关键词: 群诊模型, 关联预测, 时变模型, 径向基网络, 油田设备

Abstract: Some problems in diagnosis extent,depth and prediction of equipment in western oilfields were analyzed.The group diagnosis and correlative prediction models based on the modern methods were proposed.The qualitative diagnosis model was combined with the quantitative data to build an integrated diagnostic database,and a group diagnostic model was established.The group diagnostic model can be used to process and analyze the data of equipment group to solve the problem of diagnosis extent.The identifying model of time variation was built,on the basis of radial basis function neural network to solve the problem of diagnosis depth.The correlative prediction method was used to predict the maintenance periods based on parts recomposing method.The diagnosis and prediction systems for equipment group in the western oil fields were developed.

Key words: western oilfield of China, equipment diagnosis, group diagnosis model, correlative prediction, time variation model, radial basis function neural network