宁夏电力Issue(5)：27-32,6.DOI:10.3969/j.issn.1672-3643.2025.05.004
基于数字映射的电力二次设备状态智能研判方法
Intelligent condition assessment method for secondary power equipment based on digital mapping
摘要
Abstract
Due to the complex digital mapping relationships within secondary power equipment and the dynamic influ-ence of external environmental factors,the equipment states present strong nonlinearity and uncertainty,making accurate condition assessment difficult.In this study,the covariance matrix is decomposed,and the cumulative contribution rate is calculated to determine the number of principal components.The original data are then projected onto a new coordinate system formed by the selected principal components to extract key features.By combining neural network algorithms,a mapping model from device states to digital space is constructed,thereby generating the corresponding state vector matrix.The autoregressive integrated moving average(ARIMA)model is further used to predict the future operating states of the equipment.Combining these predictions with the abnormality degree calculation results enables intelligent condition assessment.Experimental validation demonstrates that the proposed method achieves higher values of area under curve compared to conventional approaches,indicating superior accuracy and reliability in condition assessment of secondary power equipment.关键词
数字映射/电力设备/状态研判/神经网络/时间序列Key words
digital mapping/power equipment/condition assessment/neural network/time series分类
信息技术与安全科学引用本文复制引用
赵国伟,李志远,王玉财..基于数字映射的电力二次设备状态智能研判方法[J].宁夏电力,2025,(5):27-32,6.基金项目
国网宁夏电力有限公司科技项目(5229ND240002) （5229ND240002）
