Determining appropriate guide vane openings (GVOs) of axial blowers under varying industrial conditions is vital for smooth operations in blast furnace ironmaking. This work analyses the influence GVO variations have on outlet air flow rate and pressure by using data taken from operating, industrial blast furnaces, based on which a support vector machine (SVM)-based GVO prediction model is developed. Outcomes reveal that the change status of GVOs, i.e., whether the GVO angle increases or decreases, is critical in determining the relationship between air flow and pressure. By introducing the change status and removing the transition outliers, predictions for the optimal GVOs required to meet the desired air flow rate and pressure in real time can be more accurately determined. The measured values of GVOs range from 0% to 100%, and the SVM-based model developed in this work predicted the GVOs with an RMSE of 0.2480%, significantly improving upon the baseline model which had an RMSE of 0.6047%. The resulting method can provide insights into the operation of complex ironmaking processes, enabling a more efficient adjustment of GVOs.

在不同的工业条件下确定轴流风机的合适导叶开口 (GVO) 对于高炉炼铁的顺利运行至关重要。这项工作通过使用来自运行中的工业高炉的数据分析 GVO 变化对出口空气流量和压力的影响，并在此基础上开发了基于支持向量机 (SVM) 的 GVO 预测模型。结果显示 GVO 的变化状态，即GVO 角是增大还是减小，对于确定气流和压力之间的关系至关重要。通过引入变化状态并去除过渡异常值，可以更准确地预测实时满足所需空气流量和压力所需的最佳 GVO。GVO 的测量值范围从 0% 到 100%，在这项工作中开发的基于 SVM 的模型预测 GVO 的 RMSE 为 0.2480%，显着改善了 RMSE 为 0.6047% 的基线模型。由此产生的方法可以深入了解复杂炼铁过程的运行，从而更有效地调整 GVO。