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A New Method For Machinery Fault Diagnoses Based On an Optimal Multiscale Morphological Filter

STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING 2013年第12期59卷 719-724页

作者： Tan, Wei Chen, Xiaoan Dong, Shaojiang Chongqing Univ State Key Lab Mech Transmiss Chongqing 630044 Peoples R China Chongqing Univ Technol Key Lab Adv Mfg Technol Automobile Parts Chongqing Peoples R China

In order to effectively eliminate the noise and extract the impulse components in the vibration signals, a new method based on an optimal multiscale morphological filter is proposed. In this method, firstly, the average of the closing and opening operator is used to construct the morphological filter, then the multiscale morphological filters' structure elements (SEs) are optimized and selected using a particle swarm optimization algorithm (PSO). The noise in the original signal is filtered by the multiscale morphological filter. The proposed method was evaluated by simulated signals and bearing fault signals. The results show that the method can effectively filter the noise and extract the impulse characteristics of the vibration signals, which demonstrate the effectiveness of the proposed method.

关键词： multiscale morphological filter structure element particle swarm optimization algorithm noise reduction

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Comparative analysis of the machine repair Problem with imperfect coverage and service pressure condition

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APPLIED MATHEMATICAL MODELLING 2013年第5期37卷 2870-2880页

作者： Wang, Kuo-Hsiung Liou, Cheng-Dar Lin, Yu-Hsueh Providence Univ Dept Comp Sci & Informat Management Taichung 43301 Taiwan Natl Formosa Univ Dept Business Adm Huwei 63201 Yunlin Taiwan Natl Chung Hsing Univ Dept Appl Math Taichung 402 Taiwan

In this paper we analyze the warm-standby M/M/R machine repair problem with multiple imperfect coverage which involving the service pressure condition. When an operating machine (or warm standby) fails, it may be immediately detected, located, and replaced with a coverage probability c by a standby if one is available. We use a recursive method to develop the steady-state analytic solutions which are used to calculate various system performance measures. The total expected profit function per unit time is derived to determine the joint optimal values at the maximum profit. We first utilize the direct search method to measure the various characteristics of the profit function followed by Quasi-Newton method to search the optimal solutions. Furthermore, the particle swarm optimization (PSO) algorithm is implemented to find the optimal combinations of parameters in the pursuit of maximum profit. Finally, a comparative analysis of the Quasi-Newton method with the PSO algorithm has demonstrated that the PSO algorithm provides a powerful tool to perform the optimization problem. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Comparative analysis Imperfect coverage particle swarm optimization algorithm Profit Service pressure

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PSO algorithm for fundamental frequency optimization of fiber metal laminated panels

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STRUCTURAL ENGINEERING AND MECHANICS 2013年第5期47卷 713-727页

作者： Ghashochi-Bargh, H. Sadr, M. H. Amirkabir Univ Technol Ctr Excellence Computat Aerosp Engn Dept Aerosp Engn Tehran Iran

In current study, natural frequency response of fiber metal laminated (FML) fibrous composite panels is optimized under different combination of the three classical boundary conditions using particle swarm optimization (PSO) algorithm and finite strip method (FSM). The ply angles, numbers of layers, panel length/width ratios, edge conditions and thickness of metal sheets are chosen as design variables. The formulation of the panel is based on the classical laminated plate theory (CLPT), and numerical results are obtained by the semi-analytical finite strip method. The superiority of the PSO algorithm is demonstrated by comparing with the simple genetic algorithm.

关键词： fiber metal laminated panel particle swarm optimization algorithm fundamental frequency

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A novel current injection model of GCSC for control and damping of power system oscillations

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IETE JOURNAL OF RESEARCH 2013年第6期59卷 768-773页

作者： Safari, Amin Rezaei, Navid Islamic Azad Univ Ahar Branch Dept Elect Engn Ahar Iran Iran Univ Sci & Technol Dept Elect Engn Tehran Iran

The paper proposes the theory and the modeling technique of the new invention of the flexible AC transmission system (FACTS) device, i.e., Gate controlled series capacitor (GCSC) for power flow control of power transmission lines and damping of low-frequency oscillations. In this study, a current injection model of the GCSC is used for studying the effect of the GCSC on the low-frequency oscillations, which is incorporated in the transmission system model. To be sure of optimal adjustment of the applied damping controller, the particle swarm optimization algorithm is employed as an efficient heuristic optimizer to find out the near global optimum set of the damping controller parameters. The proposed model is applied to a damping controller design of a multi-machine power system. Detailed simulations are carried out with MATLAB/SIMULINK environment and the effect of the GCSC-based damping controller and the current injection model over the system stability is studied.

关键词： Enhancing dynamic stability Gate controlled series capacitor ITAE performance index particle swarm optimization algorithm

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A novel fitting algorithm for Brillouin scattering spectrum of distributed sensing systems based on RBFN networks

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OPTIK 2013年第8期124卷 718-721页

作者： Zhang, Yanjun Fu, Guangwei Liu, Yin Bi, Weihong Li, Da Yanshan Univ Coll Informat Sci & Engn Qinhuangdao 066004 Peoples R China

In order to extract features for Brillouin scattering spectrum of distributed sensing systems with high accuracy, a novel fitting algorithm, using a hybrid algorithm based on particle swarm optimization algorithm and Levenberg-Marquardt algorithm to optimize the optimization process of radial basis function networks, is explanatorily proposed. Compared the proposed algorithm with traditional BP neural networks, the five times polynomial curve and piecewise cubic spline interpolation in fitting the simulative And experimental spectrum, respectively, the evaluation parameter is relatively better than other three algorithms under the same experiment with different pulse widths. The numerical and experimental results showed that modified RBFN networks have some referential roles, which can guarantee the accurate measurement of Brillouin scattering spectrum. (C) 2012 Elsevier GmbH. All rights reserved.

关键词： Distributed fiber sensing systems Brillouin scattering Neural networks Levenberg-Marquardt particle swarm optimization algorithm

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A New Variant Harmony Search algorithm for Unconstrained Numerical optimization Problems

A New Variant Harmony Search Algorithm for Unconstrained Num...

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2nd International Conference on Machine Design and Manufacturing Engineering (ICMDME)

作者： Xia, Honggang Wang, Qingzhou Shenyang Univ Informat Engn Coll Shenyang 110004 Peoples R China Northeastern Univ Informat & Sci Coll Shenyang 110004 Peoples R China Informat Technol Dept Liaoyang Petrifact Liaoyang 111003 Peoples R China

ISBN: (纸本)9783037857816

Harmony search (HS) algorithm is a good meta-heuristic intelligent optimization method and it does depend on imitating the music improvisation process to generate a perfect state of harmony. However, intelligent optimization methods is easily trapped into local optimal, HS is no exception. In order to modify the optimization performance of HS, a new variant of harmony search algorithm is proposed in this paper. The variant integrate the position updating of the particle swarm optimization algorithm with pitch adjustment operation, and dynamically adjust the key parameter pitch adjusting rate (PAR) and bandwidth (BW). Several standard benchmarks are to be tested. The numerical results demonstrated the superiority of the proposed method to the HS and recently developed variants (HIS, and GHS).

关键词： Harmony search algorithm position updating particle swarm optimization algorithm adjust

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Fatigue Life Prognosis of Concrete Using Extended Grey Markov Model

Fatigue Life Prognosis of Concrete Using Extended Grey Marko...

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International Conference on Applied Mechanics and Materials (ICAMM 2012)

作者： Zhu, Chao Yang, Wenbing Wang, Huilong Shaoxing Univ Sch Yuanpei Dept Econ & Management Shaoxing Peoples R China

ISBN: (纸本)9783037855911

The fatigue life prognosis of concrete is becoming more important with the development for demanding higher quality and safety in industrial. However, effective methods for this prognosis are still in need now, due to the feature of concrete. This paper proposes the extended grey Markov model (i.e. EGMM) for fatigue life prognosis of concrete. Firstly, the GM (1, 1, lambda(1), lambda(2)) (i.e. EGM) is proposed by integrating the particle swarm optimization algorithm (PSOA) with GM (1, 1) (i.e. GM). Then the Markov model is integrated with EGM and a novel prognosis method of the extended grey Markov model is proposed. The EGMM is used to combine the health states and transition probability. And a real case study is used to demonstrate the implementation and potential applications of the proposed fatigue life prognosis approach on concrete.

关键词： Prognosis grey model particle swarm optimization algorithm building materials fatigue

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Temperature Control Method for Water-Coal-Mixture Gasifier System Based on Fuzzy Control Rules Optimized by PSO algorithm

Temperature Control Method for Water-Coal-Mixture Gasifier S...

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2nd International Conference on Measurement, Information and Control (ICMIC)

作者： Zhou, Tianpei Xuzhou Coll Ind & Technol Dept Mech & Elect Engn Xuzhou 221140 Peoples R China China Univ Min & Technol Sch Informat Elect & Engn Xuzhou 221008 Peoples R China

ISBN: (纸本)9781479913909

There have many problems such as multi-interference factors, large delay and difficult to establish accurate mathematical model in temperature control system of water-coal-mixture gasifier. The gasifier temperature control is general realized by fuzzy controller in traditional method, however, the temperature control effect is not very good because the performance of fuzzy controller is affected by many factors. Considering that particle swarm optimization(PSO) algorithm has simple operation and fast convergence, the coding of fuzzy rules are completed by defining an equivalent probability matrix, the appropriate objective function is selected as particle fitness function. particles with higher fitness degree are obtained by iterative optimization, as the fuzzy control rule, which is applied to the gasifier temperature control. The results of application show the optimized control effect is much better than the original fuzzy controller in the rapidity despite the loss in the stability, to achieve optimal control.

关键词： particle swarm optimization algorithm Fuzzy control rules Temperature control Gasifier

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Aeroengine State Variable Modeling based on the PSO algorithm

Aeroengine State Variable Modeling based on the PSO Algorith...

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Chinese Automation Congress (CAC)

作者： Wang, Bin Shi, Yulin Wang, Xi Beihang Univ Dept Jet Prop Aerosp Control Lab Beijing 100191 Peoples R China

ISBN: (纸本)9781479903337

In this paper, a detailed research about aeroengine small perturbation State Variable Model (SVM) has been carried out. The small perturbation SVM was obtained by using partial derivative method and the particle swarm optimization (PSO) algorithm was selected to optimize parameter matrices. On the basis of comparison, the calculation results of the SVM have quite remarkable consistency with those results calculated by the nonlinear model. In order to better verify the accuracy and efficiency of this method, a real-time piecewise linear dynamic model (RPLDM) was constructed;and a transient simulation on sea-level condition was carried out. The results showed that the proposed approach to establishing the small perturbation SVM and the RPLDM was highly rated in validity and applicability.

关键词： aeroengine modeling state variable model particle swarm optimization algorithm real-time piecewise linear dynamic model

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Probabilistic Reactive Power optimization of Distribution Network Considering Stochastic Wind Speed and Load

Probabilistic Reactive Power Optimization of Distribution Ne...

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2nd International Conference on Applied Materials and Electronics Engineering (AMEE 2013)

作者： Chen Shuheng Chen Luan Chen Yong Univ Elect Sci & Technol China Chengdu 611731 Peoples R China

ISBN: (纸本)9783037856680

Based on the probabilistic loss model of distribution network and the improved hybrid particle swarm algorithm, a reactive power optimization algorithm is presented, which encompasses the effects of stochastic wind speed and load. Firstly, with the control vector dimension's length augmented and with the probabilistic loss method built, the reactive power optimization model is presented. Secondly, with the Niche operations embedded into the original PSO, an improved hybrid PSO algorithm is presented. Lastly, the corresponding software system program is developed in VC++ language and on basis of SQL SERVER platform. While this software system being supplied into a case, the experimental data have proved that this algorithm possesses more adaptability. At the same time, compared with the RTS algorithm, the calculating process is speeded.

关键词： Wind generation probabilistic model particle swarm optimization algorithm reactive power optimization uncertainty

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