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Artificial Intelligence Technology (ACAIT), Asian Conference on

作者： Dong Li Kaixun He Lili Tao Hanlong Liu College of Electrical and Automation Engineering Shandong University of Science and Technology Qingdao China Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology China College of Intelligent Manufacturing and Control Engineering Shanghai Second University of Technology China

ISBN: (数字)9798331517090

ISBN: (纸本)9798331517106

Wind turbine equipment, as a key component in the process production control of thermal power plants, directly affects the power generation efficiency of the plant. Due to the non-linear and non-stationary nature of the signals acquired from wind turbine sensors, this paper presents a novel active fault diagnosis approach for wind turbine systems based on deep forest techniques. Initially, multi-dimensional time-domain features are extracted from the raw fault data. Simultaneously, important features are selected from multiple angles by integrating Pearson correlation coefficient and Borutashap algorithm, following the principles of active fault diagnosis. Additionally, the whale optimization algorithm (WOA) is utilised to search the optimal sinusoidal auxiliary signal parameter, thereby highlighting specific fault manifestations and improving the model’s diagnostic capability. The deep forest, with its strong classification ability and noise resistance, overcomes the overfitting issue in shallow machine learning algorithms and the complex parameter tuning in deep learning. Then, the designed sinusoidal auxiliary signal is used as an additional input to the deep forest model, enabling the final fault classification outcomes. Finally, experiments are conducted using a wind turbine power transmission system fault simulator. The experimental results demonstrate an improvement in fault diagnosis accuracy, confirming the effectiveness of the proposed method.

关键词： Fault diagnosis Deep learning Machine learning algorithms Feature extraction Whale optimization algorithms Regression analysis Wind turbines Random forests Tuning Power generation

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Adaptive Fault-Tolerant control for Stochastic High-Order Fully Actuated Systems with Local Faults

Adaptive Fault-Tolerant Control for Stochastic High-Order Fu...

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Fault Detection, Supervision and Safety for Technical processes (SAFEprocess), CAA Symposium on

作者： Xueqing Liu Maoyin Chen Li Sheng Donghua Zhou Department of Automation Tsinghua University Beijing China College of Control Science and Engineering China University of Petroleum (East China) Qingdao China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China

This paper portrays a class of local faults, whose basic characteristic is that the fault occurs only when the system is in a certain state domain. In engineering practice, such faults are prevalent and could affect efficiency greatly. To accurately tolerate these local faults, a novel control strategy is proposed. The globally asymptotical stability in probability is guaranteed by using time-varying gains on pre-divided fields. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed framework.

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Research on target grab of leg-arm cooperative robot based on vision

Research on target grab of leg-arm cooperative robot based o...

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Data Driven control and Learning Systems (DDCLS)

作者： Haichuang Xia Xiaoping Zhang School of Electrical and Control Engineering North China University of Technology Beijing China College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Department of Engineering University of Cambridge Cambridge UK

Leg-arm cooperative robot can not only expand the motion space of traditional manipulator, but also make up the operation ability of traditional mobile robot. This paper studies the target grab of leg-arm cooperative robot based on vision. First of all, independently develop the leg-arm cooperative robot. Secondly, for the operation of the manipulator, a height-angle uncoupling PID algorithm is innovatively designed in the cylindrical coordinate system. The target position information obtained by the YOLOv3 algorithm is used as feedback to realize the accurate control of the manipulator, which can avoid the complex process of trajectory planning. Furthermore, combined with three-element trajectory planning method and motion control scheme under triangular gait, a target grab control strategy for the leg-arm cooperative robot is designed, including the height allocation decision maker and the target tracking controller. Finally, the proposed algorithm and schemes are verified with the entity robot.

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GenoHoption: Bridging Gene Network Graphs and Single-Cell Foundation Models

arXiv

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arXiv 2024年

作者： Cheng, Jiabei Li, Jiachen Yang, Kaiyuan Shen, Hongbin Yuan, Ye Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai China Key Laboratory of Biopharmaceutical Preparation and Delivery Chinese Academy of Sciences Beijing China State Key Laboratory of Biochemical Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing China

The remarkable success of foundation models has sparked growing interest in their application to single-cell biology. Models like Geneformer and scGPT promise to serve as versatile tools in this specialized field. However, representing a cell as a sequence of genes remains an open question since the order of genes is interchangeable. Injecting the gene network graph offers gene relative positions and compact data representation but poses a dilemma: limited receptive fields without in-layer message passing or parameter explosion with message passing in each layer. To pave the way forward, we propose GenoHoption, a new computational framework for single-cell sequencing data that effortlessly combines the strengths of these foundation models with explicit relationships in gene networks. We also introduce a constraint that lightens the model by focusing on learning the predefined graph structure while ensuring further hops are deducted to expand the receptive field. Empirical studies show that our model improves by an average of 1.27% on cell-type annotation and 3.86% on perturbation prediction. Furthermore, our method significantly decreases computational overhead and exhibits few-shot potential. Overall, GenoHoption can function as an efficient and expressive bridge, connecting existing single-cell foundation models to gene network graphs. Copyright © 2024, The Authors. All rights reserved.

关键词： Network theory (graphs)

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GenoHoption: Bridging Gene Network Graphs and Single-Cell Foundation Models

GenoHoption: Bridging Gene Network Graphs and Single-Cell Fo...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jiabei Cheng Jiachen Li Kaiyuan Yang Hongbin Shen Ye Yuan Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai China Key Laboratory of Biopharmaceutical Preparation and Delivery Chinese Academy of Sciences Beijing China State Key Laboratory of Biochemical Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

The remarkable success of foundation models has sparked growing interest in their application to single-cell biology. Models like Geneformer and scGPT promise to serve as versatile tools in this specialized field. However, representing a cell as a sequence of genes remains an open question since the order of genes is interchangeable. Injecting the gene network graph offers gene relative positions and compact data representation but poses a dilemma: limited receptive fields without in-layer message passing or parameter explosion with message passing in each layer. To pave the way forward, we propose GenoHoption, a new computational framework for single-cell sequencing data that effortlessly combines the strengths of these foundation models with explicit relationships in gene networks. We also introduce a constraint that lightens the model by focusing on learning the predefined graph structure while ensuring further hops are deducted to expand the receptive field. Empirical studies show that our model improves by an average of 1.27% on cell-type annotation and 3.86% on perturbation prediction. Furthermore, our method significantly decreases computational overhead. Overall, GenoHoption can function as an efficient and expressive bridge, connecting existing single-cell foundation models to gene network graphs. 1

关键词： Bridges Sequential analysis Foundation models Biological system modeling Message passing Computational modeling Perturbation methods Predictive models Genetics Periodic structures

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Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines 24

Development of a UAV-based System for Technical Diagnostics ...

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24th International Conference on Computational Problems of electrical engineering, CPEE 2023

作者： Kozlovskyi, Oleksandr Trushakov, Dmitro Rendzinyak, Serhiy Korud, Vasyl Central Ukrainian National Technical University Department of Electrical Systems and Energy Management Kropyvnytskyi Ukraine Central Ukrainian National Technical University Department of Automation and Control in Technical Systems Kropyvnytskyi Ukraine Ivan Franko National University of Lviv Faculty of Electronics and Computer Technologies Lviv Ukraine Lviv Polytechnic National University Institute of Power Engineering and Control System Lviv Ukraine

ISBN: (纸本)9798350330342

The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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IEEE Transactions on Instrumentation and Measurement 2024年 1-1页

作者： Wu, Jin Wang, Chaoqun Li, Chong Jiang, Yi Zhang, Chengxi Huang, Yulong Qi, Yuhua Xue, Bohuan Jiao, Jianhao Fan, Rui Zhang, Wei Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Control Science and Engineering Shandong University Jinan China Department of Automation and Measurement Ocean University of China Qingdao China Department of Electrical Engineering City University of Hong Kong Hong Kong China School of Internet of Things Jiangnan University Wuxi China Department of Automation Harbin Engineering University Harbin China School of Systems Science and Engineering Sun Yat-Sen University China College of Electronics and Information Engineering Tongji University Shanghai China

Similarity transformation problems are important in robotic instrumentation and computer vision based measurements since in many cases the information of visually observed scene scale is unknown and must be restored for accurate 3-dimensional reconstruction. In existing solvers, the scale is often considered as a scalar, i.e., isotropic, which may be invalid for anisotropic-scale setups. This paper exploits some mathematical coincidences that will lead to efficient solution to these problems. Possible further applications also include hand-eye calibration and structure-from-motion. We revisit pose estimation problems within the framework of similarity transformation, the one that considers scale-stretching, rotation and translation simultaneously. Two major problems are taken into account, i.e., the scale-stretching point-cloud registration and perspective-n-points (PnP). It has been found out that these two problems are quite similar. Moreover, we solve the anisotropic-scale registration problem that is important and is a remaining unsolved one in previous literatures. To compute the globally optimal solution of these non-convex problems, algebraic solution is obtained to compute all local minima using computationally efficient methods. The designed algorithm is deployed for robotic-arm pose estimation. We also extend the algorithm for solving the problem of robust magnetometer calibration. Visual pose experiments verify the superiority of the proposed method compared with representatives, including P3P, Lambda-Twist P3P and EPnP, which can be reproduced by repository in https://***/zarathustr/APnP. IEEE

关键词： Calibration

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A distributed monitoring method for non-stationary processes with application to float glass production

A distributed monitoring method for non-stationary processes...

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2022 Chinese automation Congress, CAC 2022

作者： Zheng, Jie Chen, Jianhua Ma, Bin Yang, Hui Peng, Kaixiang University of Science and Technology Beijing School of Advanced Enginnering Beijing China University of Science and Technology Beijing School of Automation and Electrical Engineering Beijing China Hebei Panel Glass Co. Ltd Process Quality Department Langfang China

ISBN: (纸本)9781665465335

process monitoring is a vital part of ensuring the normal and stable operation of modern industrial systems. The distributed method considers the local adjacency between sub-processes and the information interaction between sequences, which is a more effective process monitoring strategy for industrial systems containing multiple sub-processes. This paper proposes a new one-way transfer distributed process monitoring method based on the idea of dynamic-static fusion for non-stationary processes. Firstly, the static and dynamic information in the local sub-processes are extracted by PLS-PCA and QSFA-SFA methods respectively, and the performance of the local monitoring model is further improved by using dynamic-static fusion. Then, it is assumed that the information between the sub-processes is transmitted sequentially when considering the information interaction, which is also consistent with the current situation of most large-scale process industries in assembly-line production. Local monitoring statistics and control limits are designed, and global monitoring is achieved by Bayesian fusion. Finally, actual data from a float glass production line from a company verifies the effectiveness of this framework, which is better than the traditional single monitoring method. © 2022 IEEE.

关键词： process monitoring

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A Transfer Gated Recurrent Unit Model for Battery Health Monitoring Under Cross-Domain Conditions

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Tian, Jilun Xie, Jiale Zhang, Jiusi Huang, Congsheng Jiang, Yuchen Luo, Hao Chow, Mo-Yuen Yin, Shen Harbin Institute of Technology School of Astronautics Department of Control Science and Engineering Harbin150001 China North China Electric Power University Department of Automation Baoding071003 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Norwegian University of Science and Technology Faculty of Engineering Department of Mechanical and Industrial Engineering Trondheim7034 Norway

Battery health monitoring is crucial for ensuring maintenance reliability and safety, with broad applications in various industrial systems. Data-driven state-of-health (SOH) estimation methods can perform excellently using massive historical data without prior physical knowledge. In the battery aging process, this article extracts the essential health indicators to construct the model and adopts a suitable data preprocessing method to reduce the influence of noise. There is still a limitation for data-driven methods regarding data quality, and the domain shift caused by different operating conditions will damage estimation performance. To tackle the issue, this article proposes a transfer feature transformation (TFT) based on mean maximum discrepancy (MMD) to get a new feature space to get domain-invariant features with sufficient information. We propose a multilayer gated recurrent unit (GRU) neural network with fully connection (FC) layers to uncover hidden relationships in degraded data. Fusing TFT and GRU-FCs methods can realize an end-to-end SOH estimation under cross-domain conditions. We apply real-world public Center of Advanced Life Cycle engineering (CALCE) and NASA battery datasets and lab testing-based accelerated aging data to validate the performance of algorithms. By comparison, our proposed TFT-GRU-FCs method can get the best performance of all algorithms, and we have also given sufficient results as support. © 1963-2012 IEEE.

关键词： Electronic health record

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Exploring Bess Services for Transformer Energization on Offshore Oil and Gas Platforms

Exploring Bess Services for Transformer Energization on Offs...

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IEEE Petroleum and Chemical Industry Conference - Brasil (PCIC Brasil)

作者： Joseph K. Banda Lucas S. Araujo Danilo I. Brandao Fernando P. Marafão Elisabetta Tedeschi Department of Electric Power Engineering Norwegian University of Science and Technology (NTNU) Trondheim Norway Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais (UFMG) Belo Horizonte Brazil Department of Control and Automation Engineering Universidade Estadual Paulista (Unesp) Sorocaba Brazil Department of Industrial Engineering University of Trento Trento Italy

ISBN: (数字)9798350368154

ISBN: (纸本)9798350368161

The electrification of offshore oil and gas platforms (OOGPs), using offshore wind turbines, is now a reality, aimed at minimizing carbon emissions. In this scenario, the utilization of battery energy storage systems (BESS) improves both efficiency and power quality. As this integration comes with a high CAPEX, industries demand exploring BESS for multiple ancillary services on OOGPs. Thus, this paper proposes an alternative approach to energizing a power transformer (PT) using the BESS power conversion system (PCS) on the platform, aiming to minimize inrush currents. This avoids the necessity for additional bulky devices, converters, or dc voltage sources specifically designated for this purpose. The strategy consists of manipulating residual core flux using BESS PCS followed by a controlled switching, which reduces inrush currents during PT energization. The results show effective reduction of the inrush current from 2.31 pu to 0.16 pu for the presented case study.

关键词： Offshore installations Battery energy storage system Oils Voltage Switches Oil insulation Transformer cores

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