四川电力技术
四川電力技術
사천전력기술
SICHUAN ELECTRIC POWER TECHNOLOGY
2013年
6期
75-77
,共3页
支持向量机%设备缺陷管理%发生率%预测
支持嚮量機%設備缺陷管理%髮生率%預測
지지향량궤%설비결함관리%발생솔%예측
support vector machine%management of equipment defect%occurrence rate%prediction
缺陷预测是设备管理中的重要内容。变电设备由于运行环境复杂，设备缺陷发生的随机性较大。基于支持向量机理论，采用数据挖掘技术，通过对设备运行环境和缺陷发生率的统计分析，利用支持向量机建立设备缺陷平均发生率与设备运行环境的回归函数，回归结果与实际情况较为吻合。对给定运行环境下设备缺陷平均发生率进行预测，预测误差小于10％，对设备的运行维护管理具有较高的参考价值。
缺陷預測是設備管理中的重要內容。變電設備由于運行環境複雜，設備缺陷髮生的隨機性較大。基于支持嚮量機理論，採用數據挖掘技術，通過對設備運行環境和缺陷髮生率的統計分析，利用支持嚮量機建立設備缺陷平均髮生率與設備運行環境的迴歸函數，迴歸結果與實際情況較為吻閤。對給定運行環境下設備缺陷平均髮生率進行預測，預測誤差小于10％，對設備的運行維護管理具有較高的參攷價值。
결함예측시설비관리중적중요내용。변전설비유우운행배경복잡，설비결함발생적수궤성교대。기우지지향량궤이론，채용수거알굴기술，통과대설비운행배경화결함발생솔적통계분석，이용지지향량궤건립설비결함평균발생솔여설비운행배경적회귀함수，회귀결과여실제정황교위문합。대급정운행배경하설비결함평균발생솔진행예측，예측오차소우10％，대설비적운행유호관리구유교고적삼고개치。
Defect prediction is the important content of the equipment management .Due to the complex operating condition of transmission and distribution equipment , the randomness of the occurrence of defects is high .Based on the theory of support vector machine , the operating condition and defect occurrence rate of the equipment are analysis using data mining technology , and the regression functions for the average defect occurrence rate and the operating condition are established using support vector machine , whose regression results coincide with the actual situation .The prediction for the average occurrence rate of e-quipment defects under the given operating condition is carried out and the prediction error is less than 10%, which is of valu-able reference for the management of the operation and maintenance of the equipment .
