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

作者： Wei, Haoyu Pan, Lulu Shao, Haibin Li, Dewei Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

ISBN: (纸本)9798350303636

This paper explores distributed neighbor selection in matrix-weighted networks, where a matrix-valued weight captures the interdependencies among agents' states. We demonstrate the feasibility of preserving and, in certain cases, improving the convergence rate of matrix-weighted networks by having agents exclusively engage with a subset of their neighbors. Leveraging the inherent monotonicity of Laplacian matrix eigenvectors, we introduce a novel neighbor selection criterion that reduces network connections while enhancing convergence rates. Existing neighbor selection strategies often require acquiring information from all nodes before making decisions. In order to propose a distributed neighbor selection strategy for matrix-weighted networks, we establish a numerical relationship between Laplacian eigenvectors and a locally measurable metric. In essence, this paper extends prior findings from scalar-weighted networks to matrix-weighted networks. © 2023 IEEE.

关键词： convergence rate Distributed neighbor selection Laplacian matrix matrix-weighted networks

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A Power Grid Accident Early Warning Method Considering Multi-factor Coupling 17th

A Power Grid Accident Early Warning Method Considering Multi...

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17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Hu, Liangping Cong, Wei Xu, Anxin Wei, Zhen Han, Aoyang An, Shuhuai Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan Shandong China Rizhao Power Supply Company Shandong Electric Power Company State Grid Shandong Rizhao China Qingdao Power Supply Company Shandong Electric Power Company State Grid Shandong Qingdao China

ISBN: (纸本)9789819903566

The power grid is an important infrastructure for the development of the national economy and society. It is of great significance to carry out research on the early warning method of power grid accidents to ensure the safe and stable operation of the power grid. In this paper, a power grid accident early warning method considering multi-factor coupling is proposed, based on conditional deep convolutional generative adversarial networks to generate minority class samples to achieve dataset balance. The depth features of the two-dimensional input samples were extracted by using a deep convolutional autoencoder network for the three types of disaster factors: meteorology, equipment and geographical environment. A deep self-encoding network is constructed, and the deep feature splicing of three types of disaster-causing factors is used as input, and a softmax classifier is added to the output layer of the network to construct a multi-factor coupled power grid accident early warning model to realize the prediction and early warning of power grid accidents. Numerical simulations verify the effectiveness and accuracy of the method proposed in this paper. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Numerical methods

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DOFF-RLS-Based Equivalent Inertia Estimation for Power system with PV 4

DOFF-RLS-Based Equivalent Inertia Estimation for Power Syste...

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4th IEEE International Conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Ma, Huan Yang, Dong Qin, Hao Cao, Yongji Gao, Zhimin Zhang, Bing Cheng, Dingyi Zhang, Zhixuan State Grid Shandong Electric Power Research Institute State Grid Shandong Electric Power Company Jinan China Key Laboratory of Power System Intelligent Dispatch and Control The Ministry of Education Shandong University Jinan China Shandong Power Dispatch & Control Center State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

With the use of photovoltaic (PV) generation, a large number of synchronous generation units have been replaced, resulting in obvious decline in the equivalent inertia of power system. Facing a lack of inertia, virtual inertia control techniques are applied to PV, but there is a lack of methods to estimate the equivalent inertia of PV in real time, making it difficult to quantitatively estimate the effect of control method with virtual inertia. Therefore, this paper adopts the controlled autoregressive (CAR) identification model and the recursive least square algorithm of dynamic optimal forgetting factor (DOFF-RLS) to estimate the PV equivalent inertia, in order to address the time varying characteristics of the PV equivalent virtual inertia. The proposed identification model and solution algorithm have superior tracking capability and good convergence. All that is required is to obtain the disturbance data of frequency and active power from the point of common coupling from the phasor measurement unit (PMU). Finally, the accuracy and suitability of the identification model and method are verified by simulation. © 2022 IEEE.

关键词： Virtual addresses

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Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

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China Communications 2024年第5期21卷 297-313页

作者： Ma Shuai Yang Lei Ding Wanying Li Hang Zhang Zhongdan Xu Jing Li Zongyan Xu Gang Li Shiyin Department of Strategic and Advanced Interdisciplinary Research Peng Cheng LaboratoryShenzhen 518055China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Data-driven Intelligent Information System Laboratory Shenzhen Research Institute of Big DataShenzhen 518172China Ocean College Zhejiang UniversityZhoushan 316021China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication *** other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental *** on such a platform,we first construct a real signal dataset with ten modulation ***,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature *** also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated ***,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other *** also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

关键词： AdaBoost DBN machine learning signal demodulation

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intelligent Diagnosis of Planetary Gearboxes based on DAE-CNN 14

Intelligent Diagnosis of Planetary Gearboxes based on DAE-CN...

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14th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Kang, Tianbo Zhang, Mian Xie, Ruitong Chen, Jiwei Xiang, Hongbiao Wang, Yuhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin300384 China

ISBN: (纸本)9798350301359

Planetary gearboxes (PGs) are the core transmission components of complex rotating machinery. The diverse forms of internal gear faults often complicate diagnosis and maintenance work. To improve the fault diagnosis accuracy of PGs, this paper proposes a method for diagnosing PG faults based on deep autoencoders (DAE) and convolutional neural networks (CNN). The method fully utilizes the deep learning capability of DAE and combines it with the precise recognition ability of CNN for fault features. Through precise learning in the encoding layer, it achieves deep dimensionality reduction of fault features and further learns these features after dimensionality reduction by CNN. Compared to traditional CNN, the method reduces the computation parameters and resource consumption, resulting in higher precision intelligent fault diagnosis. Experimental results demonstrate that DAE-CNN exhibits stronger fault diagnosis ability than traditional networks. © 2023 IEEE.

关键词： component DAE-CNN deep learning fault diagnosis planetary gearboxes

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Towards Non-Virtual Inertia control of Renewable Energy for Frequency Regulation: Modeling, Analysis and New control Scheme

SSRN

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SSRN 2024年

作者： Gao, Haishu Zhang, Feng Ding, Lei Zhang, Gang Salimu, Athuman State Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan250061 China Yantai Research Institute Harbin Engineering University Yantai China

Currently, when renewable generation participates in frequency regulation, the traditional control method is to emulate synchronous generators through virtual inertia control. However, virtual inertia has a time delay, so essentially it is a kind of fast power response. Meanwhile, virtual inertia control is likely to be affected by frequency fluctuation, since it responds to the derivative of frequency. Hence, it’s worth exploring non-virtual inertia control for renewable energy when participating in frequency regulation. For this reason, a novel non-virtual inertia control scheme for renewable energy frequency regulation is proposed in this research. Firstly, the extended model of system frequency regulation (SFR), which contains virtual inertia with time delay, is built and analytically solved by order decrement on basis of Routh approximation method. Afterwards, according to analytical solution, it shows time delay really has an effect on the frequency response of renewable energy, and it can also be analytically proved that non-virtual inertia control, e.g., sole droop control, was capable to replace virtual inertia under the same frequency deviation, but more energy for frequency regulation may be needed. Furthermore, a novel two-segment droop control is presented, and to analytically prove its ability to replace virtual inertia, the impulse function balancing principle and the integration by parts algorithm were adopted to address the initial conditions of the differential equation. Based on the analytical expression, it can be analytically proved that under the same energy of frequency regulation, a lower frequency deviation can be obtained. Accordingly, a parameter setting method for two-segment droop control was proposed. Finally, the effectiveness of the proposed method is verified by using a two-area system frequency response model, and the results reveal that it can be used to replace virtual inertia and has better performance. © 2024, The Authors. All r

关键词： Time delay

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Research on Safety Integrity Level Assessment for Stage Machinery of Temporary Performance Site

Research on Safety Integrity Level Assessment for Stage Mach...

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2023 International Conference on Culture-Oriented Science and Technology, CoST 2023

作者： Hu, Yubin Su, Zhibin Wang, Zixiao Wang, Huiqin School of Information and Communication Engineering Communication University of China China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China

ISBN: (纸本)9798350357998

The safety assessment of stage performing arts equipment for the temporary site is an urgent task to be solved. In this paper, the lifting equipment is chosen for risk analysis, safety circuit identification and safety integrity level (SIL) calculation. The Hazard and Operability Study(HAZOP) and Layer Of Protection Analysis(LOPA)-based method is studied to get the expected SIL level of the related safety loops. In addition, the fault tree and Markov model methods are used to verify the actual SIL level under the existing loop structure respectively. This study provides the theory and data basis for the development of safety requirements and evaluation standards for the temporary theater of stage machinery, which has certain theoretical significance and application value. © 2023 IEEE.

关键词： Risk analysis

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Research on Risk Analysis for Lighting and Sound Equipment of Temporarily Constructed Stage

Research on Risk Analysis for Lighting and Sound Equipment o...

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2023 International Conference on Culture-Oriented Science and Technology, CoST 2023

作者： Zhang, Xueying Su, Zhibin Wang, Huiqin Jiang, Yujian School of Information and Communication Engineering Communication University of China China Ministry of Culture and Tourism Key Laboratory of Acoustic Visual Technology and Intelligent Control System Beijing China

ISBN: (纸本)9798350357998

With the increasing demand for stage performance activities, the quality and safety of performance equipment, especially for the temporarily constructed stage, have become important topics that cannot be ignored. In order to enhance the safety of performance equipment and improve the service quality, this article mainly conducts risk analysis and safety assessment on the lighting and sound equipment for stage of temporary perform site without protective measures, and uses Analytic Hierarchy Process (AHP) with Fuzzy Comprehensive Evaluation (FCE) to conduct risk analysis and evaluation. The calculated risk level of stage lighting and sound equipment is given, and relevant safety measures are proposed to reduce the potential risks. © 2023 IEEE.

关键词： Analytic hierarchy process

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Power system Equivalent Inertia Estimation Method Using system Identification 5

Power System Equivalent Inertia Estimation Method Using Syst...

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5th IEEE International Conference on Electronics Technology, ICET 2022

作者： Ma, Huan Yang, Dong Qin, Hao Cao, Yongji Cheng, Dingyi Zhang, Bing Hao, Xudong Zhou, Ning State Grid Shandong Electric Power Research Institute State Grid Shandong Electric Power Company Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China Shandong Power Dispatch & Control Center State Grid Shandong Electric Power Company Jinan China

ISBN: (纸本)9781665485081

As the proportion of renewable energy sources increase, the inertia of the power system continues to decrease, leading to a serious impact on frequency security and stability. There is an urgent need for an online estimation of the equivalent inertia of power systems. Most of the existing inertia estimation methods are based on the rate of change of frequency under large disturbance scenarios. According to the measurement data under normal operation, this paper estimates the equivalent inertia using system identification. The inertia response of the power system is analysed and an expression for the equivalent inertia is derived. An improved numerical algorithm based on subspace state space system identification and a least squares estimation method is used to calculate the equivalent inertia of the system. The validity of the proposed method is verified in a WSCC 9-bus power system case, showing that the proposed method has a high identification accuracy and can be adapted to different forms of load fluctuations. © 2022 IEEE.

关键词： Numerical methods

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Design of an electronic device for detection of exhaled gas concentration 5

Design of an electronic device for detection of exhaled gas ...

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2024 5th International Conference on Electrical, Electronic Information and Communication Engineering, EEICE 2024

作者： Fan, Chuanxiu Liu, Xue Yu, Zhichao Du, Changsong Jia, Shengde Liu, Qing Yan, Pengbo Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China Tianjin Chest Hospital Tianjin300384 China

To enable preliminary diagnosis of various diseases in the human body, detecting the concentrations of targeted components in exhaled gases is an effective way without invasive diagnosis. An exhaled gas concentration detection device is proposed in this paper. Firstly, this device employs a high-accuracy analog front end (AFE) for transmitting the concentrations of targeted components to an electronic voltage signal. The core circuit of AFE is a high-precision and low-current constant current source. Secondly, a heating circuit with controllable temperature is also designed to provide an appropriate operating temperature for different types of gas sensor materials. Thirdly, the system applies a microcontroller to directly read multiple-channel gas concentrations and independently control multiple heating circuits. The performance of the device has been validated through simulations. © Published under licence by IOP Publishing Ltd.

关键词： Computer resource management

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