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阶次分析是旋转体机械振动监测及故障诊断的最重要方法之一,因为转速的波动会使频谱图上基频以及各次谐波分量变得模糊。基于重采样原理的阶次分析是实现信号从等时采样到等角度采样的一种信号处理方法,它主要能解决因转速波动而产生的谐波分量重叠所带来的困难。本文主要通过对比基于LabVIEW编程语言的频谱分析和阶次比分析在研究变速旋转体振动信号中的优劣势,深入探讨实现阶次比分析的原理过程。 相似文献
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Two variants of systematic resampling (S-RS) are proposed to increase the diversity of particles and thereby improve the performance of particle filtering when it is utilized for detection in Bell Laboratories Layered Space-Time (BLAST) systems. In the first variant, Markov chain Monte Carlo transition is integrated in the S-RS procedure to increase the diversity of particles with large importance weights. In the second one, all particles are first partitioned into two sets according to their importance weights, and then a double S-RS is introduced to increase the diversity of particles with small importance weights. Simulation results show that both variants can improve the bit error performance efficiently compared with the standard S-RS with little increased complexity. 相似文献
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为了最大程度提升无线传感器网络(WSN)的覆盖范围并降低能耗,延长网络生命周期,提出了基于重采样技术和天牛须搜索的协同演化粒子群优化(RBASPSO)算法来优化WSN的覆盖控制问题。重采样技术平衡了粒子群算法的全局搜索能力和收敛速度,增加了粒子群整体多样性,防止算法过早收敛,加强粒子在搜索过程中跳出低质量谷底的能力; 天牛须搜索依靠个体的两个触角搜索其邻域,增强了粒子群中单个粒子的搜索能力。RBASPSO算法采用覆盖率和节点休眠率的加权作为优化WSN覆盖控制的目标函数,通过重采样技术和天牛须搜索的协同演化,既加强了单个粒子的搜索能力,又确保粒子群的多样性及活跃性,提升WSN覆盖性能。实验结果表明,RBASPSO算法不仅能有效处理复杂多峰问题; 而且可以有效提高WSN网络覆盖率,延长网络生命周期。 相似文献