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Heat Transfer Model And Applied Research Of Blackbody Cavity Liquid Steel Continuous Temperature Measurement Sensor

Posted on:2012-09-16Degree:MasterType:Thesis
Country:ChinaCandidate:Y X LiuFull Text:PDF
GTID:2231330395958157Subject:Detection Technology and Automation
Abstract/Summary:PDF Full Text Request
Accurately measuring the tundish temperature is an important part in the process of continuous casting. Currently, blackbody cavity liquid steel continuous temperature measurement sensor is widely used in tundish temperature measurement, but the structure of the sensor makes there is a certain lag in the course of temperature measurement. For the purpose of compensating the dynamic temperature measurement error introduced by the lag, this paper establishes the heat transfer model of blackbody cavity molten steel continual temperature measurement sensor, researches its dynamic characteristic through the heat transfer model, then, establishes the relationship of hot response function and the dynamic temperature measurement influencing factors and applies it in the dynamic temperature measurement compensation.This paper first establishes a three-dimensional unsteady heat transfer mechanism model of the sensor based on the heat transfer process, and according to the heat transfer differential equations and boundary conditions, establishes a finite element heat transfer model of continuous temperature sensor with finite element analysis method. Then, conducts the research to its accuracy and based on physical parameters of the sensor changing with temperature, optimizes the model with the ANSYS optimization method and then establishes relationship of physical parameters and temperature. By verification with dynamic temperature data of Anshan Iron and Steel Group Company, the optimized simulation results error is less than5℃, the model correctly.In the numerical simulation applications, this paper based on the optimization model, selects first-order function as the basic form of thermal response function, finds the relationship of different parameters of response function and different temperature measurement factors through analysis dynamic temperature measurement influencing factors, and establishes their function relationship through the orthogonal test and determines the parameters scope. Afterward, applies it in the field data estimate compensation. In the situation of dynamic temperature measurement error smaller than7degree, the average response time enhances from193s to50s, which achieves the target set by the dynamic temperature compensation. It plays an important role of reducing the impact of temperature measurement to the slab quality.
Keywords/Search Tags:temperature field analysis, dynamic temperature, parameter optimization, thermal response function, genetic algorithms, estimate compensation
PDF Full Text Request
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