Decision tree algorithm-based 220kV main transformer state assessment prediction method

• Main Authors: XIAO YINGTING, MA WEN, YANG DONGNING, ZHANG LINA, XU MIN, ZHAO ZHIYU, LI HUAFENG
• Format: Patent
• Language: Chinese; English
• Published: 22.09.2017
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a decision tree algorithm-based 220kV main transformer state assessment and prediction method. According to the method, online data monitoring, decision algorithm training and main transformer state assessment judgment are carried out; and various online monitoring data of 220KV main transformers are intensively fused and collected through data fusion by utilizing a decision algorithm technology, so as to form valuable data, so that powerful predicted data and measure support for 220KV main transformer state assessment, the safety and reliability of equipment are enhanced, and an improvement upon main transformer state assessment prediction is brought. 种基于决策树算法的220kV主变压器状态评估预测方法，采用在线监测数据、决策算法训练、主变状态评估与判定，通过数据融合，利用决策算法技术、把220KV主变各种在线监测数据集中融合，汇总形成有价值的数据，为220kV主变压器状态评估提供有力的预测数据及手段支撑，提升设备的安全可靠性，带来主变状态评估预测方式的进步。