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Frequency modulated weak signal detection based on stochastic resonance and genetic algorithm 被引量:17
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作者 XING Hongyan LU Chunxia ZHANG Qiang 《Instrumentation》 2016年第1期41-49,共9页
Stochastic resonance system is subject to the restriction of small frequency parameter in weak signal detection,in order to solve this problem,a frequency modulated weak signal detection method based on stochastic res... Stochastic resonance system is subject to the restriction of small frequency parameter in weak signal detection,in order to solve this problem,a frequency modulated weak signal detection method based on stochastic resonance and genetic algorithm is presented in this paper. The frequency limit of stochastic resonance is eliminated by introducing carrier signal,which is multiplied with the measured signal to be injected in the stochastic resonance system,meanwhile,using genetic algorithm to optimize the carrier signal frequency,which determine the generated difference-frequency signal in the lowfrequency range,so as to achieve the stochastic resonance weak signal detection. Results showthat the proposed method is feasible and effective,which can significantly improve the output SNR of stochastic resonance,in addition,the system has the better self-adaptability,according to the operation result and output phenomenon,the unknown frequency of the signal to be measured can be obtained,so as to realize the weak signal detection of arbitrary frequency. 展开更多
关键词 stochastic resonance two-dimension DUFFING OSCILLATOR frequency MODULATED GENETIC algorithm
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Adaptive stochastic resonance method for weak signal detection based on particle swarm optimization 被引量:7
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作者 XING Hongyan ZHANG Qiang LU Chunxia 《Instrumentation》 2015年第2期3-10,共8页
In order to solve the parameter adjustment problems of adaptive stochastic resonance system in the areas of weak signal detection,this article presents a new method to enhance the detection efficiency and availability... In order to solve the parameter adjustment problems of adaptive stochastic resonance system in the areas of weak signal detection,this article presents a new method to enhance the detection efficiency and availability in the system of two-dimensional Duffing based on particle swarm optimization.First,the influence of different parameters on the detection performance is analyzed respectively.The correlation between parameter adjustment and stochastic resonance effect is also discussed and converted to the problem of multi-parameter optimization.Second,the experiments including typical system and sea clutter data are conducted to verify the effect of the proposed method.Results show that the proposed method is highly effective to detect weak signal from chaotic background,and enhance the output SNR greatly. 展开更多
关键词 Adaptive stochastic resonance two-dimensional Duffing oscillator weak signal detection particle swarm optimization
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基于二维互补随机共振的轴承故障诊断方法研究 被引量:12
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作者 陆思良 苏云升 +3 位作者 赵吉文 何清波 刘方 刘永斌 《振动与冲击》 EI CSCD 北大核心 2018年第4期7-12,27,共7页
一维随机共振(One-Dimensional Stochastic Resonance,1DSR)被广泛用于轴承故障诊断中。针对传统1DSR对微弱信号的检测效果不够理想,输出信号噪声大,不能准确获得轴承故障特征频率(Fault Characteristic Frequency,FCF)等问题,提出一种... 一维随机共振(One-Dimensional Stochastic Resonance,1DSR)被广泛用于轴承故障诊断中。针对传统1DSR对微弱信号的检测效果不够理想,输出信号噪声大,不能准确获得轴承故障特征频率(Fault Characteristic Frequency,FCF)等问题,提出一种新的二维互补随机共振(Two-Dimensional Complementary Stochastic Resonance,2DCSR)方法并应用于轴承故障诊断。将采集到的轴承故障信号根据共振带位置进行带通滤波并解调,随后将解调信号对半分成两个子信号并输入2DCSR的两个输入端,利用输出信号的加权功率谱峭度(WPSK)指标对2DCSR系统参数进行自适应调节优化,得到最优的滤波输出信号及频谱,以识别轴承FCF并诊断轴承故障类型。数值仿真及实验结果表明,提出的方法可以有效地增强轴承FCF并提高轴承故障诊断效果。 展开更多
关键词 轴承故障诊断 二维互补随机共振 加权功率谱峭度 微弱信号检测
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基于随机共振与CEEMD的滚动轴承微弱故障诊断 被引量:1
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作者 张子轩 高丙朋 魏晓鹏 《组合机床与自动化加工技术》 北大核心 2023年第4期46-49,53,共5页
针对滚动轴承早期故障信号微弱且不易检测,导致故障诊断准确率低的问题,提出一种天鹰算法优化随机共振参数与互补集合经验模态分解(CEEMD)相结合的滚动轴承微弱故障诊断方法。首先,以信噪比为适应度函数,采用天鹰算法对随机共振参数进... 针对滚动轴承早期故障信号微弱且不易检测,导致故障诊断准确率低的问题,提出一种天鹰算法优化随机共振参数与互补集合经验模态分解(CEEMD)相结合的滚动轴承微弱故障诊断方法。首先,以信噪比为适应度函数,采用天鹰算法对随机共振参数进行自适应优化;其次,利用CEEMD将随机共振系统输出信号分解成一系列的本征模态分量(IMF),根据相关系数准则挑选最优的IMF,并对其进行包络谱分析,提取故障特征频率,实现故障诊断。试验结果表明,该方法避免了单纯使用随机共振检测准确率低的问题,故障诊断精确度更高,可靠性更好。 展开更多
关键词 故障诊断 天鹰算法 随机共振 信噪比 互补集合经验模态分解
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三重降噪的盲源分离抗干扰算法
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作者 曹越 张杭 +2 位作者 朱宏鹏 李睿思 曹静 《电讯技术》 北大核心 2022年第11期1656-1662,共7页
为了提高低信噪比条件下盲源分离的性能,提出了一种基于互补集合经验模态分解降噪、小波阈值降噪和随机共振降噪的三重降噪盲源分离抗干扰算法,分析了三种互补集合经验模态分解降噪与小波阈值降噪相结合的前降噪方案和扩频结合随机共振... 为了提高低信噪比条件下盲源分离的性能,提出了一种基于互补集合经验模态分解降噪、小波阈值降噪和随机共振降噪的三重降噪盲源分离抗干扰算法,分析了三种互补集合经验模态分解降噪与小波阈值降噪相结合的前降噪方案和扩频结合随机共振的后降噪方案,仿真讨论了所提算法的抗干扰性能。仿真结果表明,该算法在一定范围低信噪比条件下能够从受扰的混合信号中恢复出通信方的期望信号。 展开更多
关键词 盲源分离 抗干扰算法 互补集合经验模态 小波阈值降噪 随机共振
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