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基于CEEMD-IBES-ELM的水轮机尾水管压力脉动预测

孙彦飞 曾云 钱晶 马伟栋 张欢

排灌机械工程学报2026,Vol.44Issue(3):276-283,8.
排灌机械工程学报2026,Vol.44Issue(3):276-283,8.DOI:10.3969/j.issn.1674-8530.24.0062

基于CEEMD-IBES-ELM的水轮机尾水管压力脉动预测

Prediction of pressure pulsations in draft tube based on CEEMD-IBES-ELM

孙彦飞 1曾云 1钱晶 1马伟栋 2张欢1

作者信息

  • 1. 昆明理工大学冶金与能源工程学院,云南 昆明 650500
  • 2. 中国电建集团昆明勘测设计研究院有限公司,云南 昆明 650051
  • 折叠

摘要

Abstract

In order to effectively predict the pressure pulsation of the hydraulic turbine draft tube and take corresponding measures to reduce the pressure pulsation,a hybrid prediction model was proposed,which was based on complete ensemble empirical mode decomposition(CEEMD),the improvement of the bald eagle search algorithm(IBES),and the extreme learning machine(ELM)to predict the pressure pulsation signal of the draft tube.Firstly,the non-smooth hydraulic turbine draft tube pressure pulsation signal was split into several relatively stable submodal parts based on the CEEMD decomposi-tion.Secondly,the decomposed submodal data were input into the ELM model for in-depth training and prediction analysis,and the initial weights and thresholds were optimised by IBES.Finally,the prediction result outputs of each sub-modality were superimposed to obtain the final prediction results of the pressure pulsation signals of the hydraulic turbine draft tube.The simulation results show that the proposed CEEMD-IBES-ELM prediction method can reduce the complexity of the prediction process with relatively low reconstruction error.In addition,compared with other models,this model demon-strates significant superiority in terms of prediction accuracy and stability,and has good potential for application.

关键词

尾水管/互补集成经验模态分解/秃鹰搜索算法/极限学习机/压力脉动预测

Key words

draft tube/CEEMD/bald eagle search/extreme learning machine/pressure pulsation prediction

分类

农业科技

引用本文复制引用

孙彦飞,曾云,钱晶,马伟栋,张欢..基于CEEMD-IBES-ELM的水轮机尾水管压力脉动预测[J].排灌机械工程学报,2026,44(3):276-283,8.

基金项目

国家自然科学基金资助项目(52079059) (52079059)

排灌机械工程学报

1674-8530

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