摘要
Abstract
Condition monitoring based on electronic system as the research background,the traditional Kernel Principal Component Analysis (Kernel Principal Component Analysis,KPCA)do in the process of condition monitoring data feature dimension reduction process,makes the circuit state data at the same time of eliminating redundant information,as well as the corresponding calculation model algorithm greatly reduces computation steps,but KPCA method of dimension reduction data processing for the contribution rate of the data sample inadequacies in the ability to recognize,though achieved the pur-pose of dimension reduction,but information on the characteristics of the sample data retention capability shortcomings.This article USES the method of Empirical Mode Decomposition (Empirical Mode Decomposition,the EMD)was carried out on the output signal as sample data collection and processing,design based on Fisher criterion of state information recognition a-bility analysis,the Estimation of Distribution Algorithms (population algorithm,referred to as EDA)to improve the KPCA analysis research,through the data processing,maximum retention state master information,make the circuit system de-crease experimental error in the process of condition monitoring,fault prediction to lay the foundation for the follow-up.关键词
KPCA/EDA/Fisher准则/EMD/信息识别Key words
KPCA/EDA/fisher criterion/EMD/information identification分类
信息技术与安全科学
