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作者： Wu, Xiao-long Xu, Yuan-wu Xue, Tao Shuai, Junchao Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Wuhan Industrial Economic Development Research Center Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China

As the solid oxide fuel cell (SOFC) system work environment is a high-temperature environment for a long time, it is difficult to obtain the SOFC stack internal state change directly. When the fault occurs, it is difficult to determine where the fault occurs. Moreover, the existing literature ignores the impact of faults, which creates many problems for SOFC system control. Therefore, a state observer-based fault detection method, which is used to detect the input flow sensor fault and the fuel input fault, is proposed. Their advantage is that they do not need data processing. To realize the fault detection, the observer is used to track the changes of SOFC stack chamber temperature. To obtain the observer estimation parameter, an approach from the actual stack structure parameters is employed to approximate the observer parameters. The results show the proposed fault detect method can judge fuel input fault type quickly and shield the disturbances signals from the sensor effectively. The proposed method also can be used to other operating points or air input fault. © 2018 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Fault detection

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Single-Parameter Optimization Method for Extracting Coupling Matrix from Lossy Filters

Single-Parameter Optimization Method for Extracting Coupling...

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Chinese control Conference

作者： Wei-Hua Cao Can Liu Yan Yuan Xiao-Long Zhuang Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper presents a novel single-parameter optimization method for extracting coupling matrix from either measured or electromagnetic simulated S-parameters of a narrow band coaxial-resonator filter with losses. Having had the polynomials of the S-parameters of a filter by the Cauchy method with removing phase shift, the rational polynomials can be obtained. Once the rational polynomials having been determined, a single-parameter optimization method is proposed to obtain ε and the coupling matrix with an assigned topology, which can be extracted using well established techniques. The measured Sparameters compared with the 5-parameters obtained from the coupling matrix, and the attenuation factor K is easily determined. The loss effects will be removed after obtaining the value of the attenuation factor K. The approach is useful and can be used in computer-aided tuning of microwave filters. Example is presented to illustrate the validity of the proposed method.

关键词： Scattering parameters Tuning Couplings Loss measurement Optimization methods Transmission line measurements Transmission line matrix methods

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Staff lines Detection and Removal for Camera-Based Music Scores

Staff lines Detection and Removal for Camera-Based Music Sco...

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Chinese control Conference (CCC)

作者： Zhe Xiao Xin Chen Fang Wang Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Musical staff lines detection and removal, the first step of most Optical Music Recognition (OMR) technology, aims to detect staff positions and segment score image by removing those staff lines. To deal with issues that the disappearance of thin staff lines in the captured score image, line repaired algorithm based on music rules is proposed in this paper. It first estimates two reference lengths, staff width and space between two adjacent lines. Then projection is used to obtain potential staves positions. At least the staves are finally determined based on line repaired algorithm, the missing lines repaired and the redundant lines deleted at the same time. The proposed technique is simple and effective, making full use of global information of the musical scores. Experimental results show that our method achieves impressive results on music score images captured from cameras.

关键词： Music Lenses Cameras Optical character recognition software Optical imaging Image segmentation Character recognition

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Peak and valley time-of-use price optimization strategy with distributed power supply 8

Peak and valley time-of-use price optimization strategy with...

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8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Applications, ISCIIA and ITCA 2018

作者： Hu, Bo Zhang, Yu Han, Xin-Yang Jiao, Yu-Qiao Ding, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China State Grid Energy Research Institute Co. LTD. Beijing102200 China

This paper proposes a peak-to-valley time-based electricity price optimization method based on NSGA-II with distributed power supply. First, the curve-fitting method is used to obtain the comprehensive electricity price response curve of users in the whole society. Secondly, based on the use of time-sharing electricity price, the peak-to-valley time-sharing optimization model is established. Then, based on the NSGA-II optimization method, the optimal model is solved, and the optimal electricity price is obtained at different time periods to change the peak-to-valley load and the valley load. Finally, the simulation results verify the effectiveness of the proposed method. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Genetic algorithms

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Adaboost-kNN for dynamic emotion recognition 8

Adaboost-kNN for dynamic emotion recognition

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作者： Li, Min Su, Wanjuan Chen, Luefeng Wu, Min Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Tokyo Institute of Technology Yokohama226-8502 Japan

— K-nearest Neighbor based adaptive boosting (AdaBoost-KNN) is proposed for emotion understanding in human-robot interaction (HRI), where the real-time dynamic emotion is recognized according to facial expression. It can make robots capable of understanding human emotions and make HRI run smoothly. The Candide-3 model was adopted to extract the two-dimensional coordinate values of the key points of facial emotion, as the basis for emotion classification. The emotion classification is based on AdaBoost-KNN, which sets up seven basic KNN classifier. Then it iterates seven times to update the weight of samples, and combines the weak classifier with coefficient to establish the final classifier. Finally, the performance of the proposal is verified by using K-fold cross validation. Results show that the proposal achieves higher accuracy than that of a single KNN. © ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and control Application.

关键词： Adaptive boosting

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Fast Satellite Selection Algorithm Based on Satellite Elevation Angle and Satelte Contribution for Geometry Dilution of Precision in GPS/BEIDOU

Fast Satellite Selection Algorithm Based on Satellite Elevat...

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第37届中国控制会议

作者： Guangjun Wang Jianjin Jiang School of Automation China University of Geosciences China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex System

In order to solve the contradiction between positional accuracy and real-time in satellite navigation system, a fast satellite selection algorithm based on satellite elevation angle and satellite contribution for Geometry Dilution of Precision（GDOP） in GPS/BEIDOU is proposed, which dependents on the high dynamic GPS/BEIDOU receiver developed by our laboratory. Through compared with the existing algorithm by real data simulation, our proposed algorithm has the smaller positional error in the X, Y, Z direction and lower complexity. As a result, we can prove that the proposed method has the feasibility and better real-time performance.

关键词： GPS/BEIDOU elevation angle satellite contribution value satellite selection

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Residential virtual power plant with photovoltaic output forecasting and demand response

Residential virtual power plant with photovoltaic output for...

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作者： Cui, Shichang Wang, Yan-Wu Lin, Xiangning Xiao, Jiang-Wen School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China Hubei Provincial Collaborative Innovation Center for New Energy Microgrid China Three Gorges University Yichang China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China

Decreasing conventional power supply is promoting the development of the distributed renewable energy sources, such as solar power and wind power. Recently rooftop photovoltaic has been widely applied, and accordingly efficient energy management is getting increasingly important for fully use of renewable energy and the peak shaving of the main grid. This paper investigates the residential energy management as a small-scale virtual power plant (VPP) connected to the main grid includes distributed energy resources, energy storages and residential loads. The self-organizing map (SOM) and the radical basis function (RBF) networks are adopted to classify the weather types and predict hourly photovoltaic output precisely. In a time-of-use electricity market, price-based demand response is applied to adjust the demand. The residential VPP has two goals: maximum profit by selling surplus power to grid and minimum power purchased from grid. The two goals are integrated as an optimization object by introducing a weight parameter. The algorithm combining receding horizon optimization and linear programming is proposed to solve the optimization problem in residential VPP. Numerical simulation tests can help to find the most suitable value of the weight parameter. Different scenarios are simulated and discussed to demonstrate the performance of the VPP and the proposed algorithm. © 2019 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Energy management

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Defining digital quadruplets in the cyber-physical-social space for parallel driving

arXiv

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arXiv 2020年

作者： Liu, Teng Xing, Yang Chen, Long Cao, Dongpu Wang, Fei-Yue Vehicle Intelligence Pioneers Inc Shandong Qingdao266109 China Qingdao Academy of Intelligent Industries QingdaoShandong266109 China Department of Mechanical and Mechatronics Engineering University of Waterloo N2L 3G1 Canada State Key Laboratory of Management and Control for Complex System Institute of Automation Beijing China

Parallel driving is a novel framework to synthesize the vehicle intelligence and transport automation. This article aims to define the digital quadruplets in parallel driving. In the cyber-physical-social systems (CPSS), based on the ACP method, the names of the digital quadruplets are first given, which are descriptive, predictive, prescriptive and real vehicles. The objectives of the three virtual digital vehicles are interacting, guiding, simulating and improving with the real vehicles. Then, the three virtual components of the digital quadruplets are introduced in detail and their applications are also illustrated. Finally, the real vehicles in parallel driving system and the research process of the digital quadruplets are depicted. The presented digital quadruplets in parallel driving are expected to make the future connected automated driving safety, efficiently and synergistically. Copyright © 2020, The Authors. All rights reserved.

关键词： Vehicles

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A resonant cavity based on birdcage coil for overhauser geomagnetic sensor

A resonant cavity based on birdcage coil for overhauser geom...

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2018 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2018

作者： Bai, Bingjie Dong, Haobin Ge, Jian Liu, Huan Zhang, Cheng Wang, Luo Institute of Geophysics and Geomatics China University of Geosciences Hubei Wuhan China School of Automation China University of Geosciences Hubei Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan China Science and Technology on Near-Surface Detection Laboratory Jiangsu Wuxi China

ISBN: (纸本)9781538622223

The resonant cavity is an important component of Overhauser magnetometer sensor. Its function is to make the working substance generate dynamic nuclear polarization effect in the sensor. An alternative design of resonant cavity based on the birdcage coil structure was proposed to make the resonant frequency in accordance with the polarization frequency of the working substance. The structure and equivalent circuit of resonant cavity were analyzed. The model of resonant cavity was established and S-parameter is calculated to verify the frequency consistency of the resonant cavity and working substance. In addition, output signal experiment and simultaneous comparison testing of sensor prototype were conducted. Overall, this design has the advantages of high performance and strong anti-interference. © 2018 IEEE.

关键词： Equivalent circuits

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Hyperspectral Remote Sensing Image Classification Based on Convolutional Neural Network

Hyperspectral Remote Sensing Image Classification Based on C...

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Chinese control Conference

作者： Xiangyang Dai Wei Xue Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan

Remote sensing hyperspectral imaging can obtain rich spectral information of terrestrial objects, which allows the indistinguishable matter in the traditional wideband remote sensing to be distinguished in hyperspectral remote sensing. Hyperspectral image has the characteristics of "combining image with spectrum". Making full use of spectral information and spatial information in hyperspectral image is the premise of obtaining accurate classification results. At present, most of hyperspectral data feature extraction algorithms mainly utilize local spatial information in the same channel and spectral information in the same spatial location of different channels. However, these methods require a large amount of prior knowledge, it is difficult to fully grasp the hyperspectral data of all spatial and spectral information, and the model generalization ability is poor. With the development of deep learning, convolutional neural network shows superior performance in all kinds of visual tasks, especially in the two-dimensional image classification, and could get a high classification accuracy. In this paper, an image classification method based on three-dimensional convolution neural network is proposed based on the structural properties of hyperspectral data. In the proposed method, first the stereo image blocks of hyperspectral data are intercepted, then multi-layer convolution and pooling operation of extracted blocks by convolutional neural network are implemented to obtain the essential information of hyperspectral data, finally the classification of hyperspectral data is completed. The experimental results show the proposed method could provide better feature expression and classification accuracy for hyperspectral image.

关键词： Hyperspectral imaging Image classification Convolution Feature extraction Support vector machines

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