基于静电互相关灵敏度加权的气路碎片监测

由于静电传感器阵列（ESA）安装位置及电极数目受到工作环境限制，导致航空发动机故障预测与健康管理（PHM）系统的线性独立测量信息数较少。针对此问题，提出了一种基于静电互相关（CC）灵敏度加权的气路碎片监测方法，在同一电极数目的条件下利用互相关聚焦原理有效增加了能够表征不同敏感区域的测量信息。在此基础上设计了8电极ESA，建立了不同电极对的互相关灵敏度分布，并以获取的16个相关速度值对其进行加权计算，计算结果反映了带电碎片的速度和位置信息。带式静电实验装置和颗粒落体实验装置的实验结果验证了所提方法的有效性，对单颗粒与多颗粒的监测结果和实际分布的平均相关系数分别达到了0.668与0.652，提高了PHM系统的监测信息量和稳定性。 

Electrostatic cross-correlation sensitivity weighting based gas path debris monitoring

Due to the limit of the installation location and the electrode number of the electrostatic sensor array (ESA), the linear independent measurement information of the aeroengine fault prognostics and health management (PHM) system is rare. Aimed at this problem, this paper proposes an electrostatic cross-correlation (CC) sensitivity weighting based exhaust debris monitoring method. With the same electrode number, the CC focus method is applied to effectively enhance the number of measurement information that can characterize different sensitive regions. On this basis, the 8-electrode ESA is designed, and the CC sensitivity distribution of different electrode pairs is established and weighted by 16 correlation velocities. The results can reflect the velocity and location information of charged debris. The effectiveness of the method is validated by experiment results of the belt-style electrostatic induction experimental facility and the vertical gravity experimental device. The average correlation coefficients between the monitoring results of single particles and multiple particles and the actual distribution reached 0.668 and 0.652, respectively, which enhanced monitor information and stability of PHM system.