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检索条件"任意字段=25th International Conference on Methods and Models in Automation and Robotics"

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Influence of Mutual Inductance on High-Frequency Impedance Characteristics of Six-Phase PMSM under Inter-Turn Short-Circuit Fault

Influence of Mutual Inductance on High-Frequency Impedance C...

引用

international conference on Electrical Machines and Systems (ICEMS)

作者： Zihang Yuan Minghao Wang Jingang Bai Jiaxuan Huang Ping Zheng School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China

ISBN: (数字)9781665493024

ISBN: (纸本)9781665493031

To improve the ability to identify the inter-turn short-circuit (ITSC) fault, which is one of the most frequent fault types, of six-phase permanent-magnet synchronous machines (PMSMs), the high-frequency impedance of six-phase PMSM under ITSC fault is analyzed with consideration of the mutual inductance characteristics. the model of coupled magnetic circuit between the fault turns and other phases is established, interpreting the characteristic of mutual inductances with different fault turns locations. the high-frequency impedances of both the ITSC fault phase and healthy phases are analyzed, and the impedance decreases of healthy phase caused by mutual inductance are evaluated. Fault diagnosis indicator utilizing the high-frequency current response is designed and the indicator reliabilities of different voltage injection methods are compared.

关键词： Fault diagnosis Inductance Voltage Reliability engineering Mathematical models Circuit faults Impedance

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Design Method of Variable-Flux Machines for Improving Torque Density

Design Method of Variable-Flux Machines for Improving Torque...

引用

international conference on Electrical Machines and Systems (ICEMS)

作者： Faliang Liu Mingqiao Wang Yong Liu Zaiping Zheng Ping Zheng Jie Fu School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China Beijing Institute of Precision Mechatronics and Controls Beijing China

ISBN: (数字)9781665493024

ISBN: (纸本)9781665493031

In order to improving the torque density of the variable-flux machine, design methods for both series and parallel configurations are proposed based on the theoretical analysis. After the traditional rare-earth permanent-magnet (PM) synchronous machines (PMSM) is converted into the VFM, two typical configurations of the VFMs are given. To determine what kinds of low-coercive-force (LCF) magnets possessing torque improving capability, the simplified equivalent magnetic circuits for both configurations are established. the torque improving method for the series-configuration VFM is deduced based on the magnetic circuit. the output capability of series-configuration VFM with different LCF magnets are analyzed, which validate the accuracy of the deduced method. then, by assuming the magnetic reluctance of the teeth and yoke is much smaller than other reluctances, the contour maps of air-gap flux density for the parallel-configuration VFMs are investigated. Based on the proposed methods, the torque density of the VFMs with series-, parallel- and hybrid-configuration can be improved.

关键词： Magnetic flux Torque Design methodology Simulation Air gaps Mathematical models Synchronous machines

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A Kalman Filter-Based Submersible Position Prediction Model and a Multi-Target Dynamic Search and Rescue Scheme

A Kalman Filter-Based Submersible Position Prediction Model ...

引用

international conference on Control, automation, robotics and Vision (ICARCV)

作者： Yujie Tian Yuxi Luo Sitong Zhou Kun Zhang Yan Wang School of Astronautics Beihang University Beijing China School of Mechanical Electrical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Aiming at the deep-sea submarine search and rescue problem, this paper proposes a universally applicable submarine position prediction model and search model. the position prediction of the submersible is realized by Kalman filtering and dynamics modeling. Meanwhile, Monte Carlo method is used to construct the initialized population of the motion trajectory and optimize the search path step by step by iterative genetic algorithm. In this paper, the optimal search path is taken as the objective, the main ship SAR trajectory is simulated, and the probability of the diver is fitted as a function of time and cumulative search results. For the multiple submersible search and rescue problem, this paper proposes two possible search and rescue schemes and compares the search and rescue time. then we propose the optimal multi-objective dynamic search and rescue method. In addition, this paper adopts the G1-entropy weight-coefficient of variation combined assignment method to evaluate different search devices and creatively adopts the CRITIC method to secondary assign the weights obtained from different evaluation methods to select the optimal search device. Finally, sensitivity and robustness analysis are also carried out in this paper.

关键词： Analytical models Sensitivity Predictive models Search problems Robustness Trajectory Kalman filters Vehicle dynamics Underwater vehicles Genetic algorithms

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Trinary Relationship Interaction Detection

Trinary Relationship Interaction Detection

引用

IEEE international conference on Mechatronics, robotics and automation (ICMRA)

作者： Fangqun Gao YunTao Wu Yanduo Zhang Tao Lu Pan Tang Liwei Wang Jifeng Han Wanghui Wu Hubei Key Laboratory of Intelligent Robot School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei University of Arts and Science Xiangyang China State Key Laboratory of Power Grid Environmental Protection China Electric Power Research Institute Wuhan China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350352474

ISBN: (纸本)9798350352481

In various specialized operational scenarios, particularly those involving tool usage, the capacity to detect relationships between entities is crucial for understanding complex interactions. Traditional methods, which typically focus on unary or binary relationship detections, often fall short in capturing the subtleties present in such environments. this paper introduces the HTOI (Human Tool Object Interaction) model, a novel and pioneering approach to trinary relationship detection that addresses these limitations. the HTOI model has been designed to excel in complex interaction scenarios, including those characterized by the use of tools, as evidenced by its exceptional performance on our TData dataset. this dataset specifically highlights the nuanced actions of electric utility workers during tool-assisted operations, underscoring the model’s ability to detect intricate interactions with higher accuracy and reliability compared to existing HOI (Human Object Interaction) techniques. Our study aims to showcase the HTOI model’s significant advancement in the field of relationship detection, offering a valuable tool for analyzing and interpreting complex operational interactions involving tools.

关键词： Analytical models Mechatronics Accuracy Power industry Reliability robotics and automation

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Solving the Inverse Kinematics Problem Symbolically by Means of Knowledge-Based and Linear Algebra-Based methods

Solving the Inverse Kinematics Problem Symbolically by Means...

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12th IEEE international conference on Emerging Technologies and Factory automation (ETFA 2007), vol.3

作者： Michael Wenz Heinz Worn Institute for Process Control and Robotics Universität Karlsruhe Karlsruhe Germany

the construction of kinematics models by hand is often a tedious and error-prone process. this paper presents an overview of the Organic Robot Control project. One main goal of the project is to automate the computation of closed-formed solutions for both the forward and inverse kinematics of general industrial manipulators. For simple manipulator geometries, we use rule-based programming techniques to obtain a closed-form solution. For complicated geometries, we use elimination techniques based on the computation of Groebner basis. In so doing we convert a complicated coupled transcendental set of kinematics equations into a univariate polynomial. this polynomial can much easier be solved. the generated analytic models fulfill real time requirements and can be parallelized very well.

关键词： Kinematics Manipulators Computational geometry Polynomials Robot control Computer industry Construction industry Robot programming Closed-form solution Equations

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Analysis of Multi-Process Machining Errors of Frame Parts Based on State Space

Analysis of Multi-Process Machining Errors of Frame Parts Ba...

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Industrial automation, robotics and Control Engineering (IARCE), international conference on

作者： Haicheng Zhang Yali Ma Qi Zhang Zhi Wang School of Mechanical Engineering Dalian University of Technology State Key Laboratory of High-performance Precision Manufacturing Dalian China

ISBN: (数字)9798350380323

ISBN: (纸本)9798350380330

the critical processing characteristics of components are key in ensuring product accuracy and quality consistency. this paper focuses on the key machining characteristics of frame parts and develops a multi-process machining error prediction model based on the state space theory to anticipate machining errors. Firstly, the error sources such as reference error, fixture error, and machine tool geometric error during the multi-process processing of frame parts are described using the homogeneous coordinate transformation theory, multi-body system theory, and error transformation theory. Secondly, a multi-dimensional model is constructed using the above error sources to predict the machining error process. Lastly, the sensitivity analysis of the multi-process machining error prediction model is performed using partial derivatives to study the contribution of each error source to the multi-process machining error prediction model during the processing of frame parts. the model's effectiveness is verified by taking the machining process of the external surface key machining feature of frame parts as an example, and the contribution of each error source to the errors of the key machining feature of frame parts is further explained.

关键词： Analytical models Accuracy Fixtures Machining Predictive models Aerospace electronics Stability analysis Machine tools State-space methods Surface treatment

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Equipment Health Monitoring for Industrial Robotic Arms

Equipment Health Monitoring for Industrial Robotic Arms

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IEEE international conference on automation Science and Engineering (CASE)

作者： James Moore Daniela Sawyer Advanced Manufacturing Research Centre’s Integrated Manufacturing Group University of Sheffield Sheffield UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

the topic of equipment health monitoring (EHM) for robotics, including condition monitoring (CM), process monitoring (PM) and predictive maintenance (PdM) is of great interest within the literature, however, there is a significant lack of historical datasets for techniques to be tested upon. Commercial offerings in this area are often manufacturer specific, meaning that fleets that include robots from multiple suppliers cannot easily have performance/condition compared across the fleet. To address this, the work presented within this paper includes an accelerated wear test (AWT) conducted on an industrial robotic arm whilst being monitored using a suite of retrofitted sensors. the resulting data from the AWT is then analysed through a variety of techniques, including regression models, classification models, and a long short-term memory (LSTM) autoencoder, to demonstrate the potential for such methods to be utilised for robot ***, the associated dataset captured during the AWT is to be made openly available through the University of Sheffield’s online research data repository, ORDA, to allow further research to be conducted.

关键词： Adaptation models Accuracy Service robots Predictive models Robot sensing systems Manipulators Data models Maintenance Robots Long short term memory

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Data-Driven Energy Consumption Modeling and Simulation Method of Discrete Manufacturing Workshop Based on Simplified Power Curve

Data-Driven Energy Consumption Modeling and Simulation Metho...

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automation, Control and robotics Engineering (CACRE), international conference on

作者： Ming Yao Puikuan Chang Zhufeng Shao Qi Zhang Pengfei Niu State Key Laboratory of Tribology Tsinghua University Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control Tsinghua University Beijing China Zhili College Tsinghua University Beijing China Instrumentation Technology & Economy Institute Beijing China

ISBN: (数字)9798350350302

ISBN: (纸本)9798350350319

As a core part of industrial production, the management of energy consumption (EC) in discrete manufacturing workshops (DMWs) is critical to improving productivity, reducing costs, and minimizing environmental impact. this paper provides an in-depth study of EC in DMWs., which is categorized into two main groups: work EC and public EC. the work EC includes basic energy, manufacturing energy and transportation energy, and each EC is analyzed and modeled in detail. Different analysis methods are proposed for the two levels of concern, process level and technological level. Based on these analyses, a shop-floor level energy calculation method based on simplified power curves and a data-driven power modeling approach are proposed for constructing accurate shop-floor energy models. Taking typical manufacturing and transportation equipment such as NC machine tools and AGVs as examples, the various power characteristics in the work EC are analyzed and the corresponding models are established. the experimental results show that a better power modeling accuracy can be obtained by using the data-driven method.

关键词： Productivity Analytical models Energy consumption Accuracy conferences Transportation Manufacturing

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MLS: A Meta-Learning Based Stackelberg Model for Robot Trajectory Guidance

MLS: A Meta-Learning Based Stackelberg Model for Robot Traje...

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robotics, Control and automation (ICRCA), international conference on

作者： Jin Guo Zhiyong Jiang Yifan Liu Lili Gong Robotics Engineering Center The 21st Research Institute of China Electronics Technology Group Corporation Shanghai China

ISBN: (数字)9798350344721

ISBN: (纸本)9798350344738

the critical role of trajectory guidance in facilitating follower robots to reach target destinations under the supervision of a leader robot is well-established. However, the complexity of coordinating efficient collaboration increases when a leader must guide a diverse set of followers with unknown specific characteristics. To address this challenge, we propose a novel meta-learning-based Stackelberg approach. We model the guided trajectory planning problem as a dynamic Stackelberg game, capturing the intricate interaction dynamics between the leader and followers. Utilizing meta-learning techniques, the leader learns a meta-best-response model from a selected set of followers. When a follower initiates a guidance request, the leader swiftly adapts to the follower's unique characteristics using a few learning data. this follower-specific model is then used for effective trajectory guidance. Comprehensive simulations demonstrate the superior generalization and adaptability of our proposed method over alternative learning methods, and emphasize the practical value and effectiveness of the guidance mechanism. Our findings underscore the potential of our meta-learning-based Stackelberg approach in addressing collaborative trajectory planning challenges in heterogeneous multi-robot systems.

关键词： Metalearning Adaptation models Trajectory planning Robot kinematics Collaboration Games Trajectory

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LTM: A Fast and Error-sensitive Point Cloud Clustering Algorithm for LiDAR Panoptic Segmentation

LTM: A Fast and Error-sensitive Point Cloud Clustering Algor...

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international conference on robotics and automation Engineering (ICRAE)

作者： Peng Wu Zhengxi Hu Qianyi Zhang Jinzheng Guang Jingtai Liu Robotics and Automatic Information System Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics TBI Center Nankai University

ISBN: (数字)9798331518301

ISBN: (纸本)9798331518318

Point cloud clustering is a crucial approach to understand and analyze geometric information for both robotic systems and autonomous driving. To meet real-time requirements, several existing point cloud clustering algorithms are based on Connected Component Labeling. It means that classification decisions are made locally based on the geometric relationships among neighboring points. However, the existing neighborhood connection criterion lack robustness. this is because the difference in resolution between point clouds in the horizontal and vertical directions and various depth affect the distance between adjacent points, thereby affecting connectivity determination. In this paper, we propose a novel clustering algorithm LTM (includes Linearization, Trunk extraction and Merge). It processes the horizontal and vertical directions separately in two steps and innovatively utilizes three points to determine neighborhood connectivity. thus, it can reduce the impact of these constraints on the effectiveness. We cascade the proposed clustering algorithm with existing semantic segmentation models and perform a panoptic segmentation task on the SemanticKITTI. Experimental results demonstrate that LTM achieved the best results among all published methods of the same category. Furthermore, the single-frame processing time for clustering is within 10 milliseconds.

关键词： Point cloud compression Location awareness Laser radar Service robots Semantic segmentation Clustering algorithms Vectors Robustness Real-time systems Labeling

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