连铸结晶器热、力在线检测技术及其应用基础研究
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摘要
结晶器是钢水凝固成型的核心设备,承担着导热、支撑、约束、润滑和脱模等作用,其内部的传热和摩擦直接决定铸坯的表面裂纹和漏钢,是实现高效连铸的关键因素。促进结晶器与铸坯间形成良好、稳定的传热和润滑条件,对钢水的初期凝固和摩擦行为进行在线调控,是保证铸坯质量的工艺要求,同时也是保障连铸机稳定运行、高效生产的前提。今后连铸技术的发展,将更加依赖于生产过程的自动控制水平,因此,开发结晶器热学、力学行为在线检测的新技术、新方法,研究结晶器在线监控的基础理论及其实现途径,对进一步丰富、发展结晶器过程的基础理论及其监控实践,均有重要意义。
本文以连铸结晶器为研究对象,围绕结晶器热、力在线监控技术的应用基础问题,对结晶器传热和摩擦行为的在线检测、数值计算及其应用方法进行研究。首先,基于结晶器液压振动装置,从理论分析和实验研究两方面入手,研究开发液压振动条件下摩擦力检测的理论模型和检测方法,设计相关的软件和硬件,开发适于现场应用的摩擦力在线检测系统;其次,以实测的结晶器摩擦力数据为基础,探索结晶器摩擦力的应用方法,开发针对摩擦力异常预报的模型及相应软件;最后,依据圆坯连铸结晶器实测的温度和热流数据,借助结晶器传热反问题模型,同时结合人工神经元网络技术,建立符合实际工况条件下的结晶器传热耦合计算模型,研究开发基于实测温度数据的结晶器传热计算方法。
基于板坯连铸结晶器液压振动装置,从分析结晶器振动的受力状态入手,建立了结晶器振动的受力模型,结合现场具体的检测条件和环境,确立摩擦力在线检测的理论基础和总体思路。运用粒子群优化方法,建立了振动系统空振参数的实时优化模型。针对本文研究的问题,研究了算法的具体实现及收敛性能,并对算法的优化结果进行了测试和评价。以上述工作为基础,自行设计、构建摩擦力检测系统的硬件和软件,开发出适于在线应用的摩擦力在线检测系统,实现了瞬态结晶器摩擦力的在线连续、稳定、自动检测。以现场实测的摩擦力数据为基础,研究了不同参数与振动方式下的摩擦力周期变化行为、特征值、负滑脱等参数的变化规律;同时分析了非正弦振动波形的特点,并对液压振动装置的工作特性及振动状态的评价方法进行了初步探讨。
基于功率法测得的板坯连铸结晶器摩擦力数据,结合生产现场的异常记录,对各类异常发生时摩擦力的反应及特征进行分析和统计,结果显示,摩擦力能够对漏钢、水口断裂及液位剧烈波动等异常作出反应,其均方根在0.8～4kN范围内变化。以此为基础,采用人工神经元网络技术,并对摩擦力信号的典型特征进行模式识别,建立了摩擦力异常预报模型,开发出摩擦力异常预报软件。对应连铸现场的异常记录,利用软件对各类结晶器异常进行离线预报,结果表明:软件能够对结晶器液位波动、漏钢、水口断裂及其他异常做出预报,并具有一定的提前量,运行速度满足在线预报的要求。
基于圆坯连铸结晶器温度和热流在线实测数据,开发针对实测数据的结晶器传热计算方法。利用传热反问题模型模拟实际条件下结晶器内部的传热行为,同时采用神经元网络求解结晶器传热反问题,建立了传热反问题—神经网—正问题的结晶器传热计算耦合模型。利用模型对在线检测的连续瞬时数据进行计算,表明将神经元网络与传热数值计算结合的方法可用于结晶器传热计算,能够真实反映圆坯结晶器传热的非均匀特性,计算的精度与速度基本满足在线实时计算的要求。正常工况下,在工艺参数稳定时,圆坯周向的局部热流和坯壳厚度并不恒定,周向导热决定坯壳的厚度分布,结晶器热流与坯壳厚度沿周向呈不均匀分布。
The mould is the core instrument for primary cooling and slab forming of liquid steel, and it takes effect as heat transfer, support, restriction, lubrication and demould during continuous casting (CC). The interior heat transfer and friction of mould have close relationship with the surface defects and breakout, which is very important for the effectively continuous casting. Aiming to control and adjust the initial solidification and frictional behavior online, it is necessary to ensure the conditions of stable heat transfer and lubrication, which is not only the requirement of strand quality, but also the precondition for stable and high efficient production. In the future, the development of continuous casting technology will more strongly depend on the automatic control during producing process. Therefore, it is urgently needed to develop new technologies for online measurement of thermal and mechanical behaviors in continuous casting mould, which is very important in both fundamental study and practical application. Furthermore, investigating on mould measurement methods and their applications, will play a significant role in further understanding of basic theory and monitoring practice for mould process.
In this dissertation, fundamental studies of mould thermo-mechanical monitoring technologies and their applications are discussed, especially, the online measurement method of mould friction, as well as the numerical simulation of heat transfer and their applications. Based on the slab caster equipped with hydraulic oscillators, the theoretical model, measurement method and monitoring system of mould friction are investigated. In addition, according to the mould friction data measured on slab caster, the application method of mould friction is studied, and the prediction model and software for mould abnormalities are developed. In the last chapter of this dissertation, the calculation method, which combines the online measurement data of mould temperature and heat flux and numerical simulation, is investigated by using the inverse heat transfer model and neural network for the round billet continuous casting.
Through theorecally analyzing the loading states during mould oscillation driven by the hydraulic units, the loading model is built and the theory foundation and overall measurement method are established for mould friction monitor in CC. The real-time calculation and optimization model of empty oscillating parameters is built by particle swarm optimization (PSO). The implementation and convergence performance of PSO algorithm are discussed, and the optimized results are also analyzed and evaluated. Based on the above work, both hardware and software for mould friction measurement are designed. The measurement tests show that the system is suitable for monitoring mould friction, and realizes the online detection of transient mould friction continuously, stably, and automatically. In the basis of the mould friction data measured, the periodical variations and characteristic values of mould friction, as well as negative strip parameters are discussed, and the characteristics of non-sinusoidal waveforms are also studied. In addition, by using the measurement data of displacement and cylinder force, the oscillation service state of hydraulic oscillators and its evaluation methods are investigated.
According to the abnormal records of steel plant, mould friction measured on slab caster by power-method is used to investigate its response to abnormalities in continuous casting. The results show that mould friction can respond to most abnormalities such as breakout, submerged entry nozzle broken, and acute fluctuation of mould level. The root mean square of mould friction ranges from 0.8 to 4 kN before or during the abnormalities. The prediction model for mould friction abnormalities has been built by using artificial neural network models in combination with two pattern recognition algorithms. A set of software to predict the mould friction abnormalities in CC has been developed. The results of simulation prediction for online measurement mould friction data are found to be basically consistent with those collected from the abnormal records of steel plant, such as breakout, submerged entry nozzle broken and acute mould level fluctuations. In some cases, it can make prediction several minutes earlier than the alarm given by temperature breakout detection system. The proposed method can make the system respond fast enough in real time plant prediction, and render sufficient time for online prediction and taking operations against abnormalities.
Based on the measured data of temperature and heat flux during round billet continuous casting, the calculation method which combines the online measurement data and numerical simulation is investigated. The thermal behavior is analyzed by an inverse heat transfer model, and it reflects the real state of transient heat transfer of mould. In order to decrease the calculation time to meet the online monitor requirement, an artificial neural network model is developed to solve the inverse problem, and the IHTP/ANN/DHTP (inverse heat transfer problem, artificial neural network, and direct heat transfer problem) integrated method of thermal behavior analysis from experimental temperatures is developed. The results show that the neural network is faster for inverse model, and the calculation results by this method can correctly reflect the characteristics of non-uniform heat transfer. Also the calculation accuracy and speed meet basically the requirements of online calculation. Through calculation, it is found that although the operating conditions are stable, the shell thickness may be fluctuated. The shell thickness varies directly with the heat flux at fixed mould circumferential degrees. It is also found that the profile of shell thickness is non-uniform and similar to that of the heat flux along circumference direction.
本文以连铸结晶器为研究对象,围绕结晶器热、力在线监控技术的应用基础问题,对结晶器传热和摩擦行为的在线检测、数值计算及其应用方法进行研究。首先,基于结晶器液压振动装置,从理论分析和实验研究两方面入手,研究开发液压振动条件下摩擦力检测的理论模型和检测方法,设计相关的软件和硬件,开发适于现场应用的摩擦力在线检测系统;其次,以实测的结晶器摩擦力数据为基础,探索结晶器摩擦力的应用方法,开发针对摩擦力异常预报的模型及相应软件;最后,依据圆坯连铸结晶器实测的温度和热流数据,借助结晶器传热反问题模型,同时结合人工神经元网络技术,建立符合实际工况条件下的结晶器传热耦合计算模型,研究开发基于实测温度数据的结晶器传热计算方法。
基于板坯连铸结晶器液压振动装置,从分析结晶器振动的受力状态入手,建立了结晶器振动的受力模型,结合现场具体的检测条件和环境,确立摩擦力在线检测的理论基础和总体思路。运用粒子群优化方法,建立了振动系统空振参数的实时优化模型。针对本文研究的问题,研究了算法的具体实现及收敛性能,并对算法的优化结果进行了测试和评价。以上述工作为基础,自行设计、构建摩擦力检测系统的硬件和软件,开发出适于在线应用的摩擦力在线检测系统,实现了瞬态结晶器摩擦力的在线连续、稳定、自动检测。以现场实测的摩擦力数据为基础,研究了不同参数与振动方式下的摩擦力周期变化行为、特征值、负滑脱等参数的变化规律;同时分析了非正弦振动波形的特点,并对液压振动装置的工作特性及振动状态的评价方法进行了初步探讨。
基于功率法测得的板坯连铸结晶器摩擦力数据,结合生产现场的异常记录,对各类异常发生时摩擦力的反应及特征进行分析和统计,结果显示,摩擦力能够对漏钢、水口断裂及液位剧烈波动等异常作出反应,其均方根在0.8～4kN范围内变化。以此为基础,采用人工神经元网络技术,并对摩擦力信号的典型特征进行模式识别,建立了摩擦力异常预报模型,开发出摩擦力异常预报软件。对应连铸现场的异常记录,利用软件对各类结晶器异常进行离线预报,结果表明:软件能够对结晶器液位波动、漏钢、水口断裂及其他异常做出预报,并具有一定的提前量,运行速度满足在线预报的要求。
基于圆坯连铸结晶器温度和热流在线实测数据,开发针对实测数据的结晶器传热计算方法。利用传热反问题模型模拟实际条件下结晶器内部的传热行为,同时采用神经元网络求解结晶器传热反问题,建立了传热反问题—神经网—正问题的结晶器传热计算耦合模型。利用模型对在线检测的连续瞬时数据进行计算,表明将神经元网络与传热数值计算结合的方法可用于结晶器传热计算,能够真实反映圆坯结晶器传热的非均匀特性,计算的精度与速度基本满足在线实时计算的要求。正常工况下,在工艺参数稳定时,圆坯周向的局部热流和坯壳厚度并不恒定,周向导热决定坯壳的厚度分布,结晶器热流与坯壳厚度沿周向呈不均匀分布。
The mould is the core instrument for primary cooling and slab forming of liquid steel, and it takes effect as heat transfer, support, restriction, lubrication and demould during continuous casting (CC). The interior heat transfer and friction of mould have close relationship with the surface defects and breakout, which is very important for the effectively continuous casting. Aiming to control and adjust the initial solidification and frictional behavior online, it is necessary to ensure the conditions of stable heat transfer and lubrication, which is not only the requirement of strand quality, but also the precondition for stable and high efficient production. In the future, the development of continuous casting technology will more strongly depend on the automatic control during producing process. Therefore, it is urgently needed to develop new technologies for online measurement of thermal and mechanical behaviors in continuous casting mould, which is very important in both fundamental study and practical application. Furthermore, investigating on mould measurement methods and their applications, will play a significant role in further understanding of basic theory and monitoring practice for mould process.
In this dissertation, fundamental studies of mould thermo-mechanical monitoring technologies and their applications are discussed, especially, the online measurement method of mould friction, as well as the numerical simulation of heat transfer and their applications. Based on the slab caster equipped with hydraulic oscillators, the theoretical model, measurement method and monitoring system of mould friction are investigated. In addition, according to the mould friction data measured on slab caster, the application method of mould friction is studied, and the prediction model and software for mould abnormalities are developed. In the last chapter of this dissertation, the calculation method, which combines the online measurement data of mould temperature and heat flux and numerical simulation, is investigated by using the inverse heat transfer model and neural network for the round billet continuous casting.
Through theorecally analyzing the loading states during mould oscillation driven by the hydraulic units, the loading model is built and the theory foundation and overall measurement method are established for mould friction monitor in CC. The real-time calculation and optimization model of empty oscillating parameters is built by particle swarm optimization (PSO). The implementation and convergence performance of PSO algorithm are discussed, and the optimized results are also analyzed and evaluated. Based on the above work, both hardware and software for mould friction measurement are designed. The measurement tests show that the system is suitable for monitoring mould friction, and realizes the online detection of transient mould friction continuously, stably, and automatically. In the basis of the mould friction data measured, the periodical variations and characteristic values of mould friction, as well as negative strip parameters are discussed, and the characteristics of non-sinusoidal waveforms are also studied. In addition, by using the measurement data of displacement and cylinder force, the oscillation service state of hydraulic oscillators and its evaluation methods are investigated.
According to the abnormal records of steel plant, mould friction measured on slab caster by power-method is used to investigate its response to abnormalities in continuous casting. The results show that mould friction can respond to most abnormalities such as breakout, submerged entry nozzle broken, and acute fluctuation of mould level. The root mean square of mould friction ranges from 0.8 to 4 kN before or during the abnormalities. The prediction model for mould friction abnormalities has been built by using artificial neural network models in combination with two pattern recognition algorithms. A set of software to predict the mould friction abnormalities in CC has been developed. The results of simulation prediction for online measurement mould friction data are found to be basically consistent with those collected from the abnormal records of steel plant, such as breakout, submerged entry nozzle broken and acute mould level fluctuations. In some cases, it can make prediction several minutes earlier than the alarm given by temperature breakout detection system. The proposed method can make the system respond fast enough in real time plant prediction, and render sufficient time for online prediction and taking operations against abnormalities.
Based on the measured data of temperature and heat flux during round billet continuous casting, the calculation method which combines the online measurement data and numerical simulation is investigated. The thermal behavior is analyzed by an inverse heat transfer model, and it reflects the real state of transient heat transfer of mould. In order to decrease the calculation time to meet the online monitor requirement, an artificial neural network model is developed to solve the inverse problem, and the IHTP/ANN/DHTP (inverse heat transfer problem, artificial neural network, and direct heat transfer problem) integrated method of thermal behavior analysis from experimental temperatures is developed. The results show that the neural network is faster for inverse model, and the calculation results by this method can correctly reflect the characteristics of non-uniform heat transfer. Also the calculation accuracy and speed meet basically the requirements of online calculation. Through calculation, it is found that although the operating conditions are stable, the shell thickness may be fluctuated. The shell thickness varies directly with the heat flux at fixed mould circumferential degrees. It is also found that the profile of shell thickness is non-uniform and similar to that of the heat flux along circumference direction.
引文
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