Measurement System In A Crude Oil Intermediate Repeater And It's Research On Soft Sensor

This project is from the Daqing Oil Field Measurement and TestTechnology Service Sub-company, its main task is to develop a crude oilintermediate repeater measurement system, improve estimation accuracy ofwater cut of crude oil by the application of soft-sensing technique and doresearches on the correlative theory and application.Soft-sensing technique provides a new approach to detect and controlprimary variables which are very difficult or impossible to be detected, hasimportant significance for production automation and quality control, and is oneof the most important research directions in the area of process control. Softsensor model is the core of soft-sensing technique, so it is necessary to researchfurther on.In this thesis, a crude oil intermediate repeater measurement system isdeveloped by a hybrid method that combines rapid-prototyping method, lifecycle method and object-oriented method. This system improves the workefficiency, measuring accuracy and management level of the crud oilintermediate repeater, establishes a foundation for greatly increasing theinformation level of the business management. The reason for inaccuracy of theoriginal estimate method is analyzed, and the idea for improving the estimateaccuracy by soft-sensing technique is proposed.The RBF neural network and Support Vector Machine used for regressionfrom the angles on empirical risk minimization and structural risk minimizationare analyzed, their mathematics expression, topology and main trainingalgorithms are expounded. Basing on the analysis and contrast between RBFneural network and Support Vector Machine, a Support Vectors-RBF neuralnetwork modeling method suitable for regression is proposed . Three soft sensormodels on water cut of crude oil is established based on RBFNN, SVM andSVs-RBFNN respectively. The simulation proves that SVs-RBFNN modelingmethod is superior to RBFNN modeling method in respect of generalizationperformance. The estimation effect of three models is greatly superior to theoriginal estimate method's, proving that soft-sensing technique is effective inimproving estimate accuracy of water cut of crude oil.In addition, the ideas and methods of dealing with actual problems in thisresearch work may supply references to reforming conventional industries byinformation and to improving detection and control level of industrialautomation.