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arXiv 2023年

作者： Jones, Morgan The Department of Automatic Control and Systems Engineering The University of Sheffield United Kingdom

This paper introduces a novel approach for learning polynomial representations of physical objects. Given a point cloud data set associated with a physical object, we solve a one-class classification problem to bound the data points by a polynomial sublevel set while harnessing Sum-of-Squares (SOS) programming to enforce prior shape knowledge constraints. By representing objects as polynomial sublevel sets we further show it is possible to construct a secondary SOS program to certify whether objects are packed correctly, that is object boundaries do not overlap and are inside some container set. While not employing reinforcement learning (RL) in this work, our proposed secondary SOS program does provide a potential surrogate reward function for RL algorithms, autonomously rewarding agents that propose object rotations and translations that correctly pack objects within a given container set. Copyright © 2023, The Authors. All rights reserved.

关键词： Containers

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Pneumonia Detection from X-ray Images Using Convolutional Neural Networks

Pneumonia Detection from X-ray Images Using Convolutional Ne...

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International Conference on control systems and Computer Science (CSCS)

作者： Viorel Dediu Andreea Udrea Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Bucharest Romania

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia.

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Efficient and Collaborative Decisions for Supplier-Customer Services Management

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Procedia Computer Science 2022年 214卷 1144-1151页

作者： Catalin Dimon Dumitru Popescu Radu Bîlbîie Department of Automatic Control and Systems Engineering UPB Bucharest Romania

The research work presents a original solution for increasing the efficiency on management Supplied-Customer Services (SCS), based on a causal graph configuration. This approach expresses the connection, interaction, and collaboration between the two main actors, suppliers and consumers of goods and products. The causal graph model is intended for management of supply resources, production capacities, transport activities and customer demands. Initial configuration of this a priori generated graph includes the suppliers and consumers distributed in nodes and the interconnections expressed by the arches of the graph. A causal operator is introduced, which offer the efficient decisions propagation for the estimated solution of the supplier-customer services (SCS) problem. The customers can be served by the corresponding suppliers, or the suppliers must satisfy the services of the consumers, respectively. The road traffic is chosen for transport activities at a specific model to traffic network and appropriate control to avoid congestion and increase the real-time traffic performances for (SCS) management. The effectiveness of the proposed approach is visible on large structures of the supply-customer networks in different industrial and economic fields.

关键词： supplier customer services causal graph control network transport system management

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Estimating Wind Energy Potential: Advanced Smart Hybrid VAWT Analysis in Banjarmasin, Indonesia 6

Estimating Wind Energy Potential: Advanced Smart Hybrid VAWT...

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6th International Conference on Power engineering and Renewable Energy, ICPERE 2024

作者： Irawan, Elysa Nensy Miyagawa, Mei Putra, Maulana Yamashita, Ken-Ichiro Fujita, Goro Functional Control Systems Shibaura Institute of Technology Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan Indonesia Agency for Meteorology Climatology and Geophysics Centre for Instrumentation Calibration and Engineering Jakarta Indonesia Salesian Polytechnic Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798331504694

This study explores the potential of smart hybrid Savonius-Darrieus wind turbines to optimize wind energy capture in Indonesia, a country with significant wind resources. With solar and wind energy leading the renewable energy transition, this research focuses on enhancing wind turbine efficiency in regions with variable wind speeds. The hybrid Savonius-Darrieus turbine integrates the complementary strengths of both turbine types, employing a solenoid mechanism to switch between modes and a filtering method to stabilize operation. Our results demonstrate that this innovative design significantly reduces mechanical wear and operational instability by minimizing unnecessary switching events. Testing in Banjarmasin, Indonesia, the daily average wind energy potential for the smart hybrid and conventional hybrid turbines is calculated to be 6.1 kWh and 4.7 kWh, respectively. This condition revealed that the smart hybrid turbine generates approximately 30.89% more power than conventional hybrid turbines, highlighting its superior adaptability to fluctuating wind conditions. The turbine's ability to maintain efficient energy capture across a wide range of wind speeds underscores its potential for broader application in diverse environmental settings. © 2024 IEEE.

关键词： Windmill

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Data-driven Causal Association Discovery in Manufacturing Industries 41

Data-driven Causal Association Discovery in Manufacturing In...

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第41届中国控制会议

作者： Yiming Li Jia Xu Li Li Benoit Iung Department of Control Science & Engineering Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Nancy Research Center for Automatic Control (CRAN CNRS UMR 7039)Lorraine University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of smart sensors,information storage,processing technology and computer performance,large amounts of operating data collected from production process provide opportunities as well as challenges in remaining useful life(RUL) *** one hand,data-driven analysis approaches are experiencing a fast *** the other hand,the collected variables may be redundant,noisy and high-dimensional for ***,data dimension reduction is applied for eliminating useless *** from correlation-based methods,causal inference methods can obtain reliable models reflecting causal relationships among interesting ***,the latter is more suitable in data dimension *** this study,we use PCMCI+,a causal discovery method based on graph model,that handles both lagged and contemporaneous relationships in multi-variable time *** validate this method on time series data extracted directly from a medium frequency quenching *** obtained results confirm that PCMCI+is able to recognize causal associations among various sensor *** instance,variables in the same process have relatively larger causal relationships than those in different processes.

关键词： causal discovery manufacturing equipment PCMCI+ multi-sensor

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Locating Faults on Overhead Power Transmission Lines of 110 kV and Above Using Emergency Mode Parameters

Locating Faults on Overhead Power Transmission Lines of 110 ...

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International Youth Conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Dmitriy Sharygin Galina Filatova Andrey Yablokov Department of electric power systems automatic control Ivanovo State Power Engineering University (ISPU) Ivanovo Russia

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The article is devoted to the development of new fault location algorithms based on emergency mode parameters at instantaneous values on overhead power transmission lines of 110 kV and above. Increasing the accuracy of fault location algorithms is an important and urgent task. The methodological and simulation errors of fault location are directly related to the configuration of the power transmission line. The presence of parallel power transmission lines, mutual induction or branch substations affects the accuracy of fault location. In this work, the authors modernize their own previously developed fault location algorithms based on instantaneous values for complex power transmission line configurations. The developed fault location algorithms do not require additional corrections or means for processing primary signals and can be successfully applied when using data from digital in-strumental transformers. The studies of the algorithms were carried out on the simulation models of the overhead power lines in the Simulink/MATLAB software package. The remote fault location of the damage was carried out according to the parameters of the emergency mode. The assignment of parameters for the simulation modeling is carried out using the Monte Carlo method with subsequent statistical processing of the results and the construction of a justified inspection zone.

关键词： Instrument transformers Power transmission lines Accuracy Substations Voltage measurement Software packages Software algorithms Fault location Inspection Transmission line measurements

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Correction of Time-varying PMU Phase Angle Deviation with Unknown Transmission Line Parameters

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CSEE Journal of Power and Energy systems 2023年第1期9卷 315-325页

作者： Ancheng Xue He Kong Feiyang Xu Junbo Zhao Naichao Chang Joe H.Chow Haiyan Hong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Department of Electrical and Computer Engineering University of ConnecticutStorrs06268USA National Electric Power Dispatching and Control Center Beijing 100031China Department of Electrical Computerand Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNY 12180USA

Phasor measurement units(PMUs)provide useful data for real-time monitoring of the smart ***,there may be time-varying deviation in phase angle differences(PADs)between both ends of the transmission line(TL),which may deteriorate application performance based on *** address that,this paper proposes two robust methods of correcting time-varying PAD deviation with unknown parameters of TL(ParTL).First,the phenomena of time-varying PAD deviation observed from field PMU data are *** general formulations for PAD estimation are then *** simplify the formulations,estimation of PADs is converted into the optimal problem with a single ParTL as the variable,yielding a linear estimation of *** latter is used by second-order Taylor series expansion to estimate PADs *** reduce the impact of possible abnormal amplitude data in field data,the IGG(Institute of Geodesy&Geophysics,Chinese Academy of Sciences)weighting function is *** using both simulated and field data verify the effectiveness and robustness of the proposed methods.

关键词： Correction line parameters parameter identification phasor measurement time-varying phase angle difference deviation

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Sampling-efficient path planning and improved actor-critic-based obstacle avoidance for autonomous robots

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Science China(Information Sciences) 2024年第5期67卷 197-214页

作者： Yefeng YANG Tao HUANG Tianqi WANG Wenyu YANG Han CHEN Boyang LI Chih-yung WEN Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Center for Control Theory and Guidance Technology Harbin Institute of Technology School of Engineering The University of Newcastle Research Center for Unmanned Autonomous Systems The Hong Kong Polytechnic University

Autonomous robots have garnered extensive utilization in diverse fields. Among the critical concerns for autonomous systems, path planning holds paramount importance. Notwithstanding considerable efforts in its development over the years, path planning for autonomous systems continues to grapple with challenges related to low planning efficiency and inadequate obstacle avoidance response in a timely *** study proposes a novel and systematic solution to the path planning problem within intricate office buildings. The solution consists of a global planner and a local planner. To handle the global planning aspect, an adaptive clustering-based dynamic programming rapidly exploring random tree(ACDP-RRT) algorithm is proposed. ACDP-RRT effectively identifies obstacles on the map by leveraging geometric *** obstacles are then represented as a collection of sequentially arranged convex polygons, optimizing the sampling region and significantly enhancing sampling efficiency. For local planning, a network decoupling actor-critic(ND-AC) algorithm is employed. The proposed ND-AC simplifies the local planner design process by integrating planning and control loops into a neural network(NN) trained via an end-to-end model-free deep reinforcement learning(DRL) framework. Moreover, the adoption of network decoupling(ND) techniques leads to an improved obstacle avoidance success rate when compared to conventional actor-critic(AC)-based methods. Extensive simulations and experiments are conducted to demonstrate the effectiveness and robustness of the proposed approach.

关键词： rapidly exploring random tree (RRT) adaptive clustering network decoupling actor critic (AC) path planning

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An Interacting Multiple Model Correntropy Kalman Filter Approach for Unmanned Aerial Vehicle Localisation 16

An Interacting Multiple Model Correntropy Kalman Filter Appr...

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16th International Conference on INnovations in Intelligent systems and Applications, INISTA 2022

作者： Candan, Fethi Beke, Aykut Shen, Chen Mihaylova, Lyudmila University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Aselsan Department of Control Systems Design Ankara06750 Turkey 310018 China

ISBN: (数字)9781665498104

ISBN: (纸本)9781665498104

This paper compares a conventional interacting multiple model Kalman filter (IMM-KF) filter and an interacting multiple models with maximum correntropy Kalman filter (IMM-MCKF). A nonlinear UAV dynamics model was used to compare these two methods. The compared filters estimated the position of the UAV under the noise distribution. Although KF has reliable accuracy, MCKF has got better results under non-Gaussian or mixed distributions. At this point, these filters have been investigated under maneuver and non-maneuver motion, and it is known that better advantages will be shown when both filters are used in the IMM. These filters have been compared under non-Gaussian distributions, and the Student's-T distribution has been selected as a non-Gaussian type. The performance validation and testing stages are carried out with variable degrees of freedom, and scaling matrix factors for the Student's-T distributions have been used. Results from simulation tests from 3000 independent Monte-Carlo runs are presented. In these experiments, UAV models and UAV trajectory results have been used. © 2022 IEEE.

关键词： Kalman filters

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