一种用于信号重建和错误补偿的降噪方法,用于在持续的外部干扰下对磁悬浮陀螺仪进行错误补偿
Di Liu1, Zhen Shi1, Ziyi Yang1
1School of Geology Engineering and Geomatics, Chang'an University, 126 Yanta Road, Xi'an 710054, China.
Sensors (Basel, Switzerland)
|January 8, 2025
概括
这项研究引入了一种新的降噪方法,用于马格莱夫陀螺旋旋转器信号,显著提高了近视角测量准确度. 该技术有效地抑制了环境干扰,提高了陀螺仪的性能.
科学领域:
- 控制工程 控制工程 控制工程
- 信号处理 信号处理
- 地理空间工程是什么?
背景情况:
- 磁悬浮陀螺仪容易受到环境干扰的噪音干扰,影响测量准确度.
- 准确的近视线测量对于各种应用,包括导航和勘测至关重要.
研究的目的:
- 开发和验证磁悬浮陀螺仪旋转器信号的强大的降噪方法.
- 为了提高陀螺仪扭矩传感器的自行方向测量精度.
主要方法:
- 适应性粒子优化变量模态分解 (APSO-VMD) 用于信号分解.
- 用于过和重建无效信号的多尺度顺序.
- 经验模式分解 (EMD) 用于趋势术语错误补偿.
主要成果:
- 提出的方法有效地将补偿信号的平均标准偏差降低了46.10%.
- 北方方位的平均测量误差减少了45.63%.
- 在现场实验中,与其他四种算法相比,证明了优越的降噪性能.
结论:
- 集成的APSO-VMD和趋势期补偿方法显著提高了磁悬浮陀螺仪的方向准确性.
- 这种方法提供了有效的噪音抑制,防止持续的外部环境干扰.
- 通过现场实验验证,该方法为改善陀螺仪传感器性能提供了可靠的解决方案.
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