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miller5356

金虫 (小有名气)

[求助] 基于改进离散粒子群算法的传感器优化配置

作者:
马羚,李海军,王成刚,李国峰
文题:
基于改进离散粒子群算法的传感器优化配置
期刊名,年份,卷(期),起止页码:
电子学报, 2015, 43(12)
收录信息:
求助 EI 收录信息

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baiyuefei

版主 (文学泰斗)

风雪

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miller5356: 金币+5, ★★★★★最佳答案 2016-03-30 17:45:48
lazy锦溪: LS-EPI+1, 感谢应助! 2016-03-30 17:51:21
Accession number:


20160501878231






Title:

Optimal sensor placement based on improved discrete PSO algorithm






Authors:

Ma, Ling1 ; Li, Hai-Jun1 ; Wang, Cheng-Gang2 ; Li, Guo-Feng3





Author affiliation:

1Department of Weapon Science and Technology, Naval Aeronautical and Astronautical University, Yantai; Shandong, China






2Department of Basic Experiment, Naval Aeronautical and Astronautical University, Yantai; Shandong, China






3Brigade of Missile Technique, PLA No.92154 Troops, Yantai; Shandong, China






Source title:

Tien Tzu Hsueh Pao/Acta Electronica Sinica






Abbreviated source title:

Tien Tzu Hsueh Pao






Volume:

43






Issue:

12






Issue date:

December 1, 2015






Publication year:

2015






Pages:

2408-2413






Language:

Chinese






ISSN:

03722112






CODEN:

TTHPAG






Document type:

Journal article (JA)






Publisher:

Chinese Institute of Electronics






Abstract:

Optimal sensor placement is foundation and guarantee for design of (Prognostics and Health Management, PHM) system for avionics. The fault-sensor dependency matrix is improved which considers the failure probability of the sensors firstly. Based on this, the constraint optimization model is established and the improved discrete PSO algorithm is used to solve the problem. The algorithm designs the fitness function by the characteristics of optimal sensor placement, and the inertia weight is adjusted adaptively based on the swarm's premature degree which can avoid algorithm limits to local extremum and accelerate the convergence speed. The simulation examples demonstrate that the proposed method is effective, and the optimization results meet all the testability index requirements of system, and it can provide effective direction to the optimal sensor placement of PHM system for avionics. © 2015, Chinese Institute of Electronics. All right reserved.






Number of references:

9






Main heading:

Optimization






Controlled terms:

Algorithms - Avionics - Constrained optimization - Particle swarm optimization (PSO) - Testing






Uncontrolled terms:

Constraint optimizations - Failure Probability - Fitness functions - Optimal sensor placement - Prognostics and health managements - PSO algorithms - Simulation example - Testability






Classification code:

715 Electronic Equipment, General Purpose and Industrial - 921.5 Optimization Techniques - 961 Systems Science





DOI:

10.3969/j.issn.0372-2112.2015.12.010






Database:

Compendex
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baiyuefei

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风雪

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Accession number:


20160501878231
3楼2016-03-30 12:52:06
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