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检索条件"任意字段=Conference on Data Analysis and Modeling for Process Control II"

共 4771 条记录，以下是261-270 订阅

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Robust Tracking control with L1 Adaptive Augmentation for a Long-Stroke Vertical Nanopositioning System: Part I

Robust Tracking Control with L1 Adaptive Augmentation for a ...

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IEEE conference on control Technology and Applications (CCTA)

作者： Huaman, Alex S. Reger, Johann IMMS Inst Mikroelekt & Mechatron Syst Gemeinnutzi D-98693 Ilmenau Germany Tech Univ Ilmenau Control Engn Grp POB 10-05-65 D-98684 Ilmenau Germany

ISBN: (纸本)9781665473385

In this paper and its companion paper [1], we address the problem of modeling and robust adaptive tracking control for an overactuated vertical nanopositioning system. We first introduce the operation principle of the lifting modules. In relation to the integrated actuators, their dynamics and important parameters are obtained from experimental and projected data. We further derive a physical model from the relevant components of the motion system. The model is validated with measured data in order to illustrate that it adequately reflects the real behavior. Emphasis is placed on the merits of control allocation (CA) to handle the overactuated nature of the overall motion system. The proposed CA concept proves to be effective for the ongoing application since it demands low computational costs and fulfills the heat emission constraint. We close this paper with the formulation and analysis of a suitable model for the derivation of advanced control strategies.

关键词： controllers

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modeling and simulation of extraction steam heating system in nuclear power plant

Modeling and simulation of extraction steam heating system i...

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2021 International conference on Computational modeling, Simulation, and data analysis, CMSDA 2021

作者： Song, Ze Liu, Xianling Shao, Jiaye Wang, Shanshan Yang, Jinfeng State Nuclear Electric Power Planning Design and Research Institute Co. Ltd. Beijing China Shandong Nuclear Power Co. Ltd. Shandong China

ISBN: (纸本)9781510651968

As a clean, safe and efficient energy, nuclear energy is one of the important solutions to realize clean energy heating in China. In this paper, the nuclear heating simulation model includes process system, control system, man-machine interface are established by using the modeling tool JADE. Through the simulation and analysis of steady-state and transient conditions, the rationality and correctness of the simulation model are verified. The model can be used for operating condition simulation, design optimization, and operator training, which can improve the digitalization level and enhance security and reliability of the nuclear heating units. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： control systems

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Computer System Breakdown Intelligent analysis Simulation Model Based on Deep Learning

Computer System Breakdown Intelligent Analysis Simulation Mo...

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2023 International conference on Mechatronics, IoT and Industrial Informatics, ICMiiI 2023

作者： Zhuo, Bihua Officers College of PAP Department of Information and Communication Sichuan Chengdu610213 China

ISBN: (纸本)9798350301397

Massive process measurement message brings great computational complexity and modeling complexity to the traditional breakdown diagnosis algorithm, and the traditional diagnosis algorithm has the disadvantage that it is difficult to make online estimation by using high-order quantities. Modern industrial systems have been developing towards largescale and complexity, which makes the breakdown diagnosis means for industrial systems encounter a series of technical questions. In view of the powerful data representation learning and analysis ability of deep learning technique, breakdown diagnosis based on deep learning has attracted wide attention from industrial and academic circles, and has made intelligent process control more automatic and resultful. The means adopted in this paper is deep learning, which is carried out alternately by convolution and sub-sampling. At last, the algorithm close to the output layer adopts the common multilayer neural network. As a breakthrough in the domain of latter-day artificial intelligence, deep learning can voluntarily learn valuable traits from the original trait set or even the original data. The research in this paper shows that the algorithm in this paper is resultful in breakdown prediction, and it is suitable to be widely applied in practical applications. © 2023 IEEE.

关键词： Multilayer neural networks

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Development of an OWL Ontology Based on the Function-Oriented System Architecture to Support data Synchronization Between SysML and Domain Models 15

Development of an OWL Ontology Based on the Function-Oriente...

引用

15th International conference on Knowledge Engineering and Ontology Development, KEOD 2023 as part of the 15th International Joint conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023

作者： Zhang, Yizhe Jacobs, Georg Zhao, Jia Berroth, Joerg Hoepfner, Gregor Institute for Machine Elements and Systems Engineering RWTH Aachen University Eilfschornsteinstr. 18 Aachen52062 Germany

ISBN: (纸本)9789897586712

A promising approach to systems engineering is called Model-Based Systems Engineering (MBSE), which is increasingly accepted to support the development process of complex systems. In MBSE,engineers use Systems modeling Language (SysML) for formalized modeling of function-oriented system architecture and solution architecture that enable the integration of various domain models to support a seamless system development process. Domain models simulate the physical behaviors of systems with design parameters so as to realize the quantitative analysis and verification of systems. These design parameters often exist in multiple heterogeneous data sources and often rely on manual importation into the SysML model. However, when systems become complex with a large data volume, manual data exchanges between multiple data sources and SysML models become time-consuming and error-prone. Therefore, this work proposes an ontology based on Web Ontology Language (OWL) for managing data in a standardized way and solving heterogeneous problems. Then, an automatic synchronization mechanism is established between the ontology and the SysML model for easy exchange of data. This work demonstrates and validates the proposed approach with a case study of a technical system (i.e., wind turbine system). The contribution of this work is the creation of a standardized OWL ontology that supports an automatic synchronization between the data from multiple domain models and the SysML models, thus reducing the manual effort of dealing with heterogeneous data sources and the risk of data inconsistency occurring in manual data transmission. Copyright © 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0).

关键词： Ontology

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analysis and modeling of Steel Industry Reheating Furnace Billets Temperature 23

Analysis and Modeling of Steel Industry Reheating Furnace Bi...

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23rd International Carpathian control conference (ICCC)

作者： Zanoli, Silvia Maria Pepe, Crescenzo Astolfi, Giacomo Moscoloni, Elena Univ Politecn Marche Dip Ingn Informaz DII Ancona AN Italy Alperia Bartucci Falconara Mma AN Italy

ISBN: (纸本)9781665466363

In the present work, topics related to the production processes of the steel industry are addressed;the analysis has been focused on the rolling mill process of semi-finished products of an Italian steel plant, which follows the reheating process of the billets, carried out inside a reheating furnace. For this purpose, an in-depth knowledge of the industrial process and a preventive data analysis work, capable of informing on the behavior of the process itself, have been conducted. Thanks to the obtained results, it will then be possible to create models and control systems capable of ensuring energy saving while guaranteeing high product quality and limiting pollution emissions. The first problem addressed in the present work deals with an in-depth analysis of the values recorded by the temperature sensors (thermal imaging camera and pyrometers) and the absorption values recorded in the rolling mills. The position of the thermal imaging camera, initially located at the furnace exit, was verified to be not optimal due to the presence of scale that altered the temperature measurements. The thermal imaging camera was subsequently repositioned downstream of the descaling device and a new analysis was carried out on the new data available. In the second part of the work a mathematical model of the temperature decay of the billets have been developed which models the billets' temperature behavior from the exit of the furnace through the descaling device and up to the last rolling mill stand. The initial analysis phase was functional in order to have at disposal a subset of data for the modelling validation. Satisfactory results were obtained in both the addressed problems.

关键词： data analysis temperature model billets reheating furnace steel industry energy efficiency process optimization

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Microbial Fermentation Optimal control Method Based on Improved Particle Swarm Optimization 2

Microbial Fermentation Optimal Control Method Based on Impro...

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2nd International conference on Computational modeling, Simulation and data analysis, CMSDA 2022

作者： Liang, Yilin Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9798350345759

Microbial fermentation is a typical microbial fermentation process. Microbial bacteria ingest the nutrients of raw materials in the fermentation tank. Under appropriate conditions, enzymes in the body catalyze complex biochemical reactions to produce microorganisms. In order to guarantee the quality of modeling data and meet the accuracy, integrity, and consistency of data quality requirements, it needs to preprocess the input and output data. In this paper, the parameter model is solved by the particle swarm algorithm. Updating the parameter value of the next moment in real time constitutes a feedback correction to the prediction model. Theil inequality approach is adopted to test the tracking performance of the above model's adaptive correction method. The Monte Carlo method is applied to generate multiple groups of different kinetic model values, which are substituted into the fermentation kinetic model as the real model parameter values. After the experimental analysis, the measured value of the model established by the method in this paper is closer to the predicted value, which has the effect of feedback correction and optimal control. The external conditions in the fermentation process are optimally controlled to achieve the effects of shortening the production period. It improves the yield of fermentation terminal target products and reduces the consumption of raw materials. © 2022 IEEE.

关键词： Fermentation

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5th International conference on Creativity in Intelligent Technologies and data Science, CIT&DS 2023

5th International Conference on Creativity in Intelligent Te...

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5th International conference on Creativity in Intelligent Technologies and data Science, CIT and DS 2023

ISBN: (纸本)9783031446146

The proceedings contain 40 papers. The special focus in this conference is on Creativity in Intelligent Technologies and data Science. The topics include: modeling the Movement of Vehicles with an Anti-lock Braking System on Various Types of Road Surface Using the Principles of PID control;business process Optimization of Technological Map in Farm Management System;problem of Building High-Quality Predictive Model of River Hydrology: The Combined Use of Hydrodynamic Simulations and Intelligent Computing;business Model Innovation: Considering Organization as a Form of Reflection of Society;methodological Bases for Decision Support in the Management of Services, Taking into Account the Personal Information of Customers;complex Dynamics modeling Algorithm Application in Comparative Study of Innovation processes;methods and Technologies for Improving the Efficiency of Multi-assortment Production Optimal Planning;intelligent Technologies for Designing Digital Information Models of Chemical and Technological Objects;Information Channel for Proactive control of Machining Conditions: A Cyber-Physical System on the Basis of a CNC Machine;explainable Machine Learning in Service Management of Transport Corporation;new Algorithm for Determining the Shape of Particles and the Size of Adulteration Areas in Meat for a Decision Support System;improving the Quality of Dental Services Based on Metal Additive Technologies: Unified Digital Workflow of Treatment;detecting Anomalies in Multidimensional Time Series Using Binary Classification;Neural Network-Based Optimization of Traffic Light Regulation of a Transport Hub with data Fetched During Simulation in SUMO Package;analysis of Numerical Simulation Results in a Symbolic Numerical System for Some Strain Energy Potentials;digital Integrated Monitoring Platform for Intelligent Social analysis.

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Spatial and Multivariate Statistics in Assessing Water Quality in the North Sea 24th

Spatial and Multivariate Statistics in Assessing Water Quali...

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24th International conference on Computational Science and Its Applications (ICCSA)

作者： Ody, Christopher Ramos, M. Rosario Carolino, E. Univ Aberta Lisbon Portugal Inst Politecn Lisboa H & TRC Hlth & Technol Res Ctr ESTeSL Escola Super Tecnol Saude Lisbon Portugal Univ Lisbon Fac Ciencias CEAUL Ctr Estat & Aplicacoes Lisbon Portugal

ISBN: (纸本)9783031652226;9783031652233

The Southern North Sea region plays a vital role for both the economy and society of the surrounding countries. Analyzing the quality of your water is a critical process that involves an assessment of physical, chemical, and biological parameters, essential to guarantee environmental sustainability and the health of local communities and marine ecosystems. Using Multivariate and Spatial Statistics methods, this study seeks to identify spatial patterns and autocorrelations to assess water quality in that region. The data set used was taken on a scientific cruise carried out in December 2020 aboard the RV Meteor vessel, led by a team of German researchers. The raw data went through pretreatment guided by the data Quality control protocol of SeadataNet, an international oceanography project aimed at making European maritime data available. Spike and gradient tests were performed, in addition to data standardization and imputation through inverse distance weighting interpolation. For a better understanding of the scientific area, the data were aggregated by zones for certain analyses, and were sometimes considered globally. An exploratory spatial data analysis (ESDA) was carried out in order to summarize its main characteristics. A reduction in the dimensionality of the original data was carried out through principal component analysis as an auxiliary tool for spatial analysis. The Spatial autocorrelation is analyzed by calculating global and local Moran's I Statistics. The outcomes indicate a significant spatial autocorrelation for all variables considered in the freshwater areas and a notable range flattening of the variables in the open sea areas, which possibly caused the lack of significant spatial autocorrelation in those areas.

关键词： Exploratory spatial data analysis North Sea Principal components Spatial correlation Water quality

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Investigating Statistical Correlation Between Multi-Modality In-Situ Monitoring data for Powder Bed Fusion Additive Manufacturing 18

Investigating Statistical Correlation Between Multi-Modality...

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IEEE 18th International conference on Automation Science and Engineering (IEEE CASE)

作者： Yang, Zhuo Adnan, M. Lu, Yan Cheng, Fan-Tien Yang, Haw-Ching Perisic, Milica Ndiaye, Yande NIST Syst Integrat Div Gaithersburg MD 20899 USA Natl Cheng Kung Univ Inst Mfg Informat & Syst Tainan Taiwan Natl Kaohsiung Univ Sci & Technol Dept Elect Engn Kaohsiung 82445 Taiwan

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

In-situ measurements provide vast information for additive manufacturing process understanding and real-time control. data from various monitoring techniques observe different characteristics of a build process. Fusing multi-modal in-situ monitoring data can significantly enhance process anomaly detection, part defect prediction, and build failure diagnosis, thus improving AM part quality control. This paper compares the powder bed fusion in-process observations from two types of AM in-situ monitoring, coaxial melt pool imaging, and layerwise imaging, and investigates the correlation between the two observations for a build of parts with multiple geometric features and scan patterns. All data were collected from an open architecture powder bed fusion AM testbed. data analysis shows that both datasets exhibit significant statistical changes when new features are introduced during the build. However, further machine learning-based modeling indicates that statistical features extracted from the two data sets do not correlate very well. Discussions are provided on how the statistical analysis of the observations from the two modality monitoring system can be utilized for data fusion strategy development, especially toward improving process anomaly detection.

关键词： Additive Manufacturing Laser Powder Bed Fusion Statistical analysis Machine Learning

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Evaluating Barriers to the Adoption of Blockchain for Enhancing Transparency in the Procurement process within Apparel Supply Chains 18

Evaluating Barriers to the Adoption of Blockchain for Enhanc...

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18th IFAC Symposium on Information control Problems in Manufacturing (INCOM)

作者： Madumali, Sawani Thibbotuwawa, Amila Saniuk, Sebastian Nielsen, Peter Univ Moratuwa Ctr Supply Chain Operat & Logist Optimizat Katubedda Sri Lanka Univ Zielona Gora Dept Engn Management & Logist Syst Podgorna 50 PL-65246 Zielona Gora Poland Aalborg Univ Dept Mat & Prod DK-9220 Aalborg Denmark

The textile and apparel industry is a rapidly growing global market, with the emergence of its complexity, volatility, and competitiveness. As a result, consumer demand for transparency in the supply chain has surged, leading to the recognition of blockchain as a pivotal tool for enhanced transparency. This study focuses on evaluating barriers to blockchain adoption in apparel supply chains, with a specific emphasis on sourcing and procurement. Collaborating with industry experts in Sri Lanka, the research aims to address critical gaps in information flow. The study employed a methodology consisting of two distinct steps, incorporating a background study and Interpretative Structural modeling (ISM). data analysis involves identifying barriers, developing ISM-based hierarchy models, and conducting MICMAC analysis. The study reveals key challenges, such as lack of expertise and underdeveloped technology to adopt blockchain emphasizing the need for strategic planning to address these obstacles and facilitate successful blockchain implementation. This research contributes to bridging gaps in blockchain adoption within the apparel supply chain, providing practical insights for industry stakeholders and decision-makers. Future research should validate identified barriers and develop strategies for effective blockchain implementation. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Transparency Traceability Apparel Supply Chain Blockchain Interpretative Structural modeling

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