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A Study on Improving the Performance of Dynamic Model Based Redundant Navigation System for Sensor Fault Scenarios

Journal of Institute of Control, Robotics and Systems 2025年第4期31卷 351-359页

作者： Ko, Bo Sung Choi, Hyeong Jun Jeon, Myung Jun Cho, Hyeon Jin Song, Jin Woo Department of Artificial Intelligence and Robotics and Convergence Engineering for Intelligent Drone AIRI Sejong University Korea Republic of Department of Intelligent Mechatronics Engineering and Convergence Engineering for Intelligent Drone AIRI Sejong University Korea Republic of Agency for Defense Development Maritime Technology Research Institute Korea Republic of

This study proposes a redundant navigation system for UUV (Unmanned Underwater Vehicle) utilizing a 6 DOF (Degree of Freedom) VDM (Vehicle Dynamic Model). The system is designed to enable safe UUV asset return when all navigation sensors become inoperable. Since it is impossible to perfectly determine VDM coefficients through water tank experiments, a method to improve VDM output accuracy in real time during UUV mission is necessary. Here in this study, we introduce real-time adaptive 6 DOF VDM output error compensation algorithm to enhance the performance of redundant navigation systems. This research aims to establish the foundation for backup navigation solutions in situations when critical UUV sensor failures occur. © ICROS 2025.

关键词： Water tanks

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Aero-Hydro-Elastic-Servo Modeling and Dynamic Response Analysis of A Monopile Offshore Wind Turbine Under Different Operating Scenarios

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China Ocean engineering 2024年第3期38卷 379-393页

作者： XIE Shuang-yi GAO Jian LI Yong-ran JIANG Shu-xin ZHANG Cheng-lin HE Jiao College of Mechanical Engineering Chongqing University of TechnologyChongqing 400044China Beijing Institute of Precision Mechatronics and Controls Beijing 100076China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400044China Fishery Machinery and Instrument Research Institute Chinese Academy of Fishery SciencesShanghai 200092China School of Mechanical and Power Engineering Chongqing University of Science&TechnologyChongqing 401331China

This paper constructs a coupled aero-hydro-elastic-servo simulation framework for a monopile offshore wind turbine(OWT).In this framework,a detailed multi-body dynamics model of the monopile OWT including the gearbox,blades,tower and other components(nacelle,hub,bedplate,etc.)has been explicitly *** effects of pile−soil interaction,controller and operational conditions on the turbine dynamic responses are studied systematically in time domain and frequency *** results show that(1)a comprehensive drivetrain model has the capability to provide a more precise representation of the complex dynamic characteristics exhibited by drivetrain components,which can be used as the basis for further study on the dynamic characteristics of the drivetrain.(2)The pile−soil interaction can influence the wind turbine dynamic responses,particularly under the parked condition.(3)The effect of the pile−soil interaction on tower responses is more significant than that on blade responses.(4)The use of the controller can substantially affect the rotor characteristics,which in turn influences the turbine dynamic responses.(5)The tower and blade displacements under the operational condition are much larger than those under the parked *** model and methodology presented in this study demonstrate potential for examining complex dynamic behaviors of the monopile *** ensure accuracy and precision,it is imperative to construct a detailed model of the wind turbine system,while also taking into account simulation efficiency.

关键词： offshore wind turbine(OWT) pile−soil interaction dynamic response parked condition operating condition

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A Review on Smartphone Charger: Technologies and Challenges 5

A Review on Smartphone Charger: Technologies and Challenges

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Manoharan, S. Mahalakshmi, B. Ananthi, K. Elakya, A. Jct College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India Hindusthan College of Engineering and Technology Department of Physics Coimbatore India Sri Krishna College of Engineering and Technology Department of Mechatronics Engineering Coimbatore India Sri Krishna College of Technology Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350385649

Over 600 million people in India use smartphones at the moment as more people switch from feature phones to smartphones. In 2023, over a billion people in India are expected to use smartphones. It is predicted that 1.55 billion Indians will own smartphones by 2040. As more people acquire mobile phones and use them for longer periods of time, charging the smartphone become a prominent factor. The proportion of energy used to charge a cell phone is determined by several variables, including the phone's battery capacity, the charging technique, and the efficiency of the charging process. The method utilized for charging a phone also affects how much energy is used. Several kinds of mobile phone chargers that are available, energy-efficient charging methods, and energy costs related to smartphone usage are covered in this study. © 2024 IEEE.

关键词： Environmental impact

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MWFA Model Based Synthetic Data Creation and Utilization for the Training of XGBoost Based Fault Diagnostic Algorithm of a Squirrel Cage Induction Motor

MWFA Model Based Synthetic Data Creation and Utilization for...

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2024 International Conference on Electrical Machines, ICEM 2024

作者： Asad, Bilal Khan, Muhammad Amir Raja, Hadi Ashraf Vaimann, Toomas Kallaste, Ants Naseer, Muhammad Usman Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia The Islamia University Department of Electrical Power Engineering Bahawalpur Pakistan

ISBN: (纸本)9798350370607

The use of AI trained algorithms can be considered as a paradigm shift in the field of predictive maintenance of electrical machines. However, the accuracy of the trained algorithms depends on the accuracy, versatility, and the amount of training data set which should provide all possible faulty scenarios under different operating conditions. The collection of this huge data set is almost impossible from industry and for the laboratory test rigs. This is due to the availability of a fewer number of motors with known faults working in industry and economic restrictions on the destructive tests in the lab. This fact has increased the importance of mathematical models which can be used for the training of AI algorithms under different conditions. This paper proposes the utilization of modified winding function analysis (MWF A) model of three phase induction motor for the creation of training data set. For the simulation time, complexity, and accuracy comparison the same data set is prepared using finite element method (FEM) as well. Both trained models are blindly tested on the data set taken from the laboratory test setup and the comparative analysis is performed for accuracy, time, and complexity. © 2024 IEEE.

关键词： Predictive maintenance

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MASA: Multi Agent Situational Awareness for Visually Impaired 21

MASA: Multi Agent Situational Awareness for Visually Impaire...

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21st International Bhurban Conference on Applied Sciences and technology, IBCAST 2024

作者： Mahboob, Zaid Sadiq, Salman Khan, Umar Shahbaz Zeb, Ayesha Tiwana, Mohsin Islam College of E&ME National University of Sciences and Technology Department of Mechatronics Engineering IslamabadH-12 Pakistan

ISBN: (纸本)9798331516680

Visually impaired people (VIP) face difficulties in perceiving and comprehending their surroundings and, there-fore, feel disconnected from the environment. Due to visionary challenges, VIPs face challenges in carrying out routine activities but are also prone to possible risks and hazards in dynamic environments. A number of recent studies have proposed solutions for VIP based on different types of sensors and machine learning algorithms. But previously proposed systems lack an all-in-one wearable solution for visually impaired people due to rigorous training requirements for each scenario, and no conditional outputs based on user queries. In this research, we propose a novel solution named MASA for VIPs. MASA is a wearable solution for situational awareness and dynamic decision-making based on visual sensor and user queries. The proposed framework leverages vision language models (VLMs) and employs an agentic workflow for VLMs to reduce user cognitive overloading by removing all redundant information from the final output. The solution is deployed on a customized VR headset, which has Raspberry Pi, batteries, camera fitted into it. For evaluation purposes, 20 healthy subjects with good vision used MASA in 10 different scenarios. Qualitative feedback from the 20 subjects yielded encouraging results. Quantitative analysis was conducted using human-defined baselines. © 2024 IEEE.

关键词： Visual languages

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Strengthening Active Learning with a Reinforcement Approach in engineering Education 65

Strengthening Active Learning with a Reinforcement Approach ...

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65th IEEE Annual International Scientific Conference on Power and Electrical engineering of Riga Technical University, RTUCON 2024

作者： Vodovozov, Valery Raud, Zoja Petlenkov, Eduard Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Tallinn University of Technology Department of Computer Systems Tallinn Estonia

ISBN: (纸本)9798350365771

Nowadays, the best methods of training specialists who are able to identify new challenges, make original decisions, and explore complex issues are associated with active learning. However, it is appears that the development of new values, proclaimed as the purpose of engineering education, is not so much the goal of the learners themselves as of the educators responsible for developing curricula and the academic environment. As for students, they perceive active learning as a variety of ways to achieve their own, narrower and more specific goals, namely the successful completion of the studied disciplines. In this context, the target of the current research is to propose and substantiate a reinforcement system aimed at attracting and supporting the interest of university students in active learning based on a set of updated methodological tools. The paper demonstrates how active learning is being transformed into reinforcement learning, and supports such an observation with examples from various educational activities, including lectures, quizzes, exercises, presentations, and laboratory works. It is expected that the proposed reinforcement approach will be in need of learners, faculty and industry in the near future ahead of the big challenges facing the global educational system. © 2024 IEEE.

关键词： Federated learning

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Prediction of directivity characteristics of piezoelectric macro-fiber composite interdigital transducers: a semi-analytical approach 11

Prediction of directivity characteristics of piezoelectric m...

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11th European Workshop on Structural Health Monitoring, EWSHM 2024

作者： Raorane, Siddhesh Ambrozinski, Lukasz Stepinski, Tadeusz Packo, Pawel Department of Robotics and Mechatronics Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Krakow30-059 Poland

The employment of guided waves for structural health monitoring applications has attracted substantial attention in recent years. Piezoelectric transducers are frequently employed in these systems for elastic wave generation and acquisition. Their dynamic properties, i.e., direction-dependent frequency characteristics such as directivity patterns, are an important feature for designing a reliable monitoring strategy. Although analysis of the transducer directivity pattern can be performed using finite element models, these usually tend to be computationally very expensive, especially for parametric and optimization studies. In this paper, a semi-analytical framework is proposed that can predict the far-field directivity patterns of complex transducers of arbitrary shape and structure mounted on a substrate. The framework described in this paper integrates analytical far-field predictions with a local finite element model evaluating the traction field produced by the transducer. Consequently, the FE model accurately captures near-field responses, whereas the analytical component predicts the far-field responses. The implementation of this semi-analytical framework requires the development of analytical and numerical approaches. The former includes computation of dispersion curves of the inspected plate, the stress and displacement profiles of wave modes, and ultimately, the excitability relations, while the latter includes estimation of the traction field between the transducer and the plate using the FE model. Owing to the popularity of piezoelectric macro-fiber composite (MFC) transducers, in this paper, we apply the proposed method to predict the directivity patterns of MFC M2807-P2 transducer. To validate the reliability of the proposed method, the predicted patterns are compared with experimental results obtained using Laser Doppler Vibrometer. © 2024 11th European Workshop on Structural Health Monitoring, EWSHM 2024. All rights reserved.

关键词： Piezoelectric transducers

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Big data meets big wind:A scientometric review of machine learning approaches in offshore wind energy

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Energy and AI 2024年第4期18卷 1-12页

作者： Prangon Das Maisha Mashiata Gregorio Iglesias Department of Mechatronics Engineering Rajshahi University of Engineering&TechnologyRajshahi 6204Bangladesh School of Engineering&MaREI Environmental Research InstituteUniversity College CorkCollege Rd.CorkIreland School of Engineering Computing and MathematicsPlymouth UniversityDrake CircusPlymouthUK

Offshore wind energy offers several advantages relative to its onshore counterpart-not least stronger and steadier winds,the possibility of larger turbines,and no land *** operational complexities,environmental challenges,and higher maintenance costs of offshore wind turbines necessitate innovative *** approaches are insufficient,and new“big data”techniques,notably machine learning and deep learning,are poised to play a significant role in the design and optimisation of offshore wind turbines and *** objective of this paper is to conduct a scientometric analysis of machine learning and deep learning techniques applied to offshore wind *** research methodology employs a circular framework,integrating data acquisition and statistical analysis to provide a comprehensive scientometric insight into the state of the *** regards the country of origin,most of the publications stem from just five countries,which signals a need of greater geographical diversity in this field of *** importantly,the rapid,steady increase in the annual number of publications since 2017 reveals the interest of the research community in this novel topic.

关键词： Offshore wind Wind energy Machine learning Deep learning Neural network Artificial intelligence

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A novel adaptive harmonic balance method with an asymptotic harmonic selection

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Applied Mathematics and Mechanics(English Edition) 2023年第11期44卷 1887-1910页

作者： Rongzhou LIN Lei HOU Yi CHEN Yuhong JIN N.A.SAEED Yushu CHEN School of Astronautics Harbin Institute of TechnologyHarbin 150001China Department of Physics and Engineering Mathematics Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Automation Biomechanicsand MechatronicsFaculty of Mechanical EngineeringLodz University of TechnologyLodz 90924Poland Mathematics Department Faculty of ScienceGalala UniversityGalala 43511Egypt

The harmonic balance method(HBM)is one of the most widely used methods in solving nonlinear vibration problems,and its accuracy and computational efficiency largely depend on the number of the harmonics *** adaptive harmonic balance(AHB)method is an improved HBM *** paper presents a modified AHB method with the asymptotic harmonic selection(AHS)*** new harmonic selection procedure selects harmonics from the frequency spectra of nonlinear terms instead of estimating the contribution of each harmonic to the whole nonlinear response,by which the additional calculation is avoided.A modified continuation method is proposed to deal with the variable size of nonlinear algebraic equations at different values of path parameters,and then all solution branches of the amplitude-frequency response are *** experiments are carried out to verify the performance of the AHB-AHS *** typical nonlinear dynamic equations with different types of nonlinearities and excitations are chosen as the illustrative *** with the classical HBM and Runge-Kutta methods,the proposed AHB-AHS method is of higher accuracy and better *** AHB-AHS method proposed in this paper has the potential to investigate the nonlinear vibrations of complex high-dimensional nonlinear systems.

关键词： harmonic balance method(HBM) adaptive harmonic balance(AHB)method harmonic selection nonlinear vibration multi-frequency excitation

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Research on carbon emission calculation of sand casting for individual castings and case study

Carbon Neutral Systems

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Carbon Neutral Systems 2025年第1期1卷 1-16页

作者： Zhao, Xiuxu Cai, Wei Zhuang, Aojie School of Mechatronics Engineering Wuhan University of Technology Wuhan China

Sand casting is one of the cornerstones of modern industrial production, which has an important impact on resource consumption and environmental impact. In order to realize the decarbonization of sand casting, it is necessary to conduct an effective quantitative analysis of the impact of the casting production process on the environment. This study focuses on the quantitative calculation and optimization of carbon emissions in the sand mold casting process of a single casting. Based on existing research on carbon emission evaluation in the casting process, the carbon emission characteristics of energy, materials, and exhaust gases in each production stage of the casting process are analyzed. Combined with actual production process parameters, a carbon emission evaluation model for the casting process is established, which can quantitatively calculate and analyze the carbon emissions in the production process of a single ***, the effectiveness of the method was verified through production examples. The results of this study can provide an effective analytical method for achieving low-carbonization in the casting process from a microscopic perspective, which will provide accurate data support for further reducing carbon emissions.

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