采用粒子群算法的自适应变步长随机共振研究

张仲海;王太勇;王多;林锦州;耿博

振动与冲击 ›› 2013, Vol. 32 ›› Issue (19) : 125-130.

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PDF(1802 KB)
振动与冲击 ›› 2013, Vol. 32 ›› Issue (19) : 125-130.
论文

采用粒子群算法的自适应变步长随机共振研究

  • 张仲海1,2,王太勇1,王多1,林锦州1,耿博1
作者信息 +

Research of self-adaptive step-changed stochastic resonance using particle swarm optimization

  • Zhonghai Zhang1,2, Taiyong Wang1, Duo Wang1, Jinzhou Lin1,Bo Geng1
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文章历史 +

摘要

针对传统的自适应随机共振只能实现单参数优化和变步长随机共振计算步长选取困难的缺陷,提出一种基于粒子群优化算法(Particle Swarm Optimization, PSO)的自适应变步长随机共振方法,实现了变步长随机共振最优输出的自适应求解。该方法以双稳系统的输出信噪比作为粒子群算法的适应度函数,通过变步长随机共振系统的结构参数和计算步长的自适应同步选取,能够最优地检测出大参数条件下的微弱信号。仿真数据和工程实际数据的分析表明,该方法简单易行,适用范围广,收敛速度快,能有效的检测出强噪声背景下的高频微弱信号,具有良好的工程应用前景。

Abstract

The traditional adaptive stochastic resonance (SR) can only achieve one-parameter optimization, and it is very difficult to select the calculation step of step-changed stochastic resonance (SCSR), a new adaptive SCSR based on particle swarm optimization (PSO), which can realize the adaptive solving of optimal output of SCSR, is proposed in this paper. The output signal to noise ratio of bi-stable system is determined as the fitness function of PSO algorithm, and the structure parameters and calculation step of SCSR are selected adaptively, as a result, the weak signal which under the conditions of large parameter can be detected optimally. The proposed method is applied to simulation data and vibration signals measured on defective bearings with inner race fault. The results shows that the proposed method has advantages of simplicity, fast convergence speed and wide range of applications, and possesses a good prospect of engineering application.



关键词

变步长随机共振 / 粒子群算法 / 自适应 / 多参数同步优化

Key words

step-changed stochastic resonance (SCSR) / particle swarm optimization (PSO) / self-adaptive / multi-parameter optimization

引用本文

导出引用
张仲海;王太勇;王多;林锦州;耿博. 采用粒子群算法的自适应变步长随机共振研究[J]. 振动与冲击, 2013, 32(19): 125-130
Zhonghai Zhang;Taiyong Wang;Duo Wang;Jinzhou Lin;Bo Geng. Research of self-adaptive step-changed stochastic resonance using particle swarm optimization[J]. Journal of Vibration and Shock, 2013, 32(19): 125-130

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