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Chinese automation Congress (CAC)

作者： Pengju Xu Chao Gan Luzhao Wang Weihua Cao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China No.3 Exploration Institute of Geology and Mineral Resources of Shandong Province Yantai China

In this paper, a multi-feature extraction-based image identification method for rock debris in the drilling process is proposed, involving three main parts (trainable feature extractor, strong feature extraction, and classification). In trainable feature extractor, abstract features are obtained by extracting the full connection layer of Convolutional Neural Network (CNN). In strong feature extraction, the method uses Gray-Level Co-occurrence Matrix (GLCM) and Color Coherence Vector (CCV) to get the strong feature. In classification, the extracted abstract features and strong features are concatenated and fed into the Support Vector Machine (SVM). Comparison results with two well-known methods indicated the effectiveness of the proposed method.

关键词： Support vector machines Drilling measurement Image color analysis Neural networks Feature extraction Rocks

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No-Reference Image Quality Assessment using Meta-SGD

No-Reference Image Quality Assessment using Meta-SGD

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Chinese automation Congress (CAC)

作者： Qingqing Yan Bei Dong Xin Li Yiwen Xiang Dapeng Luo Longsheng Wei School of Automation China University of Geosciences Wuhan China Key Laboratory of Geological Survey and Evaluation of Ministry of Education Wuhan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Intelligent Technology co. Ltd of Chinese Construction Third Engineering Bureau Wuhan China School of Electronic Information and Mechanics China University of Geosciences Wuhan China

ISBN: (纸本)9781665426480

Deep learning-based no-reference image quality assessment (NR-IQA) algorithm requires massive training data and labels, but data scarcity usually exists in practical applications. Most of the previous metrics used pre-trained networks to solve this problem by fine-tuning on the target tasks. Unfortunately, the network trained on other tasks cannot be directly applied to IQA tasks and failed when encountering complex distortions. To reduce dependence on labeled data and improve generalization ability of unknown distortion types, a NR-IQA metric based on Meta-SGD is proposed, which can learn the quick adaptability of humans and obtain general meta-knowledge for distortion evaluation. Specifically, we collected a great many NR-IQA tasks with different distortion types to pre-train the model; then a meta-learning metric based on optimization, Meta-SGD, is proposed to acquire the meta-knowledge when evaluating images quality with various known distortions; finally, the obtained pre-trained meta-model can be directly applied to the new NR-IQA tasks only by fine-tuning a few images. Experiments on the TID2013 database demonstrate that the model after meta-learning obviously outperforms than some existing methods, and the average SRCC value for all types of distortion performance tests can reach 0.91.

关键词： measurement Image quality Adaptation models automation Databases Training data Distortion

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H∞ State Estimation for Time-Delayed Static Neural Networks Using an Improved Delay-Product-Type LKF

H∞ State Estimation for Time-Delayed Static Neural Networks...

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Chinese control Conference (CCC)

作者： Yong-He Lao Yu-Long Fan Liang-Tong Luo Chuan-Ke Zhang School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan P. R. China

This paper is concerned with $H_{\infty}$ performance state estimation of static neural networks with a time-varying delay. First, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second, an augmented Lyapunov-Krasovskii functional (LKF) containing delay-product-type non-integral terms and single integral terms is constructed by introducing negative definite terms. After that, a criterion with less conservatism is derived based on extended reciprocally convex matrix inequality. Finally, a numerical example is provided to reveal the effectiveness of the proposed approach.

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Design and Implementation of Gaussian Filter for Nonlinear System with Randomly Delayed measurements and Correlated Noises

Design and Implementation of Gaussian Filter for Nonlinear S...

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Chinese control Conference (CCC)

作者： Weijie Cui Xinmei Wang Qian Hu Fei Du School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

A new Gaussian approximate (GA) filter for nonlinear systems with one-step randomly delayed measurement and correlated noise is proposed in this paper. Firstly, a general framework of Gaussian filter is designed under Gaussian assumption on the conditional density. Then, the implementation of Gaussian filter is transformed into the approximation of the Gaussian weighted integral in the proposed frame. Secondly, a new cubature Kalman filtering(CKF)algorithm is developed on the basis of the spherical-radial cubature rule. The efficiency and superiority of the proposed method are illustrated in the numerical examples.

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Designation and development of hardware platform for intelligent ter-minal in 126kV Smart substation

Designation and development of hardware platform for intelli...

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International Conference on Advanced Power System automation and Protection (APAP)

作者： Tong Sun Bin Wang XinZhou Dong ShuJian Zhang MingCai Kang RunBin Cao School of Automation Nanjing University of Science and Technology Jiangsu 210094 China State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Haidian District Beijing 100084 China Electrical engineering and automation Hefei University of Technology Anhui 230009 China

According to the demand of 126kV intelligent switch with intelligent operative box, an intelligent terminal device by using cooperation control of embedded CPU (STM32F103ZET6 ARM) and Field Programmable Gates (Cyclone II EP2C8Q208C8 FPGA), which is up to the IEC61850 standard, is designed in this paper. Research program of the device is discussed. Starting from the modularization structure design, function of each module, circuit design and implementation method were introduced in detail. A hardware platform was established according to the design. Finally, the article confirmed the correctness of the hardware platform primarily through experimental method.

关键词： Optical fiber LAN Voltage measurement measurement units Optical fibers Switchgear Field programmable gate arrays Sun

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State Estimation of Finite-State Hidden Markov Models Subject to Stochastically Event-triggered measurements

State Estimation of Finite-State Hidden Markov Models Subjec...

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IEEE Annual Conference on Decision and control

作者： Wentao Chen Junzheng Wang Ling Shi Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781479978878

We consider the event-triggered state estimation of a finite-state hidden Markov model with a general stochastic event-triggering condition. Utilizing the change of probability measure approach and the event-triggered measurement information available to the estimator, analytical expressions for the conditional probability distributions of the states are obtained, based on which the minimum mean square error event-based state estimates are further calculated. We show that the results also cover the case of packet dropout, under a special parameterization of the event-triggering conditions. With the results on state estimation, a closed-form expression of the average sensor-to-estimator communication rate is also presented. The effectiveness of the proposed results is illustrated by a numerical example and comparative simulations.

关键词： State estimation Hidden Markov models Event trigger Probability distribution Mean square error numerical example

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HeROS: A simulation platform for heterogeneous robotic swarms

HeROS: A simulation platform for heterogeneous robotic swarm...

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第三十八届中国控制会议

作者： Shuai Li Yuanfang Wan Pengzhou He Chen Wang Jinan Sun Yanling Zhang Xuyang Li Guangming Xie The State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University School of Automation and Electrical Engineering University of Science and Technology Beijing National Engineering Research Center for Software Engineering Peking University Xi'an Bibang Intelligent Technology Co. Ltd.

This paper presents HeROS, which is a novel simulation platform for heterogeneous robotic swarms. Compared with some existing simulation platforms, our HeROS(Heterogeneous Robotic Swarms Simulation) platform is more efficient due to its special designed communication methods and framework. Besides, it's convenient for use since we provide many kinds of control functions with free API's. It also supports many external libraries, which can be used to develop different simulation tasks. Using our developed platform, a mission of target search and tracking is realized as a case study, where a UAV-UGV heterogeneous system consisting of a UAV and two UGVs is required to search for a ground target and then move close to *** implementation of the task successfully shows the effectiveness and performance of the HeROS platform.

关键词： Heterogeneous robotic swarms simulation platform UAV UGV cooperation

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Improving the precision of weak-value-amplification with two cascaded Michelson interferometers based on Vernier-effect

arXiv

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arXiv 2021年

作者： Huang, Jing-Hui He, Fei-Fan Duan, Xue-Ying Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 Wuhan430074 China School of Automation China University of Geosciences Lumo Road 388 Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

A modified-weak-value-amplification(MWVA) technique of measuring the mirror's velocity based on the Vernier-effect has been proposed. We have demonstrated with sensitivity-enhanced and the higher signal-to-noise ratio(SNR) by using two cascaded Michelson interferometers. These two interferometers are composed of similar optical structures. One interferometer with a fixed mirror acts as a fixed part of the Vernier-scale, while the other with a moving mirror acts as a sliding part of the Vernier-scale for velocity sensing. The envelope of the cascaded interferometers shifts much more than a single one with a certain enhancement factor, which is related to the free space range difference between these two interferometers. In addition, we calculate the SNR based on the Fisher information with both the MWVA technique and the traditional-weak-value-amplification(TMVA) technique. The results show that the SNR with our MWVA technique is larger than the the SNR with the TWVA technique within the range of our time measurement window. Our numerical analysis proved that our MWVA technique is more efficient than the TWVA technique. And by using the principles of the Vernier-effect, it is applicative and convenient to ulteriorly improving the sensitivity and SNR in measuring other quantities with the MWVA technique. © 2021, CC BY.

关键词： Signal to noise ratio

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A historical review and bibliometric analysis of research on weak measurement research over the past decades based on biblioshiny

arXiv

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arXiv 2021年

作者： Huang, Jing-Hui Duan, Xue-Ying He, Fei-Fan Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Lumo Road 388 Wuhan430074 China School of Automation China University of Geosciences Lumo Road 388 Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

Weak measurement has enabled fundamental studies in both experiment and theory of quantum measurement. Numerous researches have indicated that weak measurements have a wide range of application and scientific research value. In our work, we used bibliometric methods to evaluate the global scientific output of research on Weak measurement and explore the current status and trends in this field from 2000 to 2020. The R bibliometric package was used for quantitative and qualitative analyses of publication outputs and author contributions. In total, 636 related articles and reviews were included in the final analysis. The main results were as follows: The number of publications has increased substantially with time. Physical Review A was the most active journal. The country and institution contributing the most to this field were The United States and University Rochester respectively. The analysis of the conceptual structure of keywords indicated that weak measurements were involved a variety of metrology, quantum communication, and nonclassical features of quantum mechanics. Our bibliometric analysis shows that weak measurement research continues to be a hot-spot. The focus has evolved to study quantum information and amplify weak signals. © 2021, CC BY.

关键词： Quantum optics

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A Novel All-phase Fast Fourier Transform-based Parameters Identification of High Frequency Oscillations

A Novel All-phase Fast Fourier Transform-based Parameters Id...

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Annual Meeting Industrial and Commercial Power systems Technical Conference

作者： Feiyu Sun Dongsheng Cai Zhenyuan Zhang Qi Huang College of Nuclear Technology and Automation Engineering Chengdu University of Technology China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang P.R. China

ISBN: (数字)9798350345308

ISBN: (纸本)9798350345315

Wind and solar energy inverter-based resources (IBRs) has been employed extensively with the aim of carbon neutrality. Power systems also make extensive use of power electronic converters, leading to interactions between IBRs and with the grid, causing high frequency oscillation (HFO) problems. It damages equipment and jeopardizes the security of the system. To identify HFO components above 100 Hz, this research use Phasor measurement Unit (PMU) instantaneous value data to determine the HFO associated characteristics. To reduce the influence of spectral leakage and the fence effect, as well as to improve the identification accuracy of the related parameters, this paper adopts the RV self-convolutional window based Discrete Fourier Transform (DFT) and the Hanning double-window based all-phase Fast Fourier Transform (apFFT) hybrid algorithm to identify the HFO modal parameters. We take into account the identification accuracy in complex cases, such as non-nominal frequencies, with noise effects and multiple HFO modes. The simulation results show that the proposed method has high identification bandwidth, accuracy and strong flexibility.

关键词： Accuracy Wind energy Simulation Discrete Fourier transforms Noise Bandwidth Hafnium oxide

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