ABSTRACT

It is very important to have a slag detection system (SDS) in steelmaking to detect slag and prevent its flow for improving the quality of steel produced. Slag raking is used for removing slag from liquid iron. Detection and control of slag may be carried out with the help of refractory dart or infrared imaging in the steel making zone such as in a Basic Oxygen Furnace (BOF). Each method has its advantages and limitations. Detection and control of slag flow from ladle to tundish in a casting operation is an important step towards cleanliness of the steel production. Various techniques such as ultrasonic level sensor, conductivity measurement using magnetic field, use of microphone to monitor the sound of steel flow through shroud, monitoring the radiation intensity of the stream of steel flow through a lateral side duct of the ladle shroud and monitoring of the shroud vibration have been explored to minimize the slag flow from ladle to tundish. It is obvious from literatures that non-contact based SDS is much more preferred using advanced instrumentation techniques. The problem with the vibration-based system is reduced metal level in the tundish due to setting up of slide gate of the ladle at low flow level as well as non-detection of the slag flow where vortex did not form prior to slag flow. Research showed improved performance with the vision-based caster SDS. Monitoring the sudden brightening of the slag surface around the pouring tube with the help of a CCD camera and image processing technique is also an effective way to detect slag transfer from ladle to tundish. The major limitation of this method is that a significant amount of slag already enters the tundish due to increased flow rate at the end of the tapping before splashing takes place. This work attempts to overcome this problem. There is an increased trend in the amplitude of the undulation of the slag surface of the tundish before the sudden brightening of the slag surface. If such undulations are identified by image analysis technique, signal can be generated to move the ladle slide gate to limit a significant amount of slag flow into the tundish. This would help to improve the quality of the steel that is produced.

摘要

在炼钢过程中，有一个熔渣检测系统（SDS）来检测熔渣并防止其流动对于提高钢的质量非常重要。扒渣用于去除铁水中的渣。熔渣的检测和控制可以在炼钢区（例如碱性氧气炉 (BOF)）中借助耐火飞镖或红外成像进行。每种方法都有其优点和局限性。在铸造操作中检测和控制从钢包到中间包的渣流是实现钢铁生产清洁的重要一步。各种技术，如超声波液位传感器、使用磁场的电导率测量、使用麦克风监测钢流过护罩的声音、已经探索了通过钢包长水口侧面管道监测钢流的辐射强度和监测长水口振动，以尽量减少从钢包到中间包的渣流。从文献中可以明显看出，使用先进的仪器技术更优选基于非接触式的 SDS。基于振动的系统的问题是中间包中的金属水平降低，这是由于在低流量水平下设置了钢包的滑动浇口以及在渣流之前没有形成涡流的情况下未检测到渣流。研究表明，基于视觉的脚轮 SDS 可以提高性能。借助CCD相机和图像处理技术监测浇注管周围渣面的突然变亮也是检测钢包到中间包的渣转移的有效方法。这种方法的主要限制是，由于在出钢结束时在飞溅发生之前流速增加，大量炉渣已经进入中间包。这项工作试图克服这个问题。在渣面突然变亮之前，中间包渣面起伏幅度有增大的趋势。如果通过图像分析技术识别出这种波动，则可以生成信号以移动钢包滑门以限制大量渣流入中间包。这将有助于提高所生产钢材的质量。在渣面突然变亮之前，中间包渣面起伏幅度有增大的趋势。如果通过图像分析技术识别出这种波动，则可以生成信号以移动钢包滑门以限制大量渣流入中间包。这将有助于提高所生产钢材的质量。在渣面突然变亮之前，中间包渣面起伏幅度有增大的趋势。如果通过图像分析技术识别出这种波动，则可以生成信号以移动钢包滑门以限制大量渣流入中间包。这将有助于提高所生产钢材的质量。