| 黄国峰,庄学彬,谢礼伟,曾小慧.基于 CEEMDAN-WP-SG 的 MEMS 陀螺仪去噪算法[J].电子测量与仪器学报,2022,36(4):106-113 |
| 基于 CEEMDAN-WP-SG 的 MEMS 陀螺仪去噪算法 |
| MEMS gyroscope denoising algorithm based on CEEMDAN-WP-SG |
| |
| DOI： |
| 中文关键词: MEMS 陀螺仪 自适应噪声完备经验模态分解 小波包去噪 多尺度排列熵 马氏距离 Savitzky-Golay 滤波 |
| 英文关键词:MEMS gyroscope complete ensemble empirical mode decomposition with adaptive noise wavelet packet denoising multiscale permutation entropy Mahalanobis distance Savitzky-Golay filter |
| 基金项目: |
|
|
|
|
| 摘要点击次数: 763 |
| 全文下载次数: 862 |
| 中文摘要: |
| 为了减小 MEMS 陀螺仪随机误差,提出了一种新的去噪算法。 该算法首先通过自适应噪声完备经验模态分解
(CEEMDAN)将原始数据分解为多个本征模态函数(IMF),并根据多尺度排列熵与马氏距离将 IMF 分为噪声 IMF、混叠 IMF 和
信号 IMF;其次对噪声 IMF 用小波包(WP)去噪,对混叠 IMF 用 Savitzky-Golay 滤波器(SG)去噪;最后,把处理后的 IMF 和信号
IMF 进行重构,得到去噪后的信号。 通过所提方法对 Bumps 信号进行实验分析,去噪后信号从 6 dB 提高至 17 dB,均方误差降
低 71. 9%;对实测陀螺仪静态数据进行分析,实验结果证明去噪后信号的角度随机游走降低 31. 5%,表明该方法能显著提高
MEMS 陀螺仪的精度。 |
| 英文摘要: |
| A new denoising algorithm is proposed aiming to decrease the random error of MEMS gyroscope. Firstly, the original data is
decomposed into multiple intrinsic mode functions ( IMFs) using complete ensemble empirical mode decomposition with adaptive noise
(CEEMDAN). Then the IMFs are divided into noise IMF, mixed IMF, and signal IMF according to multi-scale permutation entropy
with Mahalanobis distance. Next, the noise IMF is denoised by wavelet packet (WP) and the mixed IMF is denoised by Savitzky-Golay
filter (SG). Finally, the denoised signal is obtained via reconstructing the processed IMF and the signal IMF. The bumps signal is
increased from 6 dB to 17 dB, and the mean square error is reduced by 71. 9% after denoising through the proposed method. The angular
random walk of the denoised signal is reduced by 31. 5% in the experimental analysis of the measured gyroscope static data, which
illustrates that the proposed method can predominantly improve the accuracy of MEMS gyroscope accuracy. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
|
|
