Article(id=1223202679795598318, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20230529, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1678032000000, receivedDateStr=2023-03-06, revisedDate=1682179200000, revisedDateStr=2023-04-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1769563844869, onlineDateStr=2026-01-28, pubDate=1703433600000, pubDateStr=2023-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769563844869, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769563844869, creator=13701087609, updateTime=1769563844869, 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=93, endPage=96, ext={EN=ArticleExt(id=1223202680122754036, articleId=1223202679795598318, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Dam Surface Displacement Monitoring System Based on Machine Vision, columnId=1222925280734335368, journalTitle=Water Resources and Power, columnName=DAM SAFETY AND MONITORING, runingTitle=null, highlight=null, articleAbstract=

Conventional dam displacement monitoring methods are often associated with large errors and low efficiency. Manual monitoring methods cannot provide continuous real-time monitoring, while automated monitoring methods, such as total station robot and GNSS, are affected by weather and have limited accuracy for vertical displacement. To overcome these shortcomings, this study proposes a new intelligent monitoring method for dam displacement based on machine vision. The method utilizes the internet of things and intelligent disaster recognition algorithm to convert picture data into deformation data, enabling ultra-high precision non-contact real-time measurement of the dam. The monitoring system was tested at Lianghui Reservoir, the results demonstrate that the operation of monitoring system is stable, and the horizontal and vertical monitoring accuracy are both 1.5 mm. The proposed method has the potential to be widely applied in other water conservancy projects for surface displacement monitoring.

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常规大坝位移监测方法中，人工监测方法通常误差大、效率低且不能实时连续监测，而自动化监测方法如全站仪机器人和GNSS面临受天气影响大和垂直位移精度低等问题，故提出一种基于机器视觉的新型大坝位移智能监测方法。该方法采用物联网及智能灾变识别算法将图片数据转化为变形数据，实现对大坝的超高精度非接触式实时测量。以梁辉水库为例，应用研究表明该监测系统运行稳定，水平和垂直方向的监测精度均为1.5 mm，可在其他水利工程表面位移监测中推广应用。

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李艺（2000-），女，硕士研究生，研究方向为水利水电工程，E-mail：lyiili@163.com

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李艺（2000-），女，硕士研究生，研究方向为水利水电工程，E-mail：lyiili@163.com

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