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Design and Analysis of Individually Demagnetized Power Converter for Switched Reluctance Motors

IEEE Transactions on Transportation Electrification 2025年第3期11卷 8439-8449页

作者： Liu, Hemiao Chen, Hao Wang, Xing Gorbounov, Yassen Wheeler, Patrick Anuchin, Alecksey Demidova, Galina Korovkin, Nikolay Liudmila, Sakhno Shenzhen Research Institute China University of Mining and Technology Shenzhen515100 China China University of Mining and Technology School of Electrical Engineering Xuzhou221116 China Xinjiang Institute of Engineering Ürümqi830000 China International Joint Research Center of Central and Eastern European Countries on New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China International Cooperation Joint Laboratory of New Energy Power Generation and Electric Vehicles of Jiangsu Province Colleges and Universities Xuzhou221008 China Xuzhou Key Laboratory of New Energy Electric Vehicle Technology and Equipment Xuzhou221008 China Mining Production University of Mining and Geology "St. Ivan Rilski " Department of Automation Sofia1700 Bulgaria The University of Nottingham Power Electronics Machines and Control Group NottinghamNG7 2RD United Kingdom Electric Drives Department Moscow111250 Russia Saint-Petersburg National Research University of Information Technologies Mechanics and Optics Faculty of Control Systems and Robotics Engineer Saint Petersburg197101 Russia Peter the Great St. Petersburg Polytechnic University Institute of Energy Saint Petersburg195251 Russia

Switched reluctance motors (SRMs) are capable of operating at high speeds and high loads. The large back EMF results in the excitation winding current being demagnetized more slowly, which, in turn, reduces the efficiency and output of the motor system. This study proposes a novel individually demagnetization power converter (IDPC) specifically designed for SRMs to effectively use the demagnetization energy through an independent demagnetization circuit. Compared with traditional converters, the IDPC can accept direct current (dc) and high-frequency ac inputs while achieving fast demagnetization and energy recovery. The topology and working principle of the IDPC are analyzed in detail in this article using a three-phase 12/8 SRM as the research object. In addition, the influence of the winding demagnetization voltage on the negative torque during the demagnetization phase was studied, as well as the functional implementation and logic control strategy of the IDPC. Simulation and experimental results confirm the validity of the proposed topology and high-frequency ac drive characteristics, as well as their advantages in terms of efficiency, output capacity, and dynamic performance. © 2015 IEEE.

关键词： Reluctance motors

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A Camera Calibration Method for Temperature Measurements of Incandescent Objects Based on Quantum Efficiency Estimation

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Sensors (Basel, Switzerland) 2025年第10期25卷 3094页

作者： Vittorio Sala Ambra Vandone Michele Banfi Federico Mazzucato Stefano Baraldo Anna Valente Automation Robotics and Machines Institute of Systems and Technology for Sustainable Production Department of Innovative Technologies University of Applied Science and Arts of Southern Switzerland via La Santa 1 6962 Lugano Switzerland.

High-temperature thermal images enable monitoring and controlling processes in metal, semiconductors, and ceramic manufacturing but also monitor activities of volcanoes or contrasting wildfires. Infrared thermal cameras require knowledge of the emissivity coefficient, while multispectral pyrometers provide fast and accurate temperature measurements with limited spatial resolution. Bayer-pattern cameras offer a compromise by capturing multiple spectral bands with high spatial resolution. However, temperature estimation from color remains challenging due to spectral overlaps among the color filters in the Bayer pattern, and a widely accepted calibration method is still missing. In this paper, the quantum efficiency of an imaging system including the camera sensor, lens, and filters is inferred from a sequence of images acquired by looking at a black body source between 700 °C and 1100 °C. The physical model of the camera, based on the Planck law and the optimized quantum efficiency, allows the calculation of the Planckian locus in the color space of the camera. A regression neural network, trained on a synthetic dataset representing the Planckian locus, predicts temperature pixel by pixel in the 700 °C to 3500 °C range from live images. Experiments done with a color camera, a multispectral camera, and a furnace for heat treatment of metals as ground truth show that our calibration procedure leads to temperature prediction with accuracy and precision of a few tens of Celsius degrees in the calibration temperature range. Tests on a temperature-calibrated halogen bulb prove good generalization capability to a wider temperature range while being robust to noise.

关键词： camera quantum efficiency multispectral camera thermal imaging

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DECOMPOSITION OF INDUSTRIAL systems FOR ENERGY EFFICIENCY OPTIMIZATION WITH OPTTOPO

arXiv

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arXiv 2022年

作者： Thiele, Gregor Johanni, Theresa Sommer, David Krüger, Jörg Department for Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology IPK Germany Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany Weierstrass Institute for Applied Analysis and Stochastics Berlin Germany Institute for Machine Tools and Factory Management Technical University of Berlin Berlin Germany

The operation of industrial facilities is a broad field for optimization. Industrial plants are often a) composed of several components, b) linked using network technology, c) physically interconnected and d) complex regarding the effect of set-points and operating points in every entity. This leads to the possibility of overall optimization but also to a high complexity of the emerging optimization problems. The decomposition of complex systems allows the modeling of individual models which can be structured according to the physical topology. A method for energy performance indicators (EnPI) helps to formulate an optimization problem. The optimization algorithm OptTopo achieves efficient set-points by traversing a graph representation of the overall system. © 2022, CC BY.

关键词： Optimization

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Implementing human-robot collaboration in highly dynamic environments: Assessment, planning and development

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AIP Conference Proceedings 2024年第1期2989卷

作者： A. Bastidas-Cruz T. Jaya G. Thiele J. Krüger Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstr. 8-9 10587 Berlin Germany Head of Industrial Automation Technology Department Institute of Machine Tools and Factory Management Technische Universität Berlin Pascalstr. 8-9 10587 Berlin Germany

Human-robot collaboration (HRC) applications have been slowly making their path in the industry. Although the required hardware and the methods for the planning and development of collaborative robotic applications are mostly already developed, some industrial branches still struggle to implement HRC. This is the case in motorcycle production, where, unlike car production, the assembly line has been optimized for manual *** on the use case described above, this paper identifies new requirements of HRC for automated screwing assembly operations in flexible production environments. In order to compensate deviations in the position of the tool relative to the workpiece, a screwing strategy based on force control is proposed. Parameter sensitivity is considered and supported experimentally with a screwing task performed by a cobot, where a method for contact detection between the nutrunner and the screw head is analyzed. This paper brings a guideline for experts from the manufacturing system engineering to implement HRC in highly dynamic assembly environments.

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Using anomaly detection and classification to support failure recovery of plants

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AIP Conference Proceedings 2024年第1期2989卷

作者： Niklas Grambow Lisa-Marie Fenner Oliver Heimann Jörg Krüger Department for Process Automation and Robotics Fraunhofer Institute for Production Systems and Design Technology Pascalstr. 8-9 10587 Berlin Germany Institute for Machine Tools and Factory Management Technische Universität Berlin Pascalstr. 8-9 10587 Berlin Germany

Failure recovery of machines is a great challenge for the plant operator. Usually, a stopped plant is quite costly and has to be put back into operation fast. In that case, experienced personnel are essential. Only their knowledge and broad understanding of the interaction of the various components allows a reliable identification of the underlying problem and enables a successful recovery. Digitization can help to address this problem. Knowledge can be stored and shared digitally across plants, locations and companies. In addition, an ever-increasing amount of machine and process data is digitally available which can further support the problem-solving process. We present a new approach to machine maintenance that relies on machine learning to help identify the underlying technical problem that led to the machines error. In contrast to predictive maintenance, our system is employed reactively and focusses on the identification and classification of singular failures rather than a predictive monitoring of the plants state. To support the operator in fault recovery, we use anomaly detection to identify the deviations in the data of the processes prior to the fault. This allows the system to generate hints as to where to look for the underlying cause of the error and helps the technician make an educated guess. Additionally, an error classification algorithm also allows troubleshooting information to be linked directly to the data. Thereby, when an error reoccurs, the knowledge gained in the first occurrence is immediately made available to the operator through information linked to the error *** this article, we present the concept behind our anomaly detection system and the required software architecture to combine the different data sources. Furthermore, we discuss the results from an experiment that simulates an optical part inspection using a camera based system, where we introduce different errors into the process and are able to demonstrate the capability

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automation of Life Data Analysis Processes

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IOP Conference Series: Materials Science and Engineering 2021年第1期1140卷

作者： Jonathan Krämer Gregor Thiele Theresa Johanni Jörg Krüger Department for Industrial automation at the Institute for Machine Tools and Factory Management Technical University of Berlin Department for Process automation and Robotics Fraunhofer Institute for Production Systems and Design Technology

Life data analysis is an effective statistical process to gain information on the reliability of technical facilities. The Weibull analysis is a widely-used method for modeling the probabilities of different functional failures. For its application in modern manufacturing and maintenance processes, an automation of this analysis is expedient. An exemplary process of data collection and fitting of a parametric model with continuous time scale is analyzed in this article. Its automation with different statistic software tools is described and comparatively evaluated. With the ambition of minimizing manual effort in the process, a highly automated solution was developed in this research. We describe this self-implemented solution in 'R' and justify that this procedure automatizes the process more than the examined commercial implementations. The here presented work proves to be a practical real-time assistance, right now applied in aircraft maintenance.

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On the Selection and Application of a Convenient Energy Management Software for Industrial Purposes

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IOP Conference Series: Materials Science and Engineering 2021年第1期1140卷

作者： Larissa Wurster Gregor Thiele Clemens Briese Jörg Krüger Plant Development Infrastructure / Assembly Trucks (TG/MAD) Daimler Truck AG Department for Process automation and Robotics Fraunhofer Institute for Production Systems and Design Technology Department for Machine Vision Fraunhofer Institute for Production Systems and Design Technology Department for Industrial automation at the Institute for Machine Tools and Factory Management Technical University of Berlin

The profitability of companies, especially in Germany, is affected by rising energy prices and increasingly stringent energy legislation. Certification according to ISO 50.001, an international standard for energy management systems, can help to meet legal requirements and increase energy efficiency. This article offers assistance in the form of a methodology that provides a structure for the selection process of an energy management system (EnMS). Considering properties of the individual company, it helps to identify an appropriate software solution. It is applied to a globally operating metalworking company in an example study. Furthermore, the measurement infrastructure in particular is a basic requirement that should not be overlooked in addition to the process of choosing an appropriate software solution. In this context, suitable metering points or criteria must be defined as well as sufficient attention paid to the anticipated costs for acquiring and integrating new measuring transducer and energy meters. The type and number of relevant measuring points must be considered in particular. Discussing these aspects, this article facilitates the process of planning and implementing an energy monitoring.

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Energy Efficiency Optimization using automationML modeling and an EnPI methodology

Energy Efficiency Optimization using AutomationML modeling a...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Gregor Thiele Niloufar Khorsandi Jörg Krüger Department for Process Automation and Robotics Institute for Production Systems and Design Technology Berlin Germany Department for Industrial Automation Technology Technical University of Berlin Berlin Germany

Industrial facilities are complex and heterogeneous systems in permanent technological change. The ambitions towards smart factories heighten the requirements for the flexible interconnection of various devices. These industrial entities are controlled, observed and optimized by many services. The tuning of process parameters of several linked components in order to boost the overall energy efficiency is one example of such services. automationML (AML) provides a hierarchical description language for industrial systems considering both structure and properties. An extension of the established standard allows for intuitive modeling of energy optimization problems. An approved energy performance indicator (EnPI) methodology was integrated in the libraries of AML in order to simplify and shorten the modeling procedure for the optimization task. The procedure is demonstrated using the example of an industrial cooling system.

关键词： Optimization Object oriented modeling Cooling Planning Energy consumption Biological system modeling Databases

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A new approach to modeling reinforcing textile structures for composite materials

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AIP Conference Proceedings 2022年第1期2430卷

作者： Andrei Biziuk Natalia Yasinskaya 1Vitebsk State Technological University Faculty of Information Technology and Robotics Department of Information Systems and Production Automation Moscow Av. 72 210038 Vitebsk Republic of Belarus 2Vitebsk State Technological University Faculty of Manufacturing Technology Department of Ecology and Chemical Technology Moscow Av. 72 210038 Vitebsk Republic of Belarus

The properties of composites largely depend on the properties of the reinforcing bases. When using woven textile materials as a reinforcing base for composites, it is necessary to pre-model the structure of this base. In this paper, the authors propose to use simulation modeling of textile materials to predict their properties. As a result, software for the simulation of textile materials has been developed, which can be used for industrial and scientific purposes. Three-dimensional models of textile materials can be used in modeling their impregnation with polymers.

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A fault diagnosis benchmark of technical systems with incomplete data — six solutions

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Control Engineering Practice 2025年 164卷

作者： Daniel Jung Erik Frisk Mattias Krysander Anna Sztyber-Betley Francesco Corrini Andrea Arici Nicolas Anselmi Mirko Mazzoleni Jiamin Xu Siwen Mo Zixuan Xu Chongpan Yang Zhile Du Hossein Safaeipour Mehdi Forouzanfar Vahid Mirahi Anna Pinnarelli Vicenç Puig Qiao Deng Yufei Liu Homayoun Najjaran Vehicular Systems Department of Electrical Engineering Linköping University Linköping SE-581 83 Sweden Faculty of Mechatronics Warsaw University of Technology Warsaw 02-525 Poland Department of Management Information and Production Engineering University of Bergamo Via G. Marconi 5 Dalmine (BG) 24044 Italy School of Automation Central South University Changsha 410083 China Department of Electrical Engineering Ahv.C. Islamic Azad University Ahvaz Iran Department of Mechanical Energy and Management Engineering (DIMEG) University of Calabria Rende Italy Institute of Robotics and Industrial Informatics (CSIC-UPC) University of Catalonia Barcelona Spain Department of Electrical and Computer Engineering University of Victoria Victoria V8W 2Y2 BC Canada

This paper presents a benchmark problem for fault diagnosis of an internal combustion engine that has been formulated and solved. The objective is to design a diagnosis system using and incomplete model information training data that only contains a limited set of fault realizations. Six different solutions to the benchmark, that were presented at the IFAC Safeprocess symposium 2024, are described and evaluated. The contribution of this paper is the benchmark and the presentation of six different solutions in one paper. The paper is intended to provide a starting point for engineers and researchers who work with fault diagnosis and monitoring of technical systems.

关键词： Fault detection and isolation Model-based diagnosis Data-driven fault diagnosis

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