RV(rotate vector)减速器是现代智能装备中关键传动机构之一，其运动参数的检测信号噪声成分较高，影响了装备的运行精度和稳定性，本文提出了一种以经验模态分解(Empirical Mode Decomposition, EMD)为基础的信号降噪方法，有效提取了RV减速器运动参数的准确信号。该方法采用连续均方误差(Consecutive Mean Square Error, CMSE)和l2范数两个指标将EMD分解得到的固有模态函数(Intrinsic Mode Function, IMF)区分为噪声IMF、噪声与信息相混合IMF、信息IMF三个部分，采用不同策略对这3部分IMF进行处理并结合部分重构(Part Reconstruction, PR)策略实现了信号的降噪处理。采用本文提出的降噪方法对RV40E减速器的检测信号进行处理，降噪后的信号信噪比得到明显改善，验证了该降噪方法的有效性。
Abstract
Rotate vector（RV）reducer is one of key transmission mechanisms in modern intelligent equipment, proportion of noise in its measurement signal of kinetic parameters is strong，which affects the operation accuracy and stability of equipment. This paper proposes a signal-denoising approach based on EMD (Empirical Mode Decomposition), and this approach can extract accurate kinetic-parameter-signals of RV reducer effectively. In the approach, the IMFs (Intrinsic Mode Function) derived from EMD are separated into 3 parts, noise IMFs, IMFs mixed with noise and information, information IMFs, with 2 indexes, CMSE (Consecutive Mean Square Error) and l2 norm. The different processing strategics are applied in 3 parts IMF, and the combination with PR (Part Reconstruction) fulfills the process of denoising. The denoising approach presented in this paper is used in the denoising process for the torque signals of RV40E reducer, the SNRs of denoised signals are improved observably, and the effectiveness of the approach is validated.
Key words: empirical mode decomposition（EMD）; RV reducer; consecutive mean square error(CMSE); l2-norm; signal denoising
关键词
EMD /
RV减速器 /
CMSE /
l2范数 /
信号降噪
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Key words
empirical mode decomposition（EMD）
/
RV reducer /
consecutive mean square error(CMSE) /
l2-norm /
signal denoising
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