检索结果-内蒙古大学图书馆

Circuits, systems, Communications and Computers (CSCC), International Conference on

作者： Izaskun Garrido Jon Lecube Fares Mzoughi Pavam Aboutalebi Irfan Ahmad Salvador Cayuela Ailtor Garrido Department of Automatic Control and Systems Engineering Automatic Control Group ACG University of the Basque Country-UPV/EHU Bilbao Spain

Wave excitations cause structural vibrations on the Oscillating Water Columns (OWC) lowering the generated power and reducing the life expectancy. The problem of generator deterioration has been considered for the Mutriku MOWC plant and a machine learning-based approach for prognosis and fault characterization has been proposed. In particular, the use of k-Nearest Neighbors (kNN) models for predicting the time to failure of OWC generators has been proposed. The analysis is based on data collected from sensors that measure various operational parameters of the turbines. The results demonstrate that the proposed kNN model is an excellent choice for reducing maintenance costs by enabling scheduling months in advance. The model's high accuracy in predicting generator failures allows for timely and cost-effective maintenance, preventing costly breakdowns and improving turbine efficiency. These results highlight the potential of machine learning-based approaches for addressing maintenance challenges in the energy sector and underscore the importance of proactive strategies in reducing operational costs and maximizing energy production.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Partially Double-Pass Structure in Serial Hybrid Fiber Amplifier

Partially Double-Pass Structure in Serial Hybrid Fiber Ampli...

引用

2023 International Conference on engineering, Science and Advanced Technology, ICESAT 2023

作者： Ali, Ali Yaseen Salh Al-Mashhadani, Mohammed Kamil Al-Mashhadani, Thamer Fahad Hammudi, Rabi Noori Bouteraa, Yassine Hammudi, Rabi Noori Tunisia Tikrit University Department of Petroleum Systems Control Engineering Saladdin Iraq Tikrit University Department of Electrical Engineering Saladdin Iraq Kut Univeristy College Department of Laser Engineering and Optoelectronics Alkut Wasit52001 Iraq Prince Sattam Bin Abdulaziz University Department of Computer Engineering Al-Kharj11942 Saudi Arabia

ISBN: (纸本)9798350344400

In this paper, a partially double pass configuration in serial hybrid fiber amplifier is experimentally demonstrated. In the proposed design, a double pass erbium gain and single pass Raman gain are achieved serially. A total pump power of 450 mW (400 mW for 1495 nm Raman amplifier and 50 mW for1480 nm in erbium amplifier) were used. At -30 dBm input signal power and optimum pumps conditions, the achieved flatness bandwidth is 80 nm (1530-1610 nm) in the conventional and long bands (C+L) bands. In addition, the obtained average gain level is 33 dB. While the obtained flatness gain is 85 nm (1525-1610 nm) within the large input signal power region at -5 dBm. By choosing a proper pump wavelength that avoid the overlapping between Raman and erbium peaks gain, a wide flatness gain is obtained. © 2023 IEEE.

关键词： Raman scattering

来源：评论

学校读者我要写书评

暂无评论

Out-of-distribution Object Detection through Bayesian Uncertainty Estimation

Out-of-distribution Object Detection through Bayesian Uncert...

引用

International Conference on Information Fusion

作者： Tianhao Zhang Shenglin Wang Nidhal Bouaynaya Radu Calinescu Lyudmila Mihaylova Automatic Control and Systems Engineering The University of Sheffield UK Department of Electrical and Computer Engineering Rowan University USA Department of Computer Science University of York UK

The superior performance of object detectors is often established under the condition that the test samples are in the same distribution as the training data. However, in many practical applications, out-of-distribution (OOD) instances are inevitable and usually lead to uncertainty in the results. In this paper, we propose a novel, intuitive, and scalable probabilistic object detection method for OOD detection. Unlike other uncertainty-modeling methods that either require huge computational costs to infer the weight distributions or rely on model training through synthetic outlier data, our method is able to distinguish between in-distribution (ID) data and OOD data via weight parameter sampling from proposed Gaussian distributions based on pre-trained networks. We demonstrate that our Bayesian object detector can achieve satisfactory OOD identification performance by reducing the FPR95 score by up to 8.19% and increasing the AUROC score by up to 13.94% when trained on BDD100k and VOC datasets as the ID datasets and evaluated on COCO2017 dataset as the OOD dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Integration of ANN for Accurate Estimation and control in Wastewater Treatment 28

Integration of ANN for Accurate Estimation and Control in Wa...

引用

28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Ţiru, Andreea Elena Vasiliev, Iulian Diaconu, Larisa Vilanova, Ramon Voipan, Daniel Ratnaweera, Harsha Dunǎrea de Jos University of Galaţi Department of Automatic Control and Electrical Engineering Galaţi Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain Dunǎrea de Jos University of Galaţi Department of Computer Science and Information Technology Galaţi Romania Ås Norway

ISBN: (纸本)9798350339918

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so. © 2023 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Study of the Shock Loads Effect on the Operation of Multi-Motor Electric Drives of a Rolling Mill with a Second-order Elastic Coupling 5

Study of the Shock Loads Effect on the Operation of Multi-Mo...

引用

5th IEEE International Conference on Modern electrical and Energy System, MEES 2023

作者： Tytiuk, Valerii Kalinin, Alexey Druzhinin, Valeriy Kuznetsov, Vitalii Chornyi, Oleksii Busher, Victor Kryvyi Rih National University Department of Electromechanics Kryvyi Rih Ukraine Abylkas Saginov Karaganda Technical University Npjsc Department of Informative Computer Systems Karaganda Kazakhstan Karaganda Industrial University Npjsc Department of Power Engineering Temirtau Kazakhstan Ukrainian State University of Science and Technologies Department of the Electrical Engineering Dnipro Ukraine National University Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi Kremenchuk Ukraine National University "odessa Maritime Academy" Dept. of Electrical Engineering and Electronics Odessa Ukraine

ISBN: (纸本)9798350359787

This paper presents a study for optimizing a hot rolling mill. The paper is devoted to the study of ways to reduce the effect of shock loads of synchronous electric drives of the roughing mill group on the relative lengthening of the metal strip in the inter-stand gap of the rolling stands of the finishing mill group. The elasticity of the metal strip in the inter-stand gap of the rolling mill has a significant impact on the movement of intercoupled multi-motor electric drives of the finishing mill group. Another crucial route of exposure that influences the motion of the electric drives within the finishing mill group involves the electromagnetic connection between the drives in the roughing and finishing mill groups. The impact of the electromagnetically connected circuits is evident through the effect of shock loads from synchronous electric drives on the angular velocity of the direct current electric drives within the finishing mill group. The characteristics of the electromagnetic communication circuit are established by the power grid arrangement and equipment specifications. To assess the quality of work of electric drives of the finishing mill group, it is proposed to use the relative lengthening of the metal strip in the inter-stand gap, which is an important indirect indicator of the quality of rolling. The mathematical model of a hot rolling mill that takes into account both the elasticity of the metal strip that connects the DC electric drives of the finishing group, and the electromagnetic coupling circuit that takes into account the impact loads of synchronous electric drives of the roughing group on the example of the mill 1700 of ArcelorMittal Temirtau JSC was proposed in this paper. Using the mathematical model developed in Simulink software using the methods of planning the experiment, regression models were obtained to establish the dependence of the parameters of overexcitation of a synchronous motor on the magnitude of the voltage sag in the no

关键词： Electric loads

来源：评论

学校读者我要写书评

暂无评论

Realization of MIMO-SLSs from Markov Parameters via Forward/Backward Corrections

Realization of MIMO-SLSs from Markov Parameters via Forward/...

引用

European control Conference (ECC)

作者： Fethi Bencherki Semiha Türkay Hüseyin Akçay Department of Automatic Control Lund University Sweden Department of Electrical and Electronics Engineering Eskisehir Technical University Eskisehir Turkey

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper serves as a first identification step in a two-step model-based control synthesis problem of switched linear systems (SLSs). More precisely, we present an algorithm that addresses the realization of the multi-input/multi-output MIMO-SLSs from Markov parameters under mild assumptions on the dwell-times and the submodels. A key point of the proposed approach is the introduction of the forward and backward correction operators, which relieves the dependence on the choice of basis vectors in computing state-space matrices of the realizations. A numerical example illustrates the derived results.

关键词： Linear systems Europe Switches control systems Vectors

来源：评论

学校读者我要写书评

暂无评论

Probabilistic Optimal Power Flow Computation for Power Grid Including Correlated Wind Sources

SSRN

引用

SSRN 2024年

作者： Xiao, Qing Tan, Zhuangxi Du, Min School of Information and Electrical Engineering Hunan University of Science and Technology Hunan Province Xiangtan China Department of Automatic Control and Systems Engineering University of Sheffield South Yorkshire Sheffield United Kingdom

This paper sets out to develop an efficient probabilistic optimal power flow (POPF) algorithm to assess the influence of wind power on power grid. Given a set of wind data at multiple sites, the marginal distribution is fitted by a newly developed generalized Johnson system, the dependence structure of wind speeds is matched by the flexible Liouville copula. In order to lower the computational burden for solving POPF model, a Lattice sampling technique is developed to generate wind samples at multiple sites, and a Logistic mixture model is proposed to fit distributions of POPF outputs, which can quantify the effect of wind speed uncertainty on power grid. Finally, the proposed methods are illustrated by case studies on the IEEE 118-bus system. © 2024, The Authors. All rights reserved.

关键词： Electric load flow

来源：评论

学校读者我要写书评

暂无评论

A Predictive control based Scheme for Maximum Power Extraction of PMSG based Wind Turbine systems

A Predictive Control based Scheme for Maximum Power Extracti...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Fahimeh Shiravani Jose Antonio Cortajarena Patxi Alkorta Mikel Gonzalez Perez Oscar Barambones Department of Automatic Control and Systems Engineering School of Engineering of Gipuzkoa – EIG/Eibar Basque Country University Spain Department of Electronic Technology School of Engineering of Gipuzko– EIG/Eibar Basque Country University Spain Department of Automatic Control and Systems Engineering School of Engineering of Gipuzkoa-EIG/Eibar Basque Country University Spain Department of Automatic Control and Systems Engineering School of Engineering of Vitoria Basque Country University Spain

In this proposal, a predictive control scheme is considered for PMSG based wind turbine system in order to maximize power extraction. The main goal is to maintain the turbine tip-speed ratio (and consequently the power coefficient) at its optimal point and regulate the PMSG rotor speed in reaction to the variation of wind speed. The control of generator speed is done by employing a generalized predictive controller. This regulator by taking advantage of the predictive feature can prepare the generator to react to the upcoming wind in advance and consequently increases the efficiency of the turbine. Also, it has been demonstrated that this controller enhances the transient response of the system compared to the conventional methods. The proposed controller has been validated through Matlab/Simulink and an experimental test bench.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Stability and the Separation Principle in Output-Feedback Stochastic MPC with Random Packet Losses

引用

IFAC-PapersOnLine 2023年第2期56卷 3818-3823页

作者： Paul Trodden Paulo Loma-Marconi Iñaki Esnaola Department of Automatic Control & Systems Engineering University of Sheffield Sheffield S1 3JD UK

This paper considers a linear quadratic Gaussian (LQG) control problem with constraints on system inputs and random packet losses occurring on the communication channel between plant and controller. It is well known that, in the absence of constraints, the Separation Principle between estimator and controller holds when the channel employs a TCP-like protocol but not so under a UDP-like protocol. This paper gives a counterexample that shows that, under a model predictive control (MPC) scheme that handles the constraints, the Separation Principle does not hold even in the TCP-like case. Theoretical analysis characterizes and reveals a trade-off between estimation errors in the estimator and prediction errors in the controller. Counterintuitively, the poorer on-average performance of the estimator in the UDP case may be compensated by smaller prediction errors in the controller.

关键词： control and estimation with data loss Predictive control Kalman filtering Stochastic optimal control problems

来源：评论

学校读者我要写书评

暂无评论

CDQKL: Consensus-Based Distributed Quantum Kernel Learning

CDQKL: Consensus-Based Distributed Quantum Kernel Learning

引用

Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Wenxuan Ma Mengxiang Liu Ruilong Deng State Key Laboratory of Industrial Control Technology and the College of Control Science and Engineering Zhejiang University Hangzhou China Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

ISBN: (数字)9798350366778

ISBN: (纸本)9798350366785

The field of quantum computing has developed rapidly in recent years due to its promising trend of surpassing traditional machine learning in terms of speed and effectiveness. Quantum kernel learning is one of the paradigms of quantum machine learning, but the training of quantum kernel is time consuming. Therefore, this work makes the first attempt to introduce a consensus-based distributed approach to quantum kernel learning - named CDQKL - that only requires to exchange model parameter information between adjacent nodes while avoiding the need of sharing local training data. Through comparative experimental studies, the advantages of CDQKL in classification accuracy and convergence speed are verified. Considering the popularization of quantum computing cloud service and miniaturization of quantum terminals, the CDQKL adapting to this trend is able to play a vital role in data security, which implies the far-reaching significance of this work. Our code is available at https://***/Leisurivan/CDOKL.

关键词： Training Adaptation models Quantum computing Accuracy Training data Machine learning Market research

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：