超低碳钢微观组织在线检测技术应用基础研究

发布时间：2018-09-18 18:13

【摘要】：金属材料微观组织在线检测技术是实现板带材组织性能在线闭环控制的前提,是当今现代化大生产企业迫切需要的用以确保生产线可靠性和产品质量稳定性的技术。本文以产品质量精准化和质量控制实时化为目标,以超低碳钢晶粒尺寸和织构在线检测为重点研究对象,结合激光超声非接触、远距离探测、适用于一些高温等恶劣环境的特点,采用激光超声技术对热轧带钢平均晶粒尺寸和织构检测；结合二维X射线面探测器检测时间短、精度高、对样品表面要求相对较高等特点,采用二维X射线面探测器技术对冷轧带钢织构在线检测进行了深入的研究,并提出了相应的在线检测工业应用方案。本文的主要工作及研究成果如下： (1)改进了激光超声检测平均晶粒尺寸的计算模型。通过对激光超声回波信号的分析处理,提出了采用超声回波时域信号的能量衰减来计算衰减系数的方法,当所检测试样的平均晶粒尺寸与标准试样的平均晶粒尺寸相差较大时,改进的计算方法使得平均晶粒尺寸的计算误差由43.2%降低到了17.8%,有效地提高平均晶粒尺寸的计算精度。并给出了热轧带钢平均晶粒尺寸激光超声在线检测技术方案。 (2)给出了描述材料深冲性能的四阶织构系数的计算模型。通过数值计算方法分析了超低碳钢中主要织构组分同一个晶面但不同方向上的表面波速度各向异性和波动性。采用激光超声技术检测了超低碳无间隙原子钢的表面波速度各向异性和波动性,通过给出的四阶织构系数计算式较好地计算出了四阶织构系数,其中,C411的计算误差在7%以内,C412和C413的计算误差都在20%以内。为热轧带钢织构在线检测提供理论依据。 (3)根据二维X射线衍射几何原理和快速织构检测理论,在实验室搭建了采用二维X射线面探测器技术的在线织构检测系统,并对运动带钢的织构进行了检测。当带钢运行速度达到0.65m/s时,通过提出的数据处理方法,较强织构的信息仍可记录到并反映出来,且此时带钢运行速度对采集数据的精度影响较小。为采用二维X射线面探测器技术的在线织构检测奠定了基础。
[Abstract]:On-line inspection technology of microstructure of metal material is the premise to realize the on-line closed-loop control of the structure and properties of sheet and strip. It is an urgent need of modern large-scale production enterprises in order to ensure the reliability of production line and the stability of product quality. In this paper, the product quality precision and quality control are taken as the target, the grain size and texture of ultra-low carbon steel are studied on line, and the laser ultrasonic non-contact, long-distance detection is used. Suitable for some bad environments such as high temperature and so on, laser ultrasonic technique is used to detect the average grain size and texture of hot rolled strip, combined with the characteristics of short detection time, high precision and relatively high requirement on the surface of the sample. In this paper, the two-dimensional X-ray surface detector is used to study the on-line texture detection of cold rolled strip, and the corresponding industrial application scheme is put forward. The main work and results of this paper are as follows: (1) the calculation model of average grain size for laser ultrasonic detection is improved. Based on the analysis and processing of laser ultrasonic echo signal, a method of calculating attenuation coefficient by using the energy attenuation of ultrasonic echo time domain signal is proposed. When the average grain size of the tested sample is different from that of the standard sample, the average grain size of the tested sample is different from that of the standard sample. The improved calculation method reduces the calculation error of the average grain size from 43.2% to 17.8, which effectively improves the calculation accuracy of the average grain size. The method of laser ultrasonic on-line testing for the average grain size of hot rolled strip is presented. (2) the calculation model of the fourth-order texture coefficient is given to describe the deep drawing property of the material. The velocity anisotropy and fluctuation of surface wave in ultra-low carbon steel with the same crystal face but different directions are analyzed by numerical method. The surface wave velocity anisotropy and wave fluctuation of ultra-low carbon interstitial atomic steel were measured by laser ultrasonic technique. The fourth-order texture coefficient was well calculated by the formula given in this paper. The calculation error of C411 is less than 7% and the errors of C412 and C413 are within 20%. It provides a theoretical basis for the on-line testing of hot rolled strip texture. (3) based on the theory of two-dimensional X-ray diffraction geometry and rapid texture detection, an on-line texture detection system using two-dimensional X-ray surface detector technology is set up in the laboratory. The texture of moving strip steel was tested. When the running speed of strip reaches 0.65m/s, the information of stronger texture can still be recorded and reflected by the proposed data processing method, and the speed of strip operation has little effect on the accuracy of data acquisition. It lays a foundation for on-line texture detection using two-dimensional X-ray surface detector technology.
【学位授予单位】：北京科技大学
【学位级别】：博士
【学位授予年份】：2015
【分类号】：TG142.15

【参考文献】