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A hybrid piecewise FDD strategy for refrigeration charge fault of airborne vapor-compression cycle system

INTERNATIONAL JOURNAL OF REFRIGERATION 2022年 135卷 164-173页

作者： Sun, Chengbin Wang, Hexu Jiang, Yanlong Gao, Zanjun Wang, Ju [a]Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Aeronautics and Astronautics 29 Yudao St. Nanjing 210016 China [b]Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing 211106 China

Many researchers have carried out study on refrigerant charge fault for variable refrigerant flow (VRF) airconditioning system, while few pay attention to refrigerant charge fault for vapor-compression refrigerant cycle system (VCS) of enhanced vapor injection (EVI) with a flash tank onboard. To develop a strategy for refrigerant charge fault of the above system, the optimization methods have been implemented to predict the refrigerant charge level (RCL) based on virtual refrigerant charge (VRC) models. Firstly, Pearson correlation coefficient analysis is employed to obtain the characteristic parameters. Secondly, a piecewise modified VRC model with the different characteristic parameters from VRC models is obtained for two cases of RCL < 75% and RCL > 75%. Meanwhile, combined with the principal component analysis (PCA) and the support vector machine (SVM) algorithm, a PCA-SVM model is developed to improve the prediction accuracy, and the average root mean squared error (RMSE) is only 7.8 compared to 14.9 of the modified VRC model when RCL > 75%, meanwhile, the correctly detected ratio is improved from 62.8% to 84.5%. Then, for solving the difficulty of fault detection and diagnosis (FDD) when RCL > 160%, the moving time window average (MA) algorithm is introduced and an online PCA-MA-SVM model is developed. Finally, a hybrid piecewise FDD strategy combined with three models for refrigeration charge fault in airborne VCS of EVI with a flash tank is obtained.

关键词： Vapor-compression refrigeration cycle system Enhanced vapor injection Refrigerant charge fault Support vector machine Moving time window average

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NUMERICAL SIMULATION AND EXPERIMENTAL RESEARCH ON TAYLOR COUETTE FLOW CHARACTERISTICS IN AIR GAP OF AVIATION MOTOR

NUMERICAL SIMULATION AND EXPERIMENTAL RESEARCH ON TAYLOR COU...

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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Ma, Hui Liang, Shuyue Zhan, Hongbo Qi, Lin Chen, Weijian Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration No.33 Shuige Road Nanjing China Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Areonautics and Astronautics No.29 Yudao Street Nanjing China

A test bench with PIV technology was built and visualization research on Taylor vortex between concentric rotating cylinders was carried out to explore the flow morphology within the annular gap by changing the rotational speed of the inner cylinder. The numerical method and accuracy were verified by experiments. The selected turbulence model was then applied for numerical simulation of the Taylor Couette flow in a simplified air gap model of an aviation motor with smooth inner and outer walls. The Taylor Couette flow characteristics in the air gap under varying rotational speed were studied, and simulation results were given for flow with axial flow and without axial flow. © The Institution of Engineering & Technology 2024.

关键词： Axial flow

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Passive Temperature Threshold Sensors Based on RFID and Shape Memory Polymer for Power system Monitoring 6

Passive Temperature Threshold Sensors Based on RFID and Shap...

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6th International Conference on Power and Energy Technology, ICPET 2024

作者： Guo, Xiaoyu Fan, Libo Han, Rongjie Huang, Jiabin Shi, Yuchao Lai, Yibo Sun, Min Power System Wide Area Measurement and Control of the Key Laboratory of Sichuan Province University of Electronic Science and Technology Chengdu China State Grid Zhejiang Electric Power Company Hangzhou China

ISBN: (纸本)9798350375855

The sensing technology of the power system promotes the deep integration of energy network and data information and helps to build a new type of power system with deep integration of digital and system. It can ensure the stable operation of the power grid. RFID sensors are widely used as passive wireless sensors. While they still face the disadvantage of missing data information when the reader is not actively interrogated. In this paper, a shape memory polymer material is introduced and its thermo-mechanical property of deformation recovery above and below the glass transition temperature is exploited to design a temperature threshold sensor. By measuring the backscatter power of the RFID tag, whether the target exceeds the threshold temperature could be determined. This method can record historical information in a non-electric form when the reader is not actively interrogated, facilitating quick problem solving or troubleshooting. In this paper, a prototype of the SMP material was fabricated using 3D printing technology. And several reader-tag temperature threshold detection experiments at different distances were conducted. The results show that the SMP material recovers its deformation near 60 °C in the reader antenna field range. And the backscatter power amplitude of the two tags is significantly flipped. This validates the feasibility of temperature threshold sensors. When electrical equipment malfunctions lead to high temperatures, temperature threshold sensors can detect the malfunction and solve the hidden problem. © 2024 IEEE.

关键词： Antennas

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Event-triggered-based self-organizing fuzzy neural network control for the municipal solid waste incineration process

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Science China(Technological Sciences) 2023年第4期66卷 1096-1109页

作者： HE HaiJun MENG Xi TANG Jian QIAO JunFei Faculty of Information Technology Beijing University of TechnologyBejing 100124China Beijing Laboratory of Smart Environmental Protection Beijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Bejing 100124China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Bejing 100124China Xi'an Institute of Electromechanical Information Technology Xi'an 710065China

Due to the large uncertainty in the municipal solid waste incineration(MSWI)process,the furnace temperature of the MSWI process is difficult to control and the controller is updated *** improve the accuracy and reduce the number of controller updates,a novel event-triggered control method based correntropy self-organizing TS fuzzy neural network(ETCSTSFNN)is ***,the neurons of the rule layer are grown or pruned adaptively based on activation intensity and control error to meet the dynamic change of the actual operating ***,the performance index is designed based on the correntropy of tracking errors,and the parameters of the controller are adjusted by gradient descent ***,a fixed threshold event-triggered condition is designed to determine whether the current controller is updated or *** stability of the control system is proved based on the Lyapunov stability ***,the furnace temperature control experiments are conducted based on the actual data of a municipal solid waste incineration plant in *** experimental results show that the proposed ET-CSTSFNN controller shows a better control performance,which can reduce the number of the controller update significantly while achieving accurate furnace temperature control compared with other traditional control methods.

关键词： municipal solid waste incineration furnace temperature fuzzy control event-triggered

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A Dynamic control Strategy for Enhancing the Energy Extracting Capability of Magnetic Field Energy Harvesters in Sensor Nodes of Power Equipment 14

A Dynamic Control Strategy for Enhancing the Energy Extracti...

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14th International Conference on Power and Energy systems, ICPES 2024

作者： Gao, Yuan Fan, Libo Huang, Jiabin Han, Rongjie Sun, Min University of Electronic Science and Technology of China Power system wide area measurement and control of the Key Laboratory of Sichuan Province Chengdu China The State Grid Zhejiang Electric Power Company Hangzhou China

ISBN: (纸本)9798350391329

With the widespread application of sensors nodes in power equipment, providing a stable energy supply for these sensors has become a significant challenge. Traditional batterypowered solutions are costly and difficult to install. The development of energy harvesting technology offers a new technical approach to address this challenge. This paper mainly investigates how to enhance the energy harvesting power of Magnetic Field Energy Harvesters (MEH) under conditions where the magnetic field around power equipment is limited. A dynamic control method is proposed to improve the energy harvesting power of MEH. The fundamental idea of dynamic control is to precisely control the MOSFETs in the rectifier, dynamically adjusting the switching times of the energy harvesting interval to be symmetric around the peak current of the primary side, thereby significantly enhancing harvesting efficiency. This method is particularly applicable when the magnetic core enters the soft saturation region, causing the energy harvesting interval to be less than T/2. Experimental results show that under constant voltage load, dynamic control effectively adjusts the energy harvesting interval, maximizing the current extracted during this interval, thereby effectively increasing energy harvesting power. Compared to passive rectification, active rectification under dynamic control increases the energy harvesting power by 76%, and the power factor of active rectification is 1.7 times that of passive rectification. The research findings provide important theoretical support and practical significance for the application of magnetic field energy harvesting technology in sensor nodes. © 2024 IEEE.

关键词： Sensor nodes

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Data-Driven Frequency Regulation Method for Multi-Terminal HVDC Grids 38

Data-Driven Frequency Regulation Method for Multi-Terminal H...

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Yong, Panxiao Jia, Yubin Guo, Jun Zhou, Jun Liu, Zhimin Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

High voltage direct current (HVDC) lines allow low-loss transmission over long distances. The multi-terminal HVDC network consists of multiple terminals connected by HVDC lines, and each area shares the frequency reserve. Through secondary frequency control, the frequency of AC and DC areas can be regulated back to the set point when the system frequency has deviated. In this paper, a data-driven model predictive control (MPC) strategy is proposed. The Kooman operator is used to obtain the high-dimensional linear model of a nonlinear system, and the Deep Learning method is used to approximate the infinite-dimensional Koopman operator. The nominal MPC is used for optimization and control, and the optimal problem is solved for the Koopman linearized system. The optimal control is applied to the original nonlinear system. Simulation results show the effectiveness of the proposed method. © 2023 IEEE.

关键词： data-driven Koopman operator model predictive control Multi-terminal HVDC

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Non-convex Optimization Based On Deep Koopman Operator 38

Non-convex Optimization Based On Deep Koopman Operator

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Guo, Jun Jia, Yubin Yong, Panxiao Zhou, Jun Liu, Zhimin Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

Non-convex optimization problems are prevalent in various fields, and finding the global optimal solution for such problems remains challenging. This paper proposes an optimization method based on deep Koopman operator, which leverages the power of deep neural networks to provide a data-driven architecture for the Koopman function. The Koopman operator is used to linearly represent non-convex problems, and the proposed method utilizes model predictive control to optimize the resulting linear systems. Simulation results show that this method can solve the non-convex optimization problem effectively, quickly and accurately, while obtaining the global optimal solution. © 2023 IEEE.

关键词： Koopman operator model predictive control Non-convex

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Fixed-Time Consensus-Based Nash Equilibrium Seeking

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 267-269页

作者： Mengwei Sun Jian Liu Lu Ren Changyin Sun the Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China the School of Artificial Intelligence and the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationAnhui UniversityHefei 230601China

Dear Editor,This letter examines the fixed-time stability of the Nash equilibrium(NE)in non-cooperative *** propose a consensus-based NE seeking algorithm for situations where players do not have perfect information and communicate via a topology *** proposed algorithm can achieve NE in a fixed time that does not depend on initial conditions and can be adjusted in advance.

关键词： Fixed seeking letter

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SSD object detection algorithm based on knowledge map

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International Journal of Wireless and Mobile Computing 2024年第2期27卷 152-160页

作者： Huang, Li Wang, Xiaofeng Lu, Jianhua Hu, Wei Zhang, Changrong College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Precision Manufacturing Research Institute Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China

With the pervasive integration of artificial intelligence into all aspects of human life, talent emerges as a primary resource. Upon analysing the current state of talent training in higher education institutions, issues such as dispersed knowledge points, overlapping content, a singular practice approach and ineffective evaluation have been identified. In response to these challenges, this paper proposes a multidisciplinary and comprehensive practical teaching methodology grounded in the knowledge graph framework. It delves into diverse paths for practical teaching and assessment, including aspects like teaching objectives, problem decomposition, resource integration, implementation methods and performance evaluation. The practical application of the SSD algorithm in researching service robot indoor object detection serves as an illustrative example. Employing the holistic practical teaching approach facilitated by the knowledge graph, this model guides students in acquiring object detection expertise, thereby enhancing their comprehensive development. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Object detection

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Modeling and validation of key components of thermal management systems

Modeling and validation of key components of thermal managem...

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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Zekun, Mei Shuai, Xu Fanxin, Meng Guangya, Zhu Dalin, Zhang Weijian, Chen Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Aeronautics and Astronautics Nanjing China 805th Research Institute of China Aerospace Science and Technology Corporation Shanghai China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration No.33 Shuige Road Nanjing China

ISBN: (数字)9781837242108

In this paper, two key components of thermal management system are modeled by the underlying logic operation of SIMULINK. Simulink-PS signal conversion module is used to connect the electric grid and the calculation part of the heat grid to build the fuel tank heat grid model. The temperature transient simulation model of phase-change heat exchanger was established by using the integral module in Simulink library. Experimental verification and literature data verification are provided for these two components. The results show that the error between simulation results and experimental data is between 0.1% and 3%, which proves the accuracy and feasibility of the system modeling in this paper. It lays a foundation for the simulation of the overall thermal management scheme. © The Institution of Engineering & Technology 2024.

关键词： Fuel tanks

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