转炉终点碳含量在线检测对实现炼钢终点准确控制, 提高钢铁产品质量, 降低能耗, 减少废气排放具有重要意义。 针对转炉冶炼终点控制及碳含量检测的难题, 研究了一种新的基于炉口辐射光谱分析的非接触式在线碳含量检测方法。 方法基于辐射光谱的支持向量机回归(SVR)实现转炉终点前过程的碳含量预测。 通过远距离光谱采集系统获取炉口火焰光谱信息, 基于冶炼过程炉口火焰辐射光谱变化规律的分析, 分别提取了表征辐射光谱整体特征的两个参数即总谱宽和辐射峰值、 以及表征发射谱的三个特征波长600, 630和775 nm处的幅值作为支持向量机的输入, 结合脱碳理论和实测碳值拟合重构的脱碳函数曲线作为支持向量机的输出, 利用支持向量机回归方法建立光谱分布与碳含量的关系模型。 通过训练样本集和测试集循环优化确定模型最佳参数。 设计的仪器和优选的模型已安装在转炉生产现场长时间运行, 现场实验结果表明, 终点碳含量检测准确率为90.2%, 测量时间小于0.3 s, 可实时在线检测, 能够满足生产需求, 为转炉冶炼终点的精确控制提供了重要依据。

Accurate on-line prediction of endpoint carbon is of significance for achieving control of end points, improving the quality of steel products, reducing energy consumption and reducing exhaust emissions. In order to solve the problems of endpoint control and carbon content measurement in converter smelting, a novel non-contact on-line method for detecting carbon content was proposed in this paper. The method realized BOF endpoint prediction and carbon content detection based on radiation spectrum with support vector regression. Firstly, a remote spectrum acquisition system was adopted to obtain flame information. Changes of flame radiation spectrum in smelting process were analyzed and spectral width and background radiation peak which characterize the overall spectral and intensity values of wavelength 600, 630 and 775 nm corresponding to emission peaks were extracted respectively and then used as inputs of support vector machines, combining decarburization theory and measured carbon value, the decarburization curve was reconstructed as output of support vector machine. The relationship model between spectral distribution and carbon content was established by support vector regression. The optimal parameters of the model were determined by training the sample set and the test set. The designed instrument and the optimized model have been installed in the converter production control room, field experiment results show that the accuracy of end-point carbon content prediction is 90.2%, and the measurement time is 0.3 s. It can be detected online in real time, and meet the production needs. The method provides an important basis for the precise endpoint control of the BOF.