Article(id=1223202691283796666, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20222338, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1667750400000, receivedDateStr=2022-11-07, revisedDate=1679846400000, revisedDateStr=2023-03-27, acceptedDate=null, acceptedDateStr=null, onlineDate=1769563847609, onlineDateStr=2026-01-28, pubDate=1703433600000, pubDateStr=2023-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769563847609, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769563847609, creator=13701087609, updateTime=1769563847609, updator=13701087609, issue=Issue{id=1223202678788965355, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='12', pageStart='1', pageEnd='228', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769563844630, creator=13701087609, updateTime=1769563913308, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223202966899901286, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223202966899901287, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=178, endPage=181, ext={EN=ArticleExt(id=1223202692298818254, articleId=1223202691283796666, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Vibration Trend Prediction of Hydropower Unit Based on VMD-SE-PSO-BIGRU, columnId=1222925284869922957, journalTitle=Water Resources and Power, columnName=ELECTROMECHANICS AND CONTROL ENGINEERING, runingTitle=null, highlight=null, articleAbstract=

In order to improve the prediction accuracy of vibration signals of hydropower units, a prediction method based on variational mode decomposition (VMD), sample entropy (SE) reconstruction and particle swarm optimization (PSO) optimization of bi-directional gated circulation unit (BIGRU) was proposed. In the VMD-SE-PSO-BIGRU model, firstly, the vibration signal was decomposed into several subsequences by VMD, and the subsequences were reconstructed by SE. The trend, oscillation and noise components of the vibration signal were obtained. Then, parameter optimized BIGRU prediction models were established for the reconstructed components. Finally, the prediction results of each component were superimposed to achieve vibration prediction. Compared with other models, example analysis shows that the prediction error of the model is smaller and the prediction accuracy is higher, which can effectively predict the vibration signals of hydropower units.

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为提高水电机组振动信号预测精度，提出了一种基于变分模态分解（VMD）与样本熵（SE）重构和粒子群算法（PSO）优化双向门控循环单元（BIGRU）的预测方法。在VMD-SE-PSO-BIGRU模型中，先利用VMD将振动信号分解为若干个子序列，并通过SE对子序列进行重构，得到最终振动信号的趋势、振荡和噪声成分，然后对得到的重构分量分别建立参数优化的BIGRU预测模型，最后叠加各分量预测结果实现振动预测。实例分析表明，与其他模型相比，所提模型预测误差更小、预测精度更高，可有效预测水电机组振动信号。

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付波（1973-），男，教授，研究方向为图像处理和智能控制，E-mail：fubofanxx@mail.hbut.edu.cn

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付波（1973-），男，教授，研究方向为图像处理和智能控制，E-mail：fubofanxx@mail.hbut.edu.cn

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