Article(id=1221425784590352579, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221425781750808678, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202205073, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1652025600000, receivedDateStr=2022-05-09, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1769140200040, onlineDateStr=2026-01-23, pubDate=1674576000000, pubDateStr=2023-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769140200040, onlineIssueDateStr=2026-01-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769140200040, creator=13701087609, updateTime=1769140200040, updator=13701087609, issue=Issue{id=1221425781750808678, tenantId=1146029695717560320, journalId=1210938733613449225, year='2023', volume='52', issue='1', pageStart='1', pageEnd='182', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769140199363, creator=13701087609, updateTime=1769145231708, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1221446888994292213, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221425781750808678, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1221446888994292214, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221425781750808678, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=89, endPage=97, ext={EN=ArticleExt(id=1221425784846205142, articleId=1221425784590352579, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Study on point cloud splicing method of underground pipe gallery in power plants based on improved 3D-Harris operator, columnId=1211002409397129992, journalTitle=Thermal Power Generation, columnName=Power generation technology forum, runingTitle=null, highlight=null, articleAbstract=
In the point cloud splicing of underground pipe gallery in power plants, an improved algorithm with 3D-Harris operator about corner detection is proposed. In this algorithm, firstly, taking multiple sets of massive point cloud data of the underground pipe gallery as analysis object, the normal information of the target detection point on the adjacent point cloud microtangent plane is obtained through principal component analysis method, thus the boundary points of the point cloud are extracted. Secondly, the covariance matrix is constructed according to the normal information of the target detection point, then the corner response intensity function is calculated and compared, and some points are selected as calculation objects to judge whether they are true corner. Thirdly, the pseudo angles are filtered out and the true angles are selected by using a pseudoangle detection method based on Gaussian curvature extreme points. At last, the fast point feature histogram method is used to match similar corners between each group, and the nearest point search point cloud registration algorithm is used to realize the splicing of multiple points and cloud in the underground pipe gallery. The results are compared with that of the conventional 3D-Harris angular point detection algorithm. It is proved that the method in paper takes less time to calculate and has a higher corner-point extraction accuracy, which can realize accurate splicing of massive point cloud of underground pipe gallery.
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提出一种基于改进3D-Harris角点检测算法的电厂地下管廊点云拼接方法。以电厂地下管廊多组海量点云数据为分析对象,利用主成分分析法获取目标检测点在邻域点云微切平面上的法向信息,进而提取点云的边界点;构建基于目标检测点法向信息的协方差矩阵,计算并比较其角点响应强度函数,从中选出部分待筛选点作为真伪角点检测对象;利用基于高斯曲率极值点的伪角点检测方法,滤除伪角点并筛选出真角点;最后通过快速点特征直方图方法匹配各组点云间的相似角点,利用最近点搜索点云配准算法实现地下管廊多组点云间的拼接,并与传统3D-Harris角点检测算法的结果进行比较。对比表明,所提出算法计算耗时短且角点提取正确率高,可实现电厂地下管廊海量点云的精确拼接。
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