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检索条件"任意字段=Conference on Process Control and Diagnostics"

共 1528 条记录，以下是1-10 订阅

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The diagnostics Methods of Software and Hardware for Data Exchange in APCS of NPP 17

The Diagnostics Methods of Software and Hardware for Data Ex...

引用

17th International conference on Management of Large-Scale System Development, MLSD 2024

作者： Byvaykov, M.E. V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9798350375718

The diagnostics of exchange of data between the elements of the top and base level systems of the Automated process control system (APCS) of a Nuclear power plant (NPP) is considering. The methods and the algorithms of diagnostics of the software and the hardware of the APCS of the NPP of the exchange of data are proposing. © 2024 IEEE.

关键词： Automated process control system (APCS) diagnostics of software and hardware exchange of data Nuclear power plant (NPP) subsystems of top and base levels of APCS of NPP

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Identification and Characterization of Modulation Scheme in an EV-PMSM control Strategy for Digital Twin Modeling 16

Identification and Characterization of Modulation Scheme in ...

引用

16th International conference on diagnostics in Electrical Engineering (Diagnostika)

作者： Ibrahim, Mahmoud Rassolkin, Anton Vaimann, Toomas Kallaste, Ants Tallinn Univ Technol Dept Elect Power Engn & Mechatron Tallinn Estonia

ISBN: (纸本)9798350361506;9798350361490

Digital twins (DT), virtual replicas of physical systems, play a pivotal role in design, monitoring, and optimization across various industries. However, the accuracy of DT relies heavily on the precision of their underlying virtual models, presenting a challenge when physical system parameters are not fully known. This research addresses this challenge by proposing a comprehensive approach to identify and characterize the modulation scheme employed in the control strategy of an Electric Vehicle Permanent Magnet Synchronous Motor (EV-PMSM). The proposed algorithm utilizes actual stator voltage and current signals obtained from the EV motor drive test bench. The identification process involves three sequential steps: switching frequency calculation, spectrum analysis, and harmonic analysis. The results of this analysis strongly indicate the utilization of Space Vector Modulation (SVM) in the control strategy. Finally, the voltage vector distribution (VVD) was calculated to serve as a cornerstone for the precise modeling of the modulator.

关键词： PMSM vector control modulation modeling digital twin

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AI driven process Diagnostic & control: Device Manufacturing 8

AI driven Process Diagnostic & Control: Device Manufacturing

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8th Electron Devices Technology & Manufacturing conference (EDTM)

作者： Park, Jaeyong Samsung Hwasung South Korea

ISBN: (纸本)9798350383089;9798350371529

This paper explores the integration of Artificial Intelligence (AI) in process control and diagnostics in semiconductor manufacturing. It highlights current trends, including machine learning (ML) for data alignment and predictive maintenance, and anticipates future advancements in data sharing and standardization. This overview showcases AI's transformative impact on equipment optimization and industry collaboration, underlining its role in shaping efficient, proactive manufacturing processes.

关键词： AI ML Generative AI Manufacturing

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Transforming Infrastructure Management in a Networked World: OMA Strategies Empowering SHM diagnostics 10th

Transforming Infrastructure Management in a Networked World:...

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10th International Operational Modal Analysis conference (IOMAC)

作者： Longo, Monica Daro, Paola Centrone, Pietro Antonio Ferrara, Salvatore Chiariotti, Paolo Cigada, Alfredo Mancini, Giuseppe Sacertis Ingn SRL CSo M DAzeglio 118 I-10126 Turin Italy Politecn Milan Dept Mech Engn Via Privata Giuseppe La Masa 1 I-20156 Milan Italy

ISBN: (纸本)9783031614279;9783031614255;9783031614248

Operational Modal Analysis (OMA) techniques are nowadays well established methods to support the Structural Health Monitoring field in Civil Engineering. However, what would be the best procedure to optimize the analysis process on a network of hundreds of infrastructures undergoing continuous monitoring and diagnostics control? Innovative data-processing approaches encompass the definition of strategies of cross-controls and combinations of algorithms that allow to respond to the need for both a prompt anomaly or damage identification and a more refined analysis. In this paper attention is focused to a network of more than 150 monitored infrastructures, detailing how the diagnostics process combines the fusion of simple vibrational control algorithms and frequency peak-picking routines for semi-real time alerting with more complex OMA techniques for the initial system identification during the finite element (FE) model updating and for periodic controls of modal shape variations over time. A representative case study of a selected bridge under continuous monitoring will be presented, showing how the OMA techniques are playing a key role in detecting structural behavior variations up to the identification of damage progression to foster proactive maintenance interventions.

关键词： Modal based SHM infrastructures monitoring diagnostics data-processing optimization bridge case studies

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Fault detection and diagnostics of complex dynamic systems using Gaussian process Models - nuclear power plant case study 27

Fault detection and diagnostics of complex dynamic systems u...

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27th International conference on Methods and Models in Automation and Robotics (MMAR)

作者： Puchalski, Bartosz Gdansk Univ Technol Fac Elect & Control Engn Dept Intelligent Control & Decis Support Syst 11-12 Gabriela Narutowicza St PL-80233 Gdansk Poland

ISBN: (纸本)9798350311075

The article examines the use of Gaussian process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working point or faulty power measurements. The article discusses the characteristics and benefits of Gaussian process Models and how they can be utilized to improve: the reliability and accuracy of nuclear power plant anomaly detection, fault diagnosis and decision making process in states of emergency. Overall, this paper highlights the capabilities of Gaussian process Models to enhance the safety, reliability and efficiency of nuclear power plants. The results of this study are expected to provide valuable insights for engineers and researchers in the fields of control engineering and nuclear power.

关键词： fault diagnosis maintenance gaussian processes process modeling

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Improving the winding angle measurement for an effective process control

Improving the winding angle measurement for an effective pro...

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IEEE International Instrumentation and Measurement Technology conference (I2MTC)

作者： D'Emilia, Giulio Chiominto, Luciano Natale, Emanuela Stamopoulos, Antonio Univ Aquila Dept Ind & Informat Engn & Econ Laquila Italy

ISBN: (纸本)9798350380903;9798350380910

Two vision systems are developed to inspect the winding angle of a filament wound carbon fiber and epoxy resin composite cylinder. The first used system relay on a high-resolution color camera. The second vision system is based on a commercial polarization and exploits the polarization information to process the image. A component inspection strategy is proposed, and the metrological performances are experimentally and carefully evaluated. Using the polarization camera variability of data concerning the winding angle is reduced to the order of 0.5 degrees, promising for a better process control and diagnostics and reducing the probability of voids and defects, which are related to the correspondence of the winding angle to the nominal one. This way the reliability of the pieces realized with composite material, which is a mandatory requirement for this kind of component, could be improved. It also results that the additional computational load is negligible making the polarization camera inspection suitable for an online use.

关键词： composite materials filament winding angle process control vision system polarization uncertainty of measurement

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DRI Advanced process control With Predictive Method and Virtual Assessment for Increased Plant Yield With Reduced OpEx and Emissions

DRI Advanced Process Control With Predictive Method and Virt...

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AISTech 2024 Iron and Steel Technology conference

作者： Pauluzzi, Dario Zugliano, Alberto Andrea, Drius Giraldo, Ashton Hertrich Mahmoud, Mohab Sales Senior Manager Danieli and C. Officine Meccaniche S.p.A. Via Nazionale 41 Buttrio33042 Italy Process Senior Engineer Danieli and C. Officine Meccaniche S.p.A. Via Nazionale 41 Buttrio33042 Italy Automation Engineer Danieli and C. Officine Meccaniche S.p.A. Via Nazionale 41 Buttrio33042 Italy Sales Engineer Danieli and C. Officine Meccaniche S.p.A. Via Nazionale 41 Buttrio33042 Italy

ISBN: (纸本)9780930767259

Q-RED is the advanced DRI process control system from Danieli for increased plant yield and reduced OpEx. The Suite comprises 4 modules: the process reconstruction model, the process gas heater diagnostics tool, the reactor tracker, and the set point optimizer. the PRM is the main core;it collects the measured variables and reconstructs the non-measured ones, offering good insight of the plant. PGH diagnostics Tool, starting from the gas entering the PGH and its working points estimates the coking tendency, rate, and the fouling status of heater’s tubes. Reactor tracker and LESTO modules help conducting the plant, optimizing quality and energy consumption. © 2024 by the Association for Iron & Steel Technology.

关键词： Energy utilization

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Development of a Machine Learning Model for Production Facility Predictive diagnostics

Development of a Machine Learning Model for Production Facil...

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2024 International conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Vorsin, Daniil Toichkin, Nikolay Murmansk Arctic University Department Of Informatics And Computer Engineering Apatity Russia

ISBN: (纸本)9798350395013

The usage of artificial intelligence in problems related to industry makes it possible to develop optimization, predictive digital models for their operation in real time. The developed model can conduct predictive diagnostics of equipment's, or can be employed as a system that offers recommendations to the user for subsequent optimization of the technological process Considering the growing complexity of technical equipment and their control systems, it becomes highly imperative to develop an intelligent diagnostic structure for safety management in multi-level industrial systems. The article's relevance stems from the implementation of machine learning algorithms in the industry, enabling the analysis of a considerable amount of sensor-derived data. As a result, this facilitates predictive equipment diagnostics, anomaly prediction, intelligent safety management, uninterrupted operations, and reduced maintenance downtime. © 2024 IEEE.

关键词： Recurrent neural networks

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Improved System of Remote Monitoring, control and Diagnosis of the State of Oil Raw Materials in the process of Its Storage 12th

Improved System of Remote Monitoring, Control and Diagnosis ...

引用

12th World conference on Intelligent Systems for Industrial Automation, WCIS 2022

作者： Gulamov, Sh. M. Kabulov, N.A. Tashkent State Technical University Tashkent Uzbekistan

ISBN: (纸本)9783031515200

The article discusses the necessity to employ the production of oil and fat for process control automation as well as an enhanced system for remote monitoring, control, and diagnostics of the condition of oilseeds during storage. Linguistic variables and their terms are defined, and relationships between the intervals of change in the physical quantities of technological parameters and the terms of linguistic variables are established. Additionally, a fuzzy control system that corresponds to the study’s subject is suggested, along with a solution to the issue of fuzzification of information. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuzzy control

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BPMN4CARS: A Car-Tailored Workflow Engine 21

BPMN4CARS: A Car-Tailored Workflow Engine

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IEEE 21st International conference on Industrial Informatics (INDIN)

作者： Koenig, Simone Vogel-Heuser, Birgit Wilch, Jan Unger, Tobias Hahn, Michael Soldo, Stjepan Kopp, Oliver Tech Univ Munich Inst Automat & Informat Syst Garching Germany Opitz Consulting GmbH Bad Homburg Germany Mercedes Benz AG Sindelfingen Germany

ISBN: (纸本)9781665493130

The importance of high-performance computers in car networks increases to realize software assistance functions. These computers offer new opportunities for use cases in car testing and diagnostics towards vehicle software and services. Therefore, car testing and diagnostics are no longer limited to the testing and functional checking of electric and electronic components. Proven concepts from computer science, such as business process management, can be integrated into the car network to provide a uniform basis for automotive use cases. In this paper, (i) the Business process Model and Notation (BPMN) standard is used to model diagnostic processes in future car production lines and (ii) a car-tailored BPMN workflow engine is introduced to execute the processes in a high-performance vehicular computer. The research on executable BPMN models in car networks bridges the gap between interdisciplinary business processes and execution in automotive IT systems.

关键词： Software-defined car Service-oriented vehicle diagnostics control and testing Car-tailored workflow engine Executing BPMN

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