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International Conference on Computing, Power and Communication Technologies (GUCON)

作者： Bhumika Sahu Abhai Tiwari J L Raheja Santosh Kumar Guru Ghasidas Central University Bilaspur Chhattisgarh India AIGROEDGE Technologies Pvt. Ltd. New Delhi India Automation & Control System Group CSIR- Central Electronics Engineering Research Institute Raj. India

ISBN: (数字)9781728150703

ISBN: (纸本)9781728150710

Food wastage dew to spoilage is one of the key global problems, the quantity of food loses and spoilage per year is 40-50% for root crops, fruits, and vegetables. This paper proposes an edge IoT & machine learning based approach for food quality monitoring. The need for this type of system is to correctly classify the vegetables and fruits in three categories fresh, semi-fresh & spoiled, further to alert about environmental conditions, either it's favorable or not using the expert algorithm developed under particular standard environmental data. The proposed system employed with Raspberry Pi as the main processing unit, temperature & humidity sensors along with three VoC gas sensors. To classify the vegetable and fruit, the sensed data (Gas Sensors MQ2, MQ3 & MQ9 along with humidity & temperature sensor) were collected over a week & machine learning models Logistic Regression, Linear SVC, rbf SVM Classifier, Random Forest with the accuracy of 99.1%, 99.9%, 99.96% & 99.96% respectively have been used to classify the data. Further, the classified and processed result was uploaded on the firebase cloud to make it possible to be monitored from anywhere in the world using a particular developed android application. The uniqueness of the system is, it uses edge IoT and its software is programmable so that it can be used to preserve any type of food items by just filling up some credentials in the settings section of GUI.

关键词： Temperature sensors Support vector machines Static VAr compensators Sensors Monitoring Random forests Gas detectors

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Time-delay assisted mechanism and adaptive LSTM hybrid train braking model of heavy haul trains

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control Engineering Practice 2025年 163卷

作者： Qiang Liu Kexuan Xu Yating Fu Jiang Liu Ling Liu State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University) Shenyang 110819 China Key Laboratory of Advanced Control and Optimization of Jiangxi Province Nanchang 330013 China School of Electrical and Automation Engineering East China Jiaotong University Nanchang 330013 China Frontiers Science Center for Smart High-speed Railway System Beijing 100044 China School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 China Beijing National Railway Research & Design Institute of Signal Communication Group Company Beijing 100070 China

The train braking model (TBM) that describes the dynamic relations of operation speed, mileage, and control force is essential for achieving stable operation and precise stopping of heavy haul trains (HHTs). However, it is difficult to establish the TBM of HHTs due to complex characteristics: (i) the long body and air braking process of the HHTs may lead to unexpected time-delays of control force; and (ii) there are significant unmodeled dynamics caused by rough tracks and external poor environment. Traditional TBM does not take into account the unmodeled dynamics and time-delays caused by air transmission during braking. To address these issues, this study proposes a data mechanism hybrid modeling strategy, which incorporates a braking time-delay assisted mechanism model and an adaptive long and short-term memory (LSTM) model. A new Bayesian optimization based time-delay estimation method is first proposed to determine unknown time-delays of each carriage and the estimated time-delays are incorporated to generate the multi-point-mass kinetic mechanism model. Moreover, the error of the mechanism-driven model is adaptively compensated by a sliding window LSTM model to conduct the unmodeled dynamics. The effectiveness of the proposed method is demonstrated using the field data.

关键词： Railroad transportation

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Simulation and analysis of high-reliability braking system of aircraft based on self-feed energy nonsimilar margin

Simulation and analysis of high-reliability braking system o...

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CSAA/IET International Conference on Aircraft Utility systems 2020, AUS 2020

作者： Wang, Xiyu Shang, Yaoxing Hu, Haiying Qiu, Binghui Teng, Fengjian Zhang, Hao Jiao, Zongxia Liu, Xiaochao School of Automation Science and Electrical Engineering Beihang University Beijing100191 China AVIC Jiangxi Hongdu Aviation Industry Group Company Ltd Nanchang330000 China Beijing Aeronautical Technology Research Center Beijing100076 China Aerospace System Engineering Shanghai Shanghai201109 China Research Institute for Frontier Science Beihang University Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China

ISBN: (纸本)9781839535635

As one of the key and important airborne systems, aircraft braking systems mostly use traditional centralized hydraulic sources. With the new concept of "multi-electric aircraft", the aircraft energy supply system has further branched. This article introduces an integrated hydraulic brake device. It does not require an on-board hydraulic source, and can directly convert the energy of the wheel rotation when the aircraft lands, to complete the braking function. Using Simulink/SimHydraulics module, a corresponding model of aircraft brake integrated hydraulic device was established. The function of this self-feeding hydraulic brake device was verified through simulation and analysis. This method provides a new way to further study the braking system. © 2020 Institution of Engineering and Technology. All rights reserved.

关键词： Electric aircraft

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GPO: Global plane optimization for fast and accurate monocular SLAM initialization

arXiv

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arXiv 2020年

作者： Du, Sicong Guo, Hengkai Chen, Yao Lin, Yilun Meng, Xiangbing Wen, Linfu Wang, Fei-Yue PA2R2T Group State Key Laboratory of Complex System Management and Control Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing10049 China ByteDance AI Lab Beijing100089 China

Initialization is essential to monocular Simultaneous Localization and Mapping (SLAM) problems. This paper focuses on a novel initialization method for monocular SLAM based on planar features. The algorithm starts by homography estimation in a sliding window. It then proceeds to a global plane optimization (GPO) to obtain camera poses and the plane normal. 3D points can be recovered using planar constraints without triangulation. The proposed method fully exploits the plane information from multiple frames and avoids the ambiguities in homography decomposition. We validate our algorithm on the collected chessboard dataset against baseline implementations and present extensive analysis. Experimental results show that our method outperforms the fine-tuned baselines in both accuracy and real-time. Copyright © 2020, The Authors. All rights reserved.

关键词： Vision

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Noncontact Current Source Reconstruction Based on Independent Component Analysis-A Simulation Study

Noncontact Current Source Reconstruction Based on Independen...

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2019 IEEE PES Innovative Smart Grid Technologies Asia, ISGT 2019

作者： Nyaaba, Ayambire Patrick Huang, Qi Li, Jian Pan, Siming Gao, Bin Tian, Guiyun Zhang, Shijun Xiao, Bin 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 Chengdu611731 China School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China No. 9 Research Institute China Electronic Technology Group China

ISBN: (纸本)9781728135205

This paper implemented a current reconstruction system based on independent component analysis and magnetic field sensors. In this paper both the normal approximation and interfered approximation of magnetic flux density generated by current carrying conductors and sensed by four magnetic sensors are presented and discussed. The output voltage of the sensor array with and without interference was calculated based on the comprehensive independent component analysis algorithm. The relative reconstruction error based on the algorithm for array output voltage are within acceptable levels for protective devices proving the feasibility of the algorithm for source reconstruction. © 2019 IEEE.

关键词： Independent component analysis

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A Multi-Objective Model with Probability Constraints of Trans-Provincial Dynamic Stability Limit

A Multi-Objective Model with Probability Constraints of Tran...

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2019年第五届机械工程及自动化科技国际会议

作者： Ke Yang Rui Mao Xu Wen Chuncheng Gao Miao Huang Wei Yan Southwest Subsection of State Grid State Key Laboratory of Power Transmission Equipment & System Security and New Technology(Chongqing University) College of Automation Chongqing University of Posts and Telecommunications Beijing Ke Dong Electric Power Control System Co. Ltd. Nari Group Corporation/State Grid Electric Power Research Institute

With the rapid development of clean energy and serious delay of grid construction, water abandonment is becoming more and more severe. Under this condition, this paper proposed a multi-objective model with probability constraints of trans-provincial hydropower consumption considering dynamic stability limit. Firstly, a mathematical expression about the dynamic stability limit of trans-provincial channel is constructed. Secondly, a risk assessment index of abandoned water is established on the basis of semi-absolute deviation. Then, based on the framework of stochastic programming, a multi-objective model with probability constraints is proposed for hydropower transmission in trans-provincial trade. By means of genetic algorithm with embedded Monte-Carlo simulation technology, the model can be solved efficiently. Finally, data of Tibet power grid is calculated to verify the validity and universality of the research. The results show that the established model can achieve optimal economic benefit between grid companies and generation enterprises, and also effective management of water abandonment risk.

关键词： A Multi-Objective Model with Probability Constraints of Trans-Provincial Dynamic Stability Limit Model

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Event-triggered consensus for linear continuous-time multi-agent systems based on a predictor

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Information Sciences 2018年 459卷 278-289页

作者： Jian Sun Qiuling Yang Xiaoyu Liu Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 PR China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 PR China China North Industrial Group Corporation Limited China Ordnance Industry Navigation and Control Technology Institute Beijing 100089 PR China

In this paper, the problem of an event-triggered consensus for a linear continuous-time multi-agent system is investigated. A new event-triggered consensus protocol based on a predictor is proposed to achieve consensus while not requiring continuous communication among agents. The predictor utilizes an artificial closed-loop system to predict the future state of each agent. With the proposed consensus protocol, each agent only needs to monitor its own states to determine its event-triggered instants. When an event of an agent is triggered, the agent immediately updates its consensus protocol and sends its state information to its neighbors. When an agent receives state information from its neighbors, the agent immediately updates its consensus protocol and predictor. A necessary and sufficient condition that solves the consensus problem is derived. Moreover, it is proved that Zeno behaviors are excluded. Finally, some numerical examples are given to illustrate that, with the proposed protocol, a multi-agent system can achieve consensus while greatly reducing event-triggered times.

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Research on Monthly Security Checking Method of Power Grid Large Consumer Direct Electric Quantity Purchasing

Research on Monthly Security Checking Method of Power Grid L...

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2018 International Conference on Power, Energy and Environmental Engineering（ICPEEE 2018)

作者： Xin-qiao FAN Zi-jing LU Jun-wei YANG Jian-bo SUN Da-hu LI School of Automation Beijing Information Science and Technology University Dispatch and Control Center State Grid Hubei Electric Power Company NARI Group Corporation(State Grid Electric Power Research Institute) Beijing Kedong Electric Power Control System Co.Ltd.

To realize the grid security checking of large consumer direct electric quantity purchasing plan,a monthly security checking method of large consumer direct electric quantity purchasing based on grid partitions is presented in the *** the method,a power grid is divided into security partitions containing a certain number of units and loads,and the monthly electric quantity decomposition and the daily electric quantity decomposition models with the constraints of electric quantity and power in the partition being considered are *** the power flow of the tie line is less than the allowed stability limit value is one of the constraints in the electric quantity trading of different *** partition electric quantity deviation is reflected in the form of slack variables in the constraint conditions,and the minimum slack variable is used as the optimization target to optimize the built *** realize the monthly security checking of the contract electric quantity,the monthly contract electric quantity is decomposed to days considering electric quantity constraints,and the daily electric quantity is decomposed to hours combining the output levels of ***,an example of the IEEE 39 node test case is constructed,and the effectiveness and feasibility of the presented security checking method is verified by setting different direct power purchasing electric quantity of units.

关键词： Security checking Electric quantity decomposition Large consumer direct electric quantity purchasing Grid partition

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Study on Grid-connected Operation Performances Evaluation of Photovoltaic Power Stations

Study on Grid-connected Operation Performances Evaluation of...

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2018 3rd International Conference on Electrical, control and automation Engineering (ECAE 2018)

作者： Xin-qiao FAN Zi-jing LU Jun-wei YANG Da-hu LI Jian-bo SUN Ya-li ZHANG School of Automation Beijing Information Science and Technology University Dispatch and Control Center State Grid Hubei Electric Power Company NARI Group Corporation(State Grid Electric Power Research Institute) Beijing Kedong Electric Power Control System Co.Ltd.

To achieve the grid-connected operation performances evaluation of photovoltaic power stations, a grid-connected operation performance index system and the comprehensive evaluation method on photovoltaic power station grid-connected performances is presented. The rank sum ratio of each photovoltaic power station to reflect grid-connected performances is calculated by using the rank-sum ratio method. According to the rank sum ratio values, the comprehensive grid-connected performance of each photovoltaic power station is evaluated. The actual monitoring data of photovoltaic power stations are used to calculate performance indexes, and comprehensive evaluation on grid-connected performances of photovoltaic power station is verified. The obtained results show that the comprehensive grid-connected performance of the photovoltaic power station can be correctly evaluated by using the presented evaluation method.

关键词： Operation performance evaluation Photovoltaic power station Rank-sum ratio

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Autoencoder-based Fault Diagnosis for Grinding system 29

Autoencoder-based Fault Diagnosis for Grinding System

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第29届中国控制与决策会议

作者： QU Xing-yu ZENG Peng Fu Dong-dong Xu chengcheng Key Lab of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Northern Heavy Industries Group Co.Itd College of Information Science and Engineering Northeastern University

ISBN: (纸本)9781509046584

At present, most fault diagnosis for grinding system is based on artificial judgments, which is inefficient, low accurate, high cost and easy to cause casualties. The traditional neural network has an unsatisfying performance to predict on high dimensional dataset, and is hard to extract crucial features, which brings about terrible classification results. To solve the above problems, the paper present a deep learning based on autoencoder to realize the intelligent diagnosis for grinding system. The algorithm applies autoencoder to extract features from fault dataset, and transit the non-linearized features to Softmax classification to recognize the fault category. This paper compares autoencoder-based deep learning networks and the traditional BP neural networks in experiments, and it is concluded that the autoencoderbased deep learning outperforms BP networks in the unbalanced classification. The classification precision is up to 92.4% by using the proposed method.

关键词： Fault Diagnosis Autoencoder Softmax Classifier Deep Learning

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