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ADCS-ELM算法滚动轴承故障诊断 被引量:6
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作者 余萍 曹洁 黄开杰 《传感器与微系统》 CSCD 2020年第5期129-132,136,共5页
针对滚动轴承的故障信息难以从复杂噪声背景下的非平稳振动信号中提取且传统方法分类精度低等问题,提出一种基于集合经验模态分解(EEMD)能量特征提取和优化极限学习机神经网络(ADCS-ELM)分类诊断相结合的轴承故障诊断方法。利用EEMD对... 针对滚动轴承的故障信息难以从复杂噪声背景下的非平稳振动信号中提取且传统方法分类精度低等问题,提出一种基于集合经验模态分解(EEMD)能量特征提取和优化极限学习机神经网络(ADCS-ELM)分类诊断相结合的轴承故障诊断方法。利用EEMD对非线性和非平稳信号的自适应分解能力,将待检测轴承故障信号分解为包含故障特征的固有模态函数集(IMFs),并提取能量特征向量;利用自适应动态搜索步长改进布谷鸟搜索算法(ADCS)优化ELM网络连接权值和隐层阈值;将提取的故障特征向量用于训练极限学习机神经网络,得到最优权值和阈值;利用ADCS-ELM进行轴承故障诊断实验。实验结果表明:与BP,LVQ和ELM网络轴承故障诊断方法相比较,所提方法能够有效提高故障识别准确率,并且具有更快的计算速度。 展开更多
关键词 合经验模态分解 固有模态函数集 极限学习机 布谷鸟搜索算法 故障诊断 滚动轴承
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Reservoir detection based on EMD and correlation dimension 被引量:3
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作者 文晓涛 贺振华 黄德济 《Applied Geophysics》 SCIE CSCD 2009年第1期70-76,103,104,共9页
In hydrocarbon reservoirs, seismic waveforms become complex and the correlation dimension becomes smaller. Seismic waves are signals with a definite frequency bandwidth and the waveform is affected by all the frequenc... In hydrocarbon reservoirs, seismic waveforms become complex and the correlation dimension becomes smaller. Seismic waves are signals with a definite frequency bandwidth and the waveform is affected by all the frequency components in the band. The results will not define the reservoir well if we calculate correlation dimension directly. In this paper, we present a method that integrates empirical mode decomposition (EMD) and correlation dimension. EMD is used to decompose the seismic waves and calculate the correlation dimension of every intrinsic mode function (IMF) component of the decomposed wave. Comparing the results with reservoirs identified by known wells, the most effective IMF is chosen and used to predict the reservoir. The method is applied in the Triassic Zhongyou group in the XX area of the Tahe oil field with quite good results. 展开更多
关键词 empirical mode decomposition correlation dimension intrinsic mode function RESERVOIR
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