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Description and comparison of fault detection algorithms based on a selected building automation device

Bulletin of the Polish Academy of Sciences: Technical Sciences 2025年第3期73卷

作者： Wlostowska, Sandra Kawa, Bartlomiej Borkowski, Piotr Department of Electrical Apparatus Faculty of Electrical Electronics Computer and Control Engineering Lodz University of Technology Lódź Poland

The article compares selected classification algorithms and those dedicated to anomaly detection. The models used temperature measurements in four rooms simulated in the MATLAB Simscape environment as test signals. The empirical part of the work consists of two parts. In the first one, an example data from the simulated building heating model object, models were built using unsupervised and supervised machine learning algorithms. Then, data from the facility was collected again with changed parameters (failures occurred at times other than the test ones, and the temperature patterns differed from those recorded and used to train the models). The algorithm effects and test signals (temperature changes) were saved in the database. The results were presented graphically in the Grafana program. The second part of the work presents a solution in which the analysis of the operating status of the heating system takes place in real time. Using an OPC server, data was exchanged between the MATLAB environment and the database installed on a virtual machine in the Ubuntu system. The conclusions present the results and collect the authors’ suggestions regarding the practical applications of the discussed classification models. © 2025 The Author(s).

关键词： Support vector machines

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Streamlining the New Product Introduction by Integrating the Escalation Process 18th

Streamlining the New Product Introduction by Integrating the...

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18th International Conference on Interdisciplinarity in engineering, INTER-ENG 2024

作者： Zgirdea, Mihai Ionica, Andreea Cristina Leba, Monica Engineering and Management Doctoral School University of Petrosani 20 Universitatii Petrosani332006 Romania Management and Industrial Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania Computer and System Control Engineering Department University of Petrosani 20 Universitatii Petrosani332006 Romania

ISBN: (纸本)9783031813771

In the dynamic landscape of modern business, companies face the challenge of rapidly introducing new products to meet consumer demands. This research aims to propel NPI efficiency, focusing on the automotive industry, by enhancing cooperative effectiveness and streamlining processes. The overarch- ing objective is to expedite high-quality product with the focus of introducing a controlled escalation process to facilitate swift corrections and improvements throughout each phase of NPI. To realize these objectives, a comprehensive NPI system has been developed. Integration of an escalation process into this sys- tem enables hierarchical escalation of concerns, blocking points, and new pro- cesses, addressing common project delays. The proposed software stands out for its unique integration of the escalation process, ensuring that all organizational members are promptly informed of any deviations using a dynamic project status feature, adapting as the project progresses. The integrated escalation process not only addresses anomalies promptly but also quantifies the time taken to restore normalcy or implement corrections, thereby fostering a more responsive and effi- cient NPI framework. The paper is organized into sections comprising a literature review on NPI methodologies, the integration of an escalation process into the NPI framework, a case study illustrating the implementation of the escalation process in an existing NPI methodology, and the subsequent results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Automotive Industry Collaborative Teamwork controlled Escalation Process Dynamic NPI Software New Product Introduction (NPI)

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Quality-Relevant Modeling and Monitoring of Industrial Cyber-Physical Systems: The Semi-Supervised Dynamic Latent Variable Models

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 39-47页

作者： Zhou, Le Wang, Yaoxin Wu, Yuanqing He, Shenghuang Song, Zhihuan Zhejiang University of Science and Technology Department of Automation and Electrical Engineering Hangzhou310023 China Guangdong University of Technology Department of Automation Guangzhou510006 China Dongguan University of Technology Department of Computer Science and Technology Dongguan523808 China Ningbo Industrial Internet Institute Ningbo315012 China Zhejiang University Department of Control Science and Engineering Hangzhou310027 China

In modern industrial cyber-physical systems, a mass of process variables has been obtained by the high-sampling online sensors. Meanwhile, the key quality indexes are usually obtained infrequently from the laboratory. Hence, these quality variables are with low sampling rate. To avail of the complete process and quality variables with various sampling rates in the dynamic processes, a set of semi-supervised dynamic latent variable models are proposed for dynamic modeling and quality-relevant monitoring. The proposed models have built a unified structure to consider both the auto-correlations and cross-correlations between the process and quality variables with unbalanced sampling sizes. Hence, the feature extraction of the time series data is dynamically adjusted under the guidance of the quality variables. Then, the quality-relevant monitoring schemes are proposed, which is validated by a numerical case and an actual wastewater treatment process. © 2024 IEEE. All rights reserved.

关键词： Indexes Probabilistic logic Kalman filters Noise Cyber-physical systems Analytical models Parameter estimation Time series analysis Process monitoring Numerical models

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Multilingual web traffic forecasting for network management using artificial intelligence techniques

Results in Engineering

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Results in engineering 2025年 26卷

作者： Samaan, Sama Salam Korial, Ayad E. Sarra, Raniya R. Humaidi, Amjad J. Computer Engineering Department University of Technology- Iraq Baghdad10001 Iraq Control and Systems Engineering Department University of Technology- Iraq Baghdad10001 Iraq

Web traffic forecasting is critical for ensuring an effective allocation of network resources for websites to avoid potential congestion and maintain service quality. Analyzing traffic forecasts helps network operators plan for future capacity needs to accommodate unexpected traffic loads. Multilingual web platforms present unique challenges due to varying traffic patterns across several languages. In this paper, modular architecture is proposed for multilingual web traffic forecasting using deep learning models. The architecture consists of multiple processes, from collecting the traffic data of the targeted website to preparing the data to be in a suitable form to feed the deep learning models. This study explores time-series forecasting methods using three deep learning models: long short-term memory (LSTM), gated recurrent units (GRU), and convolutional neural networks (CNN). A comprehensive dataset was collected from the BBC World Service websites in three languages—English, Arabic, and Persian—spanning the period from January 2017 to July 2024. The performance of the employed deep learning models is evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), relative root mean square error (RRMSE), and R-squared (R²). Results show that the CNN model outperformed the GRU and LSTM models in accuracy and variance explanation across all three language datasets. The CNN model demonstrated superior performance, achieving R² scores of 0.980, 0.989, and 0.994;MAE values of 47,195, 5090, and 6714;RRMSE values of 1.43 %, 1.90 %, and 1.86 %;and RMSE values of 61,372, 6342, and 9376 for the English, Arabic, and Persian websites, respectively. These results highlight the potential of deep learning models in capturing complicated patterns of multilingual web platforms, making them suitable for real-world network management. © 2025

关键词： Convolutional neural networks

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Joint Optimization of Wind Farm Layout Considering Yaw control 8th

Joint Optimization of Wind Farm Layout Considering Yaw Cont...

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Yiqun Jiang, Ruolin Chen, Yuanye Fang, Fang School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819602247

As wind farms continue to grow in size, minimizing wake losses between turbines in layout design becomes increasingly important. Current wind farm layout strategies often focus on the performance of individual turbines without considering wake interactions. This study introduces a coordinated control approach that considers wake effects and demonstrates an improved yaw control results to reduce the impact of wake interactions. By implementing cooperative yaw control among turbines and using the NSGA-II algorithm, the study establishes a dual optimization problem of minimizing turbine spacing and maximizing power output, ultimately yielding the optimal layout for wind turbines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wind turbines

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Delayed Transitions in GPenSIM 1st

Delayed Transitions in GPenSIM

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Feng, Yuming Samolej, Slawomir Davidrajuh, Reggie School of Computer Science and Engineering Chongqing Three Gorges University Wenzhou China Department Computer and Control Engineering Rzeszow University of Technology Rzeszow Poland Department Electrical Engineering and Computer Science University of Stavanger Stavanger Norway

ISBN: (纸本)9789819646128

The General-purpose Petri Net Simulator (GPenSIM) is a tool for modeling, simulation, and performance analysis of discrete event systems. GPenSIM is specially designed to model real-life industrial systems. Hence, the transitions in GPenSIM represent real-life events, such as machines. However, this induces a problem, namely that an enabled transition consumes tokens from its input places immediately. This act of an enabled transition immediately consuming tokens gives only monetarily visibility to the tokens, which can be a problem for certain cases where we need to see the tokens in their input places for a while. This paper proposes a method to delay an enabled transition ("delayed transitions") so that the tokens it is supposed to consume from its input places will be visible for a while. This paper, after presenting the theory and the method, also presents an application (the cat and mouse problem) of the delayed transitions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Discrete event simulation

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Application Interface for GPenSIM 1st

Application Interface for GPenSIM

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Feng, Yuming Samolej, Slawomir Davidrajuh, Reggie School of Computer Science and Engineering Chongqing Three Gorges University Wenzhou China Department of Computer and Control Engineering Rzeszow University of Technology Rzeszow Poland Department of Electrical Engineering and Computer Science University of Stavanger Stavanger Norway

ISBN: (纸本)9789819646128

The General-purpose Petri Net Simulator (GPenSIM) is a tool used by researchers to model, simulate, and analyze the performance of discrete event systems. Its popularity stems from its simple interface, extensibility, and compatibility with the MATLAB platform. This paper focuses on the crucial role of GPenSIM in Petri Net model-based software-to-software and software-to-hardware access and control, highlighting unique features and capabilities in its application interface. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： MATLAB

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Event-triggered hierarchical distributed control strategy for current sharing and voltage regulation in microgrids

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Electric Power Systems Research 2025年 247卷

作者： Zhao, Xingyang Liu, Boning Wei, Bo School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Aiming at addressing the problem of proportional load current distribution and weighted average voltage regulation in DC microgrids, this paper proposes a distributed control strategy based on event-triggered communication. The core of the control strategy is the use of hierarchical control, which avoids the direct interaction of current by introducing an auxiliary control layer. This design makes the system have the function of privacy protection, so that neighbors cannot directly obtain the local distributed generation units (DGUs) information and external observers cannot directly obtain the current information. An event-triggered communication method is designed. Compared with the traditional periodic communication method, event-triggered communication only triggers the communication when certain conditions are satisfied, which avoids unnecessary communication and makes the system more efficient and economical. Using the Lyapunov method, we show that the proposed control algorithm can achieve the control objectives. The effectiveness of the proposed control algorithm is further verified by simulations. © 2025 Elsevier B.V.

关键词： Distributed parameter control systems

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IMC Based PID controller for Spherical Tank Liquid Level control

IMC Based PID Controller for Spherical Tank Liquid Level Con...

引用

AIML-Applications for engineering & Technology (ICAET), International Conference on

作者： C. B. Kadu V. P. Bhosale P. S. Vikhe V. V. Mandhare Department of Instrumentation & Control Engineering Pravara Rural Engineering College Loni India Department of Computer Engineering Pravara Rural Engineering College Loni India

ISBN: (数字)9798350355611

ISBN: (纸本)9798350355628

In the process industries, it's hard to control a non-linear process. Nonlinear behavior is frequently seen in real processes. The challenging problem of controlling a spherical tank is result of its nonlinearity caused by the continuously varying cross section. An IMC-based PID controller is employed to improve efficiency of controlling the level of spherical tanks which exhibit nonlinear dynamics. For processes up to second-order with dead time and first-order numerator dynamics, a single tuning parameter will be offered. The process model is determined employing mathematical modeling and standard step response-based system identification. The laboratory model of an interacting and non-interacting nonlinear system is introduced, which is capable of performing more complex tasks. To verify the effectiveness of the suggested IMC based PID controller, results of real-time experiments and a simulation study on spherical tank level control are incorporated.

关键词： Process control Real-time systems Mathematical models Regulation Nonlinear dynamical systems System identification Reliability Level control Tuning Standards

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A Fusion Model for Artwork Identification Based on Convolutional Neural Networks and Transformers

arXiv

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arXiv 2025年

作者： Wang, Zhenyu Song, Heng The School of Control and Computer Engineering North China Electric Power University Beijing102206 China

The identification of artwork is crucial in areas like cultural heritage protection, art market analysis, and historical research. With the advancement of deep learning, Convolutional Neural Networks (CNNs) and Transformer models have become key tools for image classification. While CNNs excel in local feature extraction, they struggle with global context, and Transformers are strong in capturing global dependencies but weak in fine-grained local details. To address these challenges, this paper proposes a fusion model combining CNNs and Transformers for artwork identification. The model first extracts local features using CNNs, then captures global context with a Transformer, followed by a feature fusion mechanism to enhance classification accuracy. Experiments on Chinese and oil painting datasets show the fusion model outperforms individual CNN and Transformer models, improving classification accuracy by 9.7% and 7.1%, respectively, and increasing F1 scores by 0.06 and 0.05. The results demonstrate the model’s effectiveness and potential for future improvements, such as multimodal integration and architecture optimization. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolutional neural networks

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