湖南工业大学学报2025，Vol.39Issue(5)：31-38,8.DOI:10.3969/j.issn.1673-9833.2025.05.005
基于神经网络的低比转速离心泵停机瞬态过程研究
A Neural Network-Based Study on the Transient Shutdown Process of a Low Specific Speed Centrifugal Pump
摘要
Abstract
In order to reveal the hydraulic characteristics of centrifugal pumps in the transient shutdown process,a shutdown experiment has been carried out on a low specific speed open impeller centrifugal pump under six non-rated conditions,thus obtaining the real-time evolution characteristics of the external characteristic parameters such as rotational speed,inlet and outlet pressures,head,flow rate,and shaft power over time.Meanwhile,a fitting model is established for the shutdown conditions based on the BP neural network model providing a simulation test platform for the protection of the pump station under unexpected conditions such as pump station power failure or shutdown.Based on the simulation analysis it is found that the impeller speed shows a linear and rapid decline in the initial stage of shutdown,while the flow rate decreases slowly due to the inertia and impeller effects;with an increase in the opening of outlet valves,the time required for the flow rate to decline is prolonged as well,with the shaft power showing a fluctuating and rapidly declining trend in the initial stage of shutdown.The results show that the proposed model accurately presents the hydraulic performance in the transient pump shutdown process.关键词
离心泵/停机/外特性/BP神经网络Key words
centrifugal pump/shutdown/external characteristic/BP neural network分类
机械制造引用本文复制引用
童江波,孙晓,张玉良,许晓威,贾晓奇..基于神经网络的低比转速离心泵停机瞬态过程研究[J].湖南工业大学学报,2025,39(5):31-38,8.基金项目
湖南省研究生科研创新基金资助项目(QL20230263) （QL20230263）
湖南省重点领域研发计划基金资助项目(2022GK2068) （2022GK2068）
浙江省基础公益研究计划基金资助项目(LZY21E050001) （LZY21E050001）
