth of 29Hz. The study characterizes the sensor's performance and identifies its static and dynamic response to aid in developing complex, closed-loop tactile feedback control systems toward realizing the biomimetic implementation of synthetic skin in soft-prosthetic devices.

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