Experimental investigation on unstable flow in multi-stage centrifugal blower with inlet guide vane

Hiradate, Kiyotaka; Sakamoto, Kiyohide; Shinkawa, Yasushi; Joukou, Satoshi; Uchiyama, Takeshi

doi:10.1299/jfst.2016jfst0009

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…Furthermore, speed variations have been shown to threaten the stability of non-constant speed blowers by causing temporary stall harmonics. [19][20][21] Therefore, in this work we aim to solve the challenge of GVO optimisation for constant speed blowers. The effect of variations of GVOs on the interaction of flow rate and pressure is firstly investigated using the data collected from a real ironmaking process and, based on which, an SVM-based model is developed to select the optimal GVOs in the process of blast furnace ironmaking.…”

Section: Introductionmentioning

confidence: 99%

Guide Vane Opening Prediction for Constant Speed Axial Blowers in Blast Furnace Ironmaking with Variation Information

et al. 2021

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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.

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Section: Introductionmentioning

confidence: 99%