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In order to more effectively solve some difficult problems in gearbox failure diagnosis, a gearbox fault diagnosis method based on Relevance Vector Machine (RVM) is proposed. RVM is developed in Bayesian framework. It does not need to estimate the regularization parameter with less relevance vectors, and its kernel function does not need to satisfy Mercer condition. Simulation results show that: compared with the traditional BP neural network, RVM has the faster modeling speed, more accurate diagnosis, and is worthy of promotion and application in fault diagnosis of the gearbox. © (2013) Trans Tech Publications, Switzerland. Source


Gan X.-S.,XiJing College | Duanmu J.-S.,PLA Air Force Aviation University | Wang J.-F.,PLA Air Force Aviation University | Cong W.,PLA Air Force Aviation University
Knowledge-Based Systems | Year: 2013

To improve the ability of detecting anomaly intrusions, a combined algorithm is proposed based on Partial Least Square (PLS) feature extraction and Core Vector Machine (CVM) algorithms. Principal elements are firstly extracted from the data set using the feature extraction of PLS algorithm to construct the feature set, and then the anomaly intrusion detection model for the feature set is established by virtue of the speediness superiority of CVM algorithm in processing large-scale sample data. Finally, anomaly intrusion actions are checked and judged using this model. Experiments based on KDD99 data set verify the feasibility and validity of the combined algorithm. © 2012 Elsevier B.V. All rights reserved. Source


Ma Z.,Lanzhou University | Ma Z.,Yuncheng University | Zhou J.,Lanzhou University | Chen Z.,XiJing College | Xie E.,Lanzhou University
Diamond and Related Materials | Year: 2011

Terbium-doped SiCN (SiCN:Tb) thin films were deposited by rf magnetron reactive sputtering at 800 °C. The as-prepared samples were characterized by XRD, FTIR, and XPS. The results showed that SiCN:Tb films mainly contained both SiC and Si3N4 nano-compositions with complicated chemical bond networks. Photoluminescence measurements indicated that the undoped SiCN films exhibited a blue-green light emission, while SiCN:Tb films emitted a strong green one. The SiC nanocrystallites formed in the undoped SiCN films might be responsible for the blue-green light emission, while the formed quaternary Si-C-Tb-O compositions in the doped samples could account for the strong green PL behaviors. © 2011 Elsevier B.V. Source


Gan X.,XiJing College | Duanmu J.,PLA Air Force Aviation University | Meng Y.,Xian Jiaotong University | Cong W.,PLA Air Force Aviation University
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2012

To accurately describe the dynamic characteristics of a flight vehicle by means of an aerodynamic model, a wavelet neural network (WNN) aerodynamic modeling method from flight data based on an improved particle swarm optimization (IPSO) algorithm is proposed. To address the deficiencies of the standard PSO(SPSO) algorithm, the closest particle information and mutation operation are introduced in this method to improve the global searching ability of WNN parameters and overcome premature convergence. Then, in light of the aerodynamic modeling flow from flight data for flight vehicles, a WNN model trained by the IPSO algorithm is established. Experimental results show that the proposed aerodynamic modeling method is characterized by high forecast precision, fast convergence speed and effective suppression of premature convergence. It is valid and feasible for aerodynamic modeling from flight data. Source


Wang Z.,XiJing College
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | Year: 2011

The passivity control problem for a nonlinear electromechanical transducer chaotic system with relative 2nd order is studied. It is assumed that the system has a standard chain structure. By using the Backstepping method and the equivalence relation between the passivity and the stability, feedback stabilizing controller of the system is designed and has been proved. The simulation results demonstrate the effectiveness of the proposed method. Source

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