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miller5356金虫 (小有名气)
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[求助]
基于改进离散粒子群算法的传感器优化配置
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baiyuefei
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【答案】应助回帖
★ ★ ★ ★ ★
感谢参与，应助指数 +1
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
感谢参与，应助指数 +1
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
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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 |
2楼2016-03-30 12:51:52
baiyuefei
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3楼2016-03-30 12:52:06
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