摘要
航天电子装置的多余物检测对航天器安全可靠运行作用重大。目前微粒碰撞噪声检测(particle im-pact noise detection,PIND)是多余物检测中应用最普遍的方法,检测系统采用的驱动形式多为冲击和正弦振动。为了提高多余物检测的检出率和准确度,在PIND中引入随机振动,但这给多余物信号的特征分析带来困难。经验模态分解(empirical mode decomposition,EMD)和希尔伯特-黄变换(Hilbert-Huang transform,HHT)可适应非线性、非平稳信号的处理,同时具有不需预先知识的自适应处理能力,引入EMD和HHT方法用于多余物特征分析,以解决目前存在的困难。实验数据的仿真研究证明了该方法的有效性和优越性。
Detection of remainders in aerospace electronic equipment plays a significant role in the safety and reliability of a space system, and the particle impact noise detection （PIND） method is widely used to detect the remainders. Drive signals in the PIND system are mostly shock and sinusoidal waves. The random signal can be a better one for the PIND system to improve the inspection probability and the inspection accuracy. However, the random signal increases difficulties in analyzing the characteristics of the remainders. Therefore, an analysis method on the characteristics of remainders in aerospace electronic equipment based on the empirical mode de- composition （EMD） and the Hilbert-Huang transform （HHT） is proposed, and its validity and excellencies are finally proven.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2012年第10期2187-2192,共6页
Systems Engineering and Electronics
基金
国家自然科学基金(51077022)资助课题
关键词
航天地面设施
特征分析
希尔伯特-黄变换
航天电子装置
多余物检测
aerospace grounding requirement
characteristic analysis
Hilbert-Huang transform
aerospace electronic equipment
remainder detection
