关键词: 电子系统, 监测数据优化, 特征空间样本选择, 核主成分分析, 分布估计算法

Abstract: To solve the redundancy and high-dimensional problem of the electronic system condition monitoring data, a monitoring data optimization algorithm that combined the sample optimization and features optimization was put forward. Firstly, monitoring data samples were optimized by feature space sample selection algorithm, and the most representative samples were found; then monitoring data characteristics were optimized by KPCA-EDA algorithm after the sample optimization. More recognition information was retained on guarantee that the feature information was enough. Finally, a filter circuit was taken as an example to simulate, and the result shows that this method is effective.

Key words: electronic system, monitoring data optimization, feature space sample selection, Kernel Principal Component Analysis (KPCA), Estimation of Distribution Algorithms (EDA）