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European control Conference (ECC)

作者： Manuel Lara Francisco Vázquez Jan-Willem van Wingerden Sebastiaan Paul Mulders Juan Garrido Department of Electrical Engineering and Automation University of Cordoba Cordoba Spain Delft Center for Systems and Control Faculty of Mechanical Engineering Delft University of Technology Delft The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In order to mitigate periodic blade loads in wind turbines, recent research has analyzed different Individual Pitch control (IPC) approaches, which typically use the multi-blade coordinate (MBC) transformation. Some of these studies show that the introduction of an additional tuning parameter in the MBC, namely the azimuth offset, helps to decouple the nonrotating axes in the MBC transformation and enhances the IPC performance. However, these improvements have been studied without considering the increased control effort performed by the pitch signal, which is the main negative side effect of the IPC. This work addresses this trade-off between pitch signal effort and blade fatigue reduction for IPC applied to a wind turbine operating in the full load region. Here, two IPC schemes, with and without additional azimuth offset, are designed and applied to a 15 MW monopile offshore wind turbine simulated with OpenFAST software. The optimal tuning of the IPC parameters is performed by means of a multi-objective optimization solved by genetic algorithms. The optimization procedure minimizes two objective functions related to pitch signal effort and blade fatigue load. The resulting Pareto fronts show a range of optimal solutions for each IPC scheme. The selected optimal solution for IPC with azimuth offset compared to the optimal solution for IPC without offset achieves improvements of more than 10% in blade load reduction maintaining similar pitch signal effort.

关键词： Azimuth Blades Simulation Fatigue Linear programming Software Wind turbines

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Liquid Filling Quality control System for Beverage Industry Using Image Processing (CNN)

Liquid Filling Quality Control System for Beverage Industry ...

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International Conference on control, automation and Systems ( ICCAS)

作者： B. Chatchapol W. Autanan W. Anan Department of Electrical Engineering Faculty of Electric Engineering Rajamangala University of Technology Lanna Chiang Mai Thailand Robotics Engineering and AI Faculty of Engineering Chiang Mai University Chiang Mai Thailand Department of Electronic Engineering and Automation Control System Faculty of Engineering Rajamangala University of Technology Lanna Chiang Mai Thailand

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The beverage industry has been leveraging automation to enhance production efficiency. An essential advancement involves the use of AI and image processing to ensure the high quality of products. Image processing systems employ sophisticated algorithms to meticulously inspect specific aspects of the production process (liquid level, lid sealing, text print). The CNN algorithm is primarily utilized to scrutinize water bottle images to verify their quality. Maintaining consistent production speed poses a challenge, underscoring the importance of examining the image processing system from various perspectives. The research proposed implementing a system that oversees liquid filling quality through an image processing algorithm, a camera module, and conveyor belt speed control to address. This system monitors liquid levels and bottle capping while the production line is operational. On average, the system achieves a 98.89 percent accuracy rate in detecting liquid levels and a 100 percent accuracy rate in sealing the lids. Furthermore, the conveyor speed control can adjust automatically to detect variations in product movement speed.

关键词： Liquids Image processing Velocity control Production Quality control Inspection Belts Filling Beverage industry Monitoring

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Predictive maintenance for electrical motors: Current approach and usage of artificial intelligence algorithms

Predictive maintenance for electrical motors: Current approa...

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International Conference on Methods and Models in automation and Robotics (MMAR)

作者： Tomasz Herzog Krzysztof Bartecki Faculty of Electrical Engineering Automatic Control and Computer Science Opole University of Technology Opole Poland Rockwell Automation Power Control Business Katowice Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

The article presents the current approach in artificial intelligence methods used in predictive maintenance for electrical motors. The study focuses on presenting data classification methods for fault detection and isolation using data from condition monitoring systems. We discuss the advantages and disadvantages of using machine learning methods like perceptron and Support Vector Machine (SVM) for fault classification problems. Our conclusion shows great interest in machine learning methods combined with condition monitoring systems. Our future research will focus on comparing SVM, perceptron networks, and other methods, such as K-nearest neighbors, with their possibility for implementation in embedded firmware systems.

关键词： Support vector machines Condition monitoring Accuracy Fault detection Artificial neural networks Machine learning Prediction algorithms

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Model and Software In-The-Loop Testing of Engine’s Speed and Load control Functionality

Model and Software In-The-Loop Testing of Engine’s Speed an...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Anam Tahir Pontus Prinsén Jari Böling Automation Engineering Faculty of Technology University of Turku Turku Finland Marine–R&D–Automation & Control Wärtsilä Finland Oy Vaasa Finland

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

This paper focuses on the designing of the engine simulation models using the Wärtsilä 31 (W31) dual fuel (DF) first-order marine engine model, operating on torque and the performance output is the engine speed. X-in-the-loop simulations are proposed using the closed-loop system of proportional integral derivative control designs with respect to manual tuning and direct synthesis techniques to test the engine’s speed and load control functionality. The model-in-the-loop simulation evaluates the performance of the engine model i.e. the model-based testing whereas the software-in-the-loop simulation verifies the engine model in a simulation environment using the W31DF UNIC control system. The simulation results show the effectiveness of the proposed testing methods with respect to stability and settling performance.

关键词： Adaptation models Torque Manuals Mathematical models Stability analysis Engines Tuning

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State of Health Assessment of Lithium Batteries Based on Fusion Model and Feature Extraction

State of Health Assessment of Lithium Batteries Based on Fus...

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Cognitive Computing and Complex Data (ICCD), International Conference on the

作者： Qiwei Zhang Yulong Li Peipei Cai Rongkai Zhao Tian Peng Smart Energy Division Huadong Engineering Corporation Limited Hangzhou China Automation Engineering Room Hangzhou Huachen Power Control Engineering Corporation Limited Hangzhou China Beidou Innovation Studio Hangzhou Huachen Power Control Engineering Corporation Limited Hangzhou China Faculty of Automation Huaiyin Institute of Technology Huai’an China

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

Lithium battery State of Health (SOH) is crucial for stable operation and reducing failure risks. This paper identifies three key health features—IC curve peak value, constant voltage drop discharge time, and IC curve peak voltage—through Pearson correlation analysis. A multi-model fusion approach is utilized to construct and train three individual models: Temporal Convolutional Network (TCN), Extreme Learning Machine (ELM), and Long Short-Term Memory Network (LSTM). Additionally, three pairwise fusion models—TCN-LSTM, TCN-ELM, and ELM-LSTM—and a comprehensive TCN-LSTM-ELM model are developed. Validation using NASA dataset shows that TCN-LSTM-ELM fusion model achieves the highest prediction accuracy.

关键词： Training Accuracy Computational modeling Voltage Predictive models Lithium batteries Data models Integrated circuit modeling Optimization Long short term memory

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Toward Automating the Composition of Digital Twins Within System-of-Systems

Toward Automating the Composition of Digital Twins Within Sy...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Milapji Singh Gill Jingxi Zhang Andreas Wortmann Alexander Fay Institute of Automation Technology Helmut Schmidt University Hamburg Germany Institute of Control Engineering of Machine Tools and Manufacturing Units University of Stuttgart Germany Chair of Automation Ruhr University Bochum Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Cyber-Physical Production Systems necessitate efficient configuration and continuous reconfiguration to adapt to evolving requirements and shifting goals. This process involves integrating various system structures to derive new functions and behaviors. The concept of the Digital Twin, which allows for effective integration and testing, is instrumental in facilitating this task. However, a fundamental prerequisite is that Digital Twins of individual system components must be composed efficiently and in accordance with dynamic System-of-Systems. We address this challenge by introducing an approach for the automated horizontal and vertical composition of Digital Twins, aimed at minimizing manual intervention and enhancing adaptability. Therefore, a pipeline specifically designed for this goal is proposed, which includes the generation of new functions and behaviors. This approach is intended to provide a foundation for future research.

关键词： Production systems Instruments Pipelines Digital twins Manufacturing automation Testing

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High-Precision Dimensional Measurement for Digital Crown Part of Smartwatch from Microscopic Image

High-Precision Dimensional Measurement for Digital Crown Par...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Hongqiang Lyu Yuhang Zhang Liang Bai Shengjun Xu Huangwei Zhong Yuan Liu Faculty of Electronic and Information Engineering School of Automation Science and Engineering Xi'an Jiao tong University Shaanxi China School of Information and Control Engineering Xi'an University of Architecture and Technology Shaanxi China

Digital crown is a precision part used for human-computer interaction in the smartwatch. The diameter of the digital crown determines its grade. Currently, mainly used Coordinate Measuring Machine(CMM) to measure the diameter of digital crown, but the measurement method has the problem of high cost and low efficiency. To address the problem, we propose a high-precision dimensional measurement system for digital crown part of smartwatch. The system consists of four modules: microscopic image acquisition module, central host, machine vision software and PLC control module. The image of digital crown is captured by the microscopic image acquisition module and sent to the software through the central host. In the machine vision software, we propose a defect detection algorithm using ResNet to filter defective digital crown in real time, and we design a circle detection algorithm based on edge point tracking to measure the diameter of digital crown. The measurement result is sent to the PLC control module through wireless transmission and control the mechanical suction cups to place the part. Finally, we create a dataset to test the performance of the system, the defect detection model achieves an accuracy of 97.33% and a runtime of 47ms, the dimensional measurement algorithm achieves a maximum error of 0.003878mm, a grading accuracy of 95.29%, and a measurement time of 465ms.

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Federated Intelligence for Intelligent Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 1-5页

作者： Zhang, Weishan Zhang, Baoyu Jia, Xiaofeng Qi, Hongwei Qin, Rui Li, Juanjuan Tian, Yonglin Liang, Xiaolong Wang, Fei-Yue School of China University of Petroleum Qingdao China Department of Data Management Big Data Centre Beijing Beijing China Technology Company Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This letter is a brief summary of a series of IEEE TIV's decentralized and hybrid workshops (DHWs) on Federated Intelligence for Intelligent Vehicles. The discussed results are: 1) Different scales of large models (LMs) can be federated and deployed on IVs, and three types of federated collaboration between large and small models can be adopted for IVs. 2) Federated fine-tuning of LMs is beneficial for IVs data security. 3) The sustainability of IVs can be improved through optimizing existing models and continuous learning using federated intelligence. 4) LM-enhanced knowledge can make IVs smarter. IEEE

关键词： Intelligent vehicle highway systems

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Automating RTGC with PID control: Utilizing Camera-Based Image Processing and Object Detection

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IFAC-PapersOnLine 2024年第7期58卷 299-304页

作者： Steven Bandong Yul Y. Nazaruddin Augie Widyotriatmo Muhammad R. Miransyahputra Yan Setiaji Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

The high traffic in the container yard requires effective management, and one method to address this is through automation. The Rubber Tyred Gantry Crane (RTGC) plays a crucial role in container yards. Automating the RTGC involves determining the container’s location and sway angle to provide feedback for the control system. The advancements in computer vision technology offer a unique solution to tackle these challenges. This paper proposes image processing as a means to sense the sway angle and MobileNet SSD to detect the container’s location. The proposed method yields accurate measurement results and is integrated with optimized PID-PD for position and sway angle control in RTGC. The effectiveness of the proposed method is demonstrated through successful performance in both simulation and experiments conducted on a laboratory-scale RTGC prototype.

关键词： port automation RTGC control system computer vision optimization camera based sensor

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Digital CEOs in Digital Enterprises:Automating,Augmenting,and Parallel in Metaverse/CPSS/TAOs

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 820-823页

作者： Juanjuan Li Rui Qin Sangtian Guan Xiao Xue Peng Zhu Fei-Yue Wang with State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Intelligence and Computing Tianjin UniversityTianjin 300072China School of Economics and Management Nanjing University of Science and TechnologyNanjing 210094China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

BIG models or foundation models are rapidly emerging as a key force in advancing intelligent societies[1]–[3]Their significance stems not only from their exceptional ability to process complex data and simulate advan... 详细信息

关键词： exceptional Auto advancing

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