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An adaptive turbo-shaft engine modeling method based on PS and MRR-LSSVR algorithms

Chinese Journal of Aeronautics 2013年第1期26卷 94-103页

作者： Wang Jiankang Zhang Haibo Yan Changkai Duan Shujing Huang Xianghua College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Aviation Motor Control System Institute Aviation Industry Corporation of China

In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.

关键词： Adaptive engine model Least square support vector regression machine Modeling method Parameter selection Turbo-shaft engine

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New algorithm for the loss of excitation function

New algorithm for the loss of excitation function

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International Conference on Green Computing Communication and Electrical engineering (ICGCCEE)

作者： G. Priyadharshini M. Mynavathi M. Sowmiya Dept of Instrumentation and Control Engineering Sethu Institute of Technology Madurai India Dept of Electrical and Electronics Engineering Dr.N.G.P. Institute of technology Coimbatore India Power System Engineering Thiagarajar College of Engineering Madurai India

ISBN: (纸本)9781479949816

Loss of field is one of the incidents that threats synchronous generators and power systems. After the excitation is lost, rotor current decays at a rate determined by the field circuit time constant. The internal generator voltage will decay at the same rate. Then the machine behaves as an asynchronous generator and draws a high quantity of reactive power from the network. The active power output will intensely oscillate and excessive current will traverse through stator windings. In this paper two protection methods are considered. The first one is based on conventional impedance method which consists of offset Mho relay for the fast detection of loss of field in synchronous generators. The second one is based on the measurement of the three phase reactive power output of the machine, and monitors the direction and magnitude of leading reactive power at the generator output terminal. It mainly aims to develop algorithms for the conventional impedance method and the reactive power method. The comparison of these two methods is also carried out to find out the method in which quick tripping results can be obtained. A two machine system is used in case studies and is modeled using MATLAB simulink.

关键词： Generators Reactive power Relays Impedance Rotors Impedance measurement

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A fault diagnosis model of power transformer using Imperialistic Competitive Algorithm and Support Vector Machine

A fault diagnosis model of power transformer using Imperiali...

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The 2014 IMSS International Conference on Future Manufacturing engineering(ICFME 2014)

作者： Yiyi Zhang Zhihua Zhong Hanbo Zheng Chao Tang Yan Sun Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Archives of Guangxi University State Grid Henan Electric Power Research Institute College of Engineering and Technology Southwest University Guangxi Power Grid Power Dispatching and Control Center

A fault diagnosis model using an Imperialistic Competitive Algorithm(ICA) and SVM integrated approach was established in the *** was applied to search and obtain the parameters of ***,cross validation and normalizations were applied in the training processes of SVM,and the trained SVM model with the selected parameters was established to conduct fault *** results demonstrate that the proposed approach promotes the fault diagnosis accuracy of transformers.

关键词： power transformer fault diagnosis Support Vector Machine(SVM) Imperialistic Competitive Algorithm(ICA) DGA

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Effect of training methods on the accuracy of PCA-KNN partial discharge classification model

Effect of training methods on the accuracy of PCA-KNN partia...

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IEEE Region 10 International Conference TENCON

作者： Norasage Pattanadech Phethai Nimsanong Electrical Engineering Dept King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Power System Operation and Control Section 2 Metropolitan Electricity Authority Bangkok Thailand

The aim of this paper is to describe the effect of training methods on the accuracy of PCA-KNN partial discharge (PD) classification model. This model used principal component analysis (PCA) combined with k-nearest neighbor (KNN) model, so called, PCA-KNN PD classification model for PD pattern classification. PD phenomena, corona at high voltage side in air (CHV), corona at low voltage side in air (CLV), surface discharge (SF), and internal discharge (IN) were experimented in the shielding room. Electromagnetic wave due to PD phenomena was detected using a log-periodic antenna and recorded employing a spectrum analyzer. 80 PD experiments in total were performed. The original independent variables for the classification model, skewness and kurtosis of each period of the captured signals, were calculated. To study the effect of training methods: two patterns for data training, odd/even and block training methods were investigated. In case of the block training method, the effect of training data number can be examined as well. Besides, noise signals were generated with the computer program and trained into the PD classification models. The peak of noise signal was set up at 30% of the peak value of the PD signal. These noise signals were added with the PD signals to generated a mixed noise - PD signal. Then, the mixed noise - PD signals were used to evaluate the performance of the PCA-KNN PD classification model. It was found that the block data training method provided the higher accuracy PD classification compared with the odd/event data training method. The block training method with 80% training data/20% testing data gave the highest accuracy (95% correction) for PD classification without noise signal. However, this training technique provided the lowest accuracy (56.25% correction) for PD classification with the mixed noise-PD signals.

关键词： Partial discharges Training Noise Accuracy Discharges (electric) Training data Testing

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Analysis of the Steady State Characteristics and Regulation Strategies of the Frequency in the Northwest power Grid

Analysis of the Steady State Characteristics and Regulation ...

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International Conference on Instrumentation, Measurement, Computer, Communication and control (IMCCC)

作者： Dandan Dong Zhongwei Li Hengxu Zhang Yufeng Guo Tao Zhao Dept. of Electrical Engineering Harbin Institute of Technology Harbin China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong University) Jinan China

ISBN: (纸本)9781479965762

Using frequency data of the Northwest power Grid from Feb. 15th to 28th, 2013 that is measured by PMU-light units in Shandong University, the steady state characteristics of frequency are analyzed in this paper. Duration and number of low-frequency and high-frequency events are listed. Statistics of daily highest, lowest and average frequency values are given. Ensemble averaged frequency values are calculated. Characteristics of steady-state frequency in the Northwest power Grid are summarized and influence factors of frequency are discussed. The influence of the proportion of wind power on the frequency quality is simulated. The necessity of the application of a new frequency control method called DFR (Demand as Frequency controlled Reserve) in the Northwest power Grid is discussed.

关键词： power grids Time-frequency analysis Frequency control Wind turbines power system stability

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Effect of noise signals on partial discharge classification models

Effect of noise signals on partial discharge classification ...

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IEEE Region 10 International Conference TENCON

This document proposes the comparison of four statistical classification models for partial discharge (PD) classification as follows: k-nearest neighbors (KNN) model, probabilistic neural network (PNN) model, and other two statistical models using principal component analysis (PCA) for a data reduction approach combined with KNN and PNN models, so called, PCA-KNN model and PCA-PNN model. PD phenomena, corona at high voltage side in air (CHV), corona at low voltage side in air (CLV), surface discharge (SF), and internal discharge (IN) were simulated and measured in the shielding room. Electromagnetic wave due to PD phenomena was detected using a log-periodic antenna and recorded employing a spectrum analyzer. 80 experiments in total were performed for CHV, CLV, SF, and IN. The original independent variables for each classification model, skewness and kurtosis of each period of the captured signals, were calculated. Then, 60% of experimented data was used as a training data for the PD classification model. Another 40% experimented data was used to evaluate the performance of the designed PD classification models. Besides, noise signals were generated with computer program and trained into the PD classification model as well. The peak of noise signal was set up at 10%, 20% and 30% of the peak value of the PD signal. These noise signals were added with the PD signals to generate a mixed noise - PD signal. Then, the mixed noise - PD signals were used to evaluate the performance of the PD classification models. It was found that the designed KNN, PNN, PCA-KNN and PCA - PNN model can predict PD patterns without noise signal with the accuracy 100%. Noise signals with amplitude of 20% or more of peak value of PD signal have obviously influence the accuracy of PD pattern classification. The combination of PCA with KNN model can improve the ability of PD classification compared with KNN PD classification model. However, it seems that PCA provided negative effect when PCA was c

关键词： Partial discharges Noise Principal component analysis Discharges (electric) Atmospheric modeling Data models Training

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A formal model for attack mutation using dynamic description logics 8

A formal model for attack mutation using dynamic description...

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8th IFIP International Conference on Intelligent Information Processing, IIP 2014

作者： Wang, Zhuxiao Guo, Jing Shi, Jin He, Hui Zhang, Ying Peng, Hui Tian, Guanhua School of Control and Computer Engineering State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing100029 China Education Technology Center Beijing International Studies University Beijing100024 China Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783662449790

All currently available Network-based Intrusion Detection systems (NIDS) rely upon passive protocol analysis which is fundamentally flawed as an attack can evade detection by exploiting ambiguities in the traffic stream as seen by the NIDS. We observe that different attack variations can be derived from the original attack using simple transformations. This paper proposes a semantic model for attack mutation based on dynamic description logics (DDL(X)), extensions of description logics (DLs) with a dynamic dimension, and explores the possibility of using DDL(X) as a basis for evasion composition. The attack mutation model describes all the possible transformations and how they can be applied to the original attack to generate a large number of attack variations. Furthermore, this paper presents a heuristics planning algorithm for the automation of evasion composition at the functional level based on DDL(X). Our approach employs classical DL-TBoxes to capture the constraints of the domain, DL-ABoxes to present the attack, and DL-formulas to encode the objective sequence of packets respectively. In such a way, the evasion composition problem is solved by a decidable tableau procedure. The preliminary results certify the potential of the approach. © IFIP International Federation for Information Processing 2014.

关键词： Semantics

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A molecular cryptography model based on structures of DNA self-assembly

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Chinese Science Bulletin 2014年第11期59卷 1192-1198页

作者： Yang, Jing Ma, Jingjing Liu, Shi Zhang, Cheng Beijing Key Laboratory of New Technology and System on Measuring and Control for Industrial Process School of Control and Computer Engineering North China Electric Power University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China

With the progress of DNA computing, DNA-based cryptography becomes an emerging interdisciplinary research field. In this paper, we present a novel DNA cryptography that takes advantage of DNA self-assembled structure. Making use of the toehold strands recognition and strand displacement, the bit-wise exclusive-or (XOR) operation is carried out to fulfill the information encryption and decryption in the form of a one-time-pad. The security of this system mainly comes from the physical isolation and specificity of DNA molecules. The system is constructed by using complex DNA self-assembly, in which technique of fluorescent detection is utilized to implement the signal processing. In the proposed DNA cryptography, the XOR operation at each bit is carried out individually, thus the encryption and decryption process could be conducted in a massive, parallel way. This work may demonstrate that DNA cryptography has the great potential applications in the field of information security.

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A short-term heuristic method for peak operation of pumped hydroenergy storage plants between multiple power grids on bulk power grid platform

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Dianli Xitong Zidonghua/Automation of Electric power systems 2014年第9期38卷 53-60页

作者： Cheng, Xiong Shen, Jianjian Cheng, Chuntian Wu, Xinyu Lu, Jianyu Li, Gang Institute of Hydropower System and Hydroinformatics Dalian University of Technology Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China East China Electric Power Dispatching and Controlling Subcenter State Grid Corporation of China Shanghai200120 China

A short-term heuristic method of pumped (hydroenergy) storage plants (PSP) operation for regulating peak loads of multiple power grids has been developed based on the actual project of East China Grid (ECG). The power generation or pump power of PSP is decided by the maximum or minimum value of the total load at each iteration. And power generation or pump power is further allocated between power grids using two strategies, known as power cutup and combination optimization. This process is repeated till the desired target objectives of PSP are satisfied. The case results over ECG show that the proposed method is able to solve the load distribution problem of PSP between multiple power grids. ©2014 State Grid Electric power Research institute Press.

关键词： Heuristic methods

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Modeling and detection of rotating stall in axial flow compressors, II: Experimental study for a low-speed compressor in Beihang University

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Kongzhi Lilun Yu Yingyong/control Theory and Applications 2014年第10期31卷 1414-1422页

作者： Wang, Cong Si, Wen-Jie Wen, Bin-He Zhang, Ming-Ming Wang, Yong Hou, An-Ping College of Automation Science and Technology South China University of Technology GuangzhouGuangdong510640 China Institute of AVIC Aviation Motor Control System WuxiJiangsu214063 China Department of Mechanics and Engineering Science Peking University Beijing100871 China School of Energy and Power Engineering BeiHang University Beijing100191 China

Early detection of rotating stall and surge in axial flow compressors is of great importance for improving the working efficiency and stability of the compressor. Based on deterministic learning (DL) theory and dynamical pattern recognition, this paper presents experimental research for approximately accurate modeling and rapid detection of stall precursors, and then employs a low-speed axial flow compressor test rig of Beihang University for online experimental verification. Firstly, by installing high response dynamic pressure transducers arranged circumferentially around the casing of the axial compressor, the dynamic pressure data are collected. Based on deterministic learning theory, the system dynamics underlying prestall and stall inception patterns are identified. Secondly, based on modeling results, rapid detection of small oscillation faults is used to perform the detection of stall precursors. Sufficient online experiments are conducted to investigate the efficiency of the approach. Results show that, in different working speeds, this approach successfully detects inception signal of aerodynamic instability of the compressor 0:3 s~1 s in advance to the start of rotating stalls. ©, 2014, South China University of Technology. All right reserved.

关键词： Pattern recognition

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