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Multi-scale prediction of MEMS gyroscope random drift based on EMD-SVR 被引量:1
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作者 HE Jia-ning ZHONG Ying LI Xing-fei 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2020年第3期290-296,共7页
To improve the prediction accuracy of micro-electromechanical systems(MEMS)gyroscope random drift series,a multi-scale prediction model based on empirical mode decomposition(EMD)and support vector regression(SVR)is pr... To improve the prediction accuracy of micro-electromechanical systems(MEMS)gyroscope random drift series,a multi-scale prediction model based on empirical mode decomposition(EMD)and support vector regression(SVR)is proposed.Firstly,EMD is employed to decompose the raw drift series into a finite number of intrinsic mode functions(IMFs)with the frequency descending successively.Secondly,according to the time-frequency characteristic of each IMF,the corresponding SVR prediction model is established based on phase space reconstruction.Finally,the prediction results are obtained by adding up the prediction results of all IMFs with equal weight.The experimental results demonstrate the validity of the proposed model in random drift prediction of MEMS gyroscope.Compared with a single SVR model,the proposed model has higher prediction precision,which can provide the basis for drift error compensation of MEMS gyroscope. 展开更多
关键词 random drift MEMS gyroscope empirical mode decomposition(EMD) support vector regression(SVR) phase space reconstruction multi-scale prediction
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基于改进MED-SSD的齿轮箱复合故障诊断方法 被引量:7
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作者 周杰 王云艺 +2 位作者 陈传海 王立鼎 刘阔 《吉林大学学报(工学版)》 EI CAS CSCD 北大核心 2022年第2期450-457,共8页
针对齿轮箱在强噪声环境下复合故障信号微弱、故障特征难以提取等问题,本文提出了一种改进的最小熵反褶积(MED)与奇异谱分解(SSD)结合的方法。首先,构建边际功率谱峰度指数(MPSK),利用MPSK对MED进行参数优化;为弥补SSD的不足,将改进的ME... 针对齿轮箱在强噪声环境下复合故障信号微弱、故障特征难以提取等问题,本文提出了一种改进的最小熵反褶积(MED)与奇异谱分解(SSD)结合的方法。首先,构建边际功率谱峰度指数(MPSK),利用MPSK对MED进行参数优化;为弥补SSD的不足,将改进的MED作为SSD的前置滤波器;然后利用相关系数分析法选择有意义的奇异谱分量(SSC);最后对信号进行频谱分析,确定具体的故障模式。采用仿真信号与齿轮箱试验台的复合故障信号对所提方法进行了应用,验证了方法的有效性和优越性。 展开更多
关键词 奇异谱分解 最小熵反褶积 原子搜索优化算法 模态分量重构 复合故障
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