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作者： Chang, Ru Fang, Yi-Ming Wang, Zhi-Jie Tian, Hai-Bo Key Lab of Industrial Computer Control Engineering of Hebei Province College of Electric Engineering Yanshan University Qinhuangdao 066004 China

ISBN: (纸本)9789881725592

To deal with the problems caused by unmatched uncertainties and external load disturbance exist in mill hydraulic servo position system, a robust adaptive controller design method is presented in this paper. The controller is composed of a state feedback controller and an adaptive compensator, the state feedback controller is obtained by solving a Riccati equation, and the compensator is obtained by estimating the upper bounds of the unknown external disturbances. It is proved that the global asymptotic stability of the resulting closed-loop system can be guaranteed. Finally, simulation results for the mill hydraulic servo position system illustrate the validity of the proposed algorithm. © 2011 Chinese Assoc of Automati.

关键词： Closed loop systems

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Cooperative spectrum sensing for cognitive radios based on a PA-GABC algorithm

Cooperative spectrum sensing for cognitive radios based on a...

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International Conference on Electronics, Communications and control (ICECC)

作者： Xinbin Li Lei Liu Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yan Shan University Qinhuangdao China

Spectrum sensing plays a critical role in cognitive radio networks. A good sensing scheme can reduce the false alarm probability and increase the detection probability, and thus improves utilization. In this paper, in order to avoid the defect that cooperative spectrum sensing based on Particle Swarm Optimization (PSO) algorithm is easy to trap into a local optimization. We propose a population adaptive Gbest-guided artificial bee colony (PA-GABC) algorithm and it is applied to cooperative spectrum sensing for cognitive radios field. Simulations are performed to compare the performance of the PA-GABC algorithm and traditional artificial bee colony (ABC) algorithm. The performance of the proposed cooperative spectrum sensing method based on the PA-GABC and that of the cooperative spectrum sensing method using particle swarm optimization (PSO) algorithm are also compared. Results show that the proposed PA-GABC-based cooperative spectrum sensing method is efficient and stable, and it gets higher detection probability than the ABC-based method and the PSO-based method under the same probability of false alarm.

关键词： Sensors Cognitive radio Algorithm design and analysis Optimization Signal processing algorithms Particle swarm optimization Electrical engineering

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Adaptive Particle Swarm-Based Fuzzy Clustering Algorithm in the Application of Steam Drum Pulverized Coal Fired Boiler

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International Journal of Advancements in Computing Technology 2011年第11期3卷 444-452页

作者： Ma, Yunfei Niu, Peifeng Zhao, Yantao Ma, Xiaofei Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 Hebei Province China Key Laboratory of Hebei Province Industrial Computer Control Engineering Yanshan University Qinhuangdao 066004 China Northeastern University at Qinhuangdao Qinhuangdao 06600 China

The Pulverized Coal Fired Boiler is a control object with time-varying parameters, large delay and multivariate tight-coupling. This paper, aiming at improving the actualities of excessive parameters and suboptimal data clustering effect in the Steam Drum Pulverized Coal Boiler running, proposes a new algorithm - Fuzzy Clustering Algorithm (APFM) to fulfill the efficiency optimization of the boiler combustion. Based on the Adaptive Particle Swarm Optimization Algorithm (APSO), this new algorithm overcomes the disadvantages of FCM algorithm such as the sensitivity to initial value and the easy involvement in partial optimum, and enhances the abilities of APSO algorithm such as global search and escape from partial optimum. Finally, the feasibility and effectiveness of this clustering method is demonstrated through the simulation experiment.

关键词： Fuzzy clustering

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Fault search based on grey fuzzy multi-attribute decision-making

Fault search based on grey fuzzy multi-attribute decision-ma...

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International Conference on Fluid Power and Mechatronics (FPM)

作者： Chengyu Yao Zhen Dang Dongning Chen Shijun Lv Key Laboratory of Industrial Computer Control Engineering of Hebei Yanshan University Qinhuangdao China Key Laboratory of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University Qinhuangdao China

In order to overcome the characteristics of uncertainty and incomplete information of fault attribute in searching for fault, a new fault search method based on the fault tree and grey fuzzy multi-attribute decision-making is proposed in this paper. Firstly, utilizing fault tree analysis (FTA) method to determine the initial fault alternative, fault probability and search cost of the fault alternative are considered as fault attributes simultaneously, the attribute value of fault alternative is described as grey fuzzy numbers, calculating the attribute weight by the information entropy method. Then, the grey relational grade between the fault alternative and the ideal alternative is calculated base on grey relational analysis method, and relative closeness of fault alternative is achieved. Finally, according to the relative closeness determine the search order of all fault alternatives. An engineering example of the hydraulic suspension system of a certain type truck is adopted to demonstrate the feasibility and accuracy of the proposed method.

关键词： Decision making Fault trees Suspensions Search methods Pragmatics Fault diagnosis Manganese

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Bearing fault detection and diagnosis of a wind turbine

Bearing fault detection and diagnosis of a wind turbine

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International Conference on Consumer Electronics, Communications and Networks

作者： Shenggang Yang Xiaoli Li Ming Liang Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University슠 Qinhuangdao China Department of Mechanical Engineering University of Ottawa Ottawa ONT Canada

The most commonly used components in a wind turbine are bearings which failure could lead to malfunction and ultimately complete stall of a mission-critical equipment. Hence, bearing Fault Detection is an imperative part of preventive maintenance procedures of a wind turbine. This paper presents a Free Parameter method to implement bearing fault diagnosis. This method extracts the amplitude and frequency modulations of the vibration signals that measure from a wind turbine system. As the amplitude demodulation is inherent in it, the fault frequency will be detected from the spectrum of the signal. Simulated signal and experimental data has validated the effectiveness of this method.

关键词： Resonant frequency Vibrations Band pass filters Wind turbines Harmonic analysis Fault detection Power harmonic filters

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Sensor selection for an accurate closed form localization in cognitive radio networks: The trade-off between model accuracy and geometry structure

Sensor selection for an accurate closed form localization in...

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IEEE Conference on industrial Electronics and Applications (ICIEA)

作者： Bin Zhao Kai Ma Xinping Guan Wengdong Xiao Key Laboratory of Industrial Computer Control Engineering of Hebei province Institute of Electrical Engineering Yanshan University슠 Qinhuangdao China Institute for Infocomm Research Agency for Science Technology and Research Singapore

In cognitive radio networks (CRNs), localization of primary user is the key problem for location-aware spectrum allocation. In order to improve spectrum utilization and decrease interference to primary users, localization should be computationally efficient and as accurate as possible. Based on an accurate closed form localization method, the tradeoff between model accuracy and geometry structure is analyzed. By selecting part of the secondary users, the estimation accuracy is increased and the computation amount is reduced at the same time. Finally, the simulations are performed and the proposed tradeoff analysis is done. The simulation results show the significant improvement on the localization performance by sensor selection.

关键词： Accuracy Geometry Cognitive radio Computational modeling Estimation Signal to noise ratio

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Wind turbine bearing condition monitoring based on high frequency resonance method

Wind turbine bearing condition monitoring based on high freq...

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International Conference on Electronics, Communications and control (ICECC)

作者： Xueyan Zhang Shenggang Yang Xiaoli Li Department of Information Technology Ningbo TV & Radio University Ningbo Zhejiang China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao China

Bearing is the most frequently used component in a wind turbine, and its' faults would lead to completely stall of a machine. Therefore, bearing Fault Diagnosis is an important part of condition monitoring in a wind turbine. This paper presented a High Frequency Resonance (HFR) method to implement bearing fault detection and fault diagnosis. This technique extracted the amplitude and frequency modulations of the vibration signals which measured from a wind turbine system. For the amplitude demodulation is inherent in the vibration signals, the fault frequency will be detected from the spectrum of the transformed original signals. And the effectiveness of this approach has been validated by simulated signal and experimental data.

关键词： Vibrations Resonant frequency Wind turbines Noise measurement Harmonic analysis Power harmonic filters Fault detection

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Joint power and carrier allocation for cognitive radio networks based on OFDMA

Joint power and carrier allocation for cognitive radio netwo...

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作者： Wei, Xiaomin Ma, Kai Zhao, Bin Luo, Xiaoyuan Guan, Xinping Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9789881725592

This paper is concerned with the joint power and carrier allocation problem in cognitive radio networks based on OFDMA. Considering the limit of the throughput for original resource allocation algorithm, we propose the improved framework, in which the secondary user can transmit with a proper power as the primary user is active. Numerical results show that the proposed algorithm can improve the throughput of the network effectively. © 2011 Chinese Assoc of Automati.

关键词： Cognitive radio

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Multi-Objective Optimization for Tandem Cold Rolling Schedule

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Journal of Iron and Steel Research International 2010年第11期17卷 34-39页

作者： YANG Jing-ming ZHANG Qing CHE Hai-jun HAN Xin-yan Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 Hebei China

Considering the multivariable, strong-coupled, and nonlinear features of tandem cold rolling mill, a mathematical model of multi-objective optimization was built to facilitate the design of new systems aiming at equating the relative load, preventing slip, and obtaining best shape. BP （back propagation） neural network based on Levenberg- Marquardt algorithm was used for predicting the rolling force. The multi-objective fuzzy theory and method were introduced during the optimization. With an example of 1 370 mm tandem cold rolling mill, the rolling schedule of the common rolling, the single-objective optimization design, and the multi-objective fuzzy optimization design were compared with each other. The results generated from the case study showed that the proposed approach could significantly decreased the values of three objective functions simultaneously and the performance of the optimal rolling schedule was satisfactory and promising. Moreover, the capability and usefulness of fuzzy application in tandem cold rolling schedule were clearly demonstrated.

关键词： rolling schedule tandem cold rolling neural network multi-objective fuzzy optimization

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T-S model based fault tree analysis on the hoisting system of rubber-tyred girder hoister

T-S model based fault tree analysis on the hoisting system o...

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2010 WASE International Conference on Information engineering, ICIE 2010

作者： Yao, Chengyu Zhang, Yingyi Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9780769540801

Hoisting system is the key part of the girder hoister, and its reliability determines the stability and security of the girder hoister directly. Hoisting system consists of mechanical, electrical and hydraulic components. Owing to the multiple and complex failure modes and mechanisms of the components, the hoisting system's reliability evaluation is accomplished by Fault Tree Analysis (FTA) based on T-S model. Failure probabilities can be described as fuzzy possibilities and fault degrees are expressed in terms of fuzzy numbers, while events' relationships are described by T-S gates instead of conventional logic gates. A method to acquire knowledge about the premise and consequent events is given, in terms of fuzzy rules of T-S gates made up of fuzzy possibilities and fault degrees of components. Fuzzy possibilities of the intermediate events and the top event are computed by MATlab, in terms of information about field experiences and expert data. Considering the influence of fault degrees to the system at the same time, it offers reference to find and improve relevant weaknesses of the system, thus the dependability of the whole hoisting system is improved. © 2010 IEEE.

关键词： Fault tree analysis

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