Article(id=1281627169709338765, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.01.0430, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752076800000, receivedDateStr=2025-07-10, revisedDate=1762704000000, revisedDateStr=2025-11-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1783493328739, onlineDateStr=2026-07-08, pubDate=1769529600000, pubDateStr=2026-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783493328739, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783493328739, creator=13701087609, updateTime=1783493328739, updator=13701087609, issue=Issue{id=1281627156769903305, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='1', pageStart='1', pageEnd='280', issueExtLink='null', onlineDate='null', pubDate='1769529600000', pubDateStr='2026-01-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783493325654, creator='13701087609', updateTime=1783588714348, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282027246013624992, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282027246013624993, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=57, endPage=62, ext={EN=ArticleExt(id=1281627169893888142, articleId=1281627169709338765, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Design of a comprehensive inspection vehicle for heavy-haul railway line, columnId=1277328337617941059, journalTitle=China Safety Science Journal, columnName=Safety Technology and Engineering, runingTitle=null, highlight=null, articleAbstract=

To achieve accurate identification and evaluation of the service state of heavy-haul railway lines, a heavy-haul railway line comprehensive inspection vehicle was designed and developed, integrating six major inspection systems: a track condition inspection system, a rail profile measurement system, a track geometry measurement system, a rail flaw detection system, a wheel-rail force measurement system, and a vibration measurement system. A positioning and synchronization system is employed to enable synchronized acquisition and correlation analysis of multi-source line-condition data, and to provide graded alarms for suspected defects. The results show that, since its commissioning in July 2023, the heavy-haul railway line comprehensive inspection vehicle, operating at speeds up to 80 km/h, has continuously collected multi-source data including track geometry parameters, surface inspection images, internal B-scan images, wheel-rail forces, and vibration signals, and has established a database of typical defects. By combining the positioning and synchronization system with a multi-source spatiotemporal mapping model, the system realizes automatic alignment and correlation analysis of inspection data, enabling accurate tracing of defect causes and reducing both false positives and missed detections. Furthermore, the proposed graded alarm mechanism for suspected defects supports differentiated responses such as speed restriction, reporting, and record-keeping according to exceedance levels, thereby ensuring train operation safety while improving both heavy-haul railway maintenance efficiency and train operation efficiency.

, authors=Yuan CAO¹, Jian LI¹, Yongkui SUN^{**, 1}, Shuai SU¹, Weifeng YANG², Wenkun WANG², authorsList=Yuan CAO, Jian LI, Yongkui SUN, Shuai SU, Weifeng YANG, Wenkun WANG, authorCompany=null, correspAuthors=Yongkui SUN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281627170233626767, articleId=1281627169709338765, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=重载铁路线路综合检测车设计, columnId=1277328337940902469, journalTitle=中国安全科学学报, columnName=安全技术与工程, runingTitle=null, highlight=null, articleAbstract=

为精确辨识与评估重载铁路线路服役状态，设计并研制重载铁路线路综合检测车，集成包括轨道状态巡检、钢轨轮廓检测、轨道几何参数检测、钢轨探伤检测、轮轨力检测、振动检测6大检测系统；通过定位同步系统同步检测和关联分析线路多源状态数据，并分级报警可疑病害。结果表明：重载铁路线路综合检测车自2023年7月下线投入运行以来，依托最高80 km/h的运行能力，采集线路几何参数、表面巡检图像、内部B型图、轮轨力和振动等多源数据，建立典型病害库；结合定位同步系统与多源数据时空映射模型，自动对齐与关联分析检测数据，准确溯源线路病害成因、降低误报率和漏报率；构建的可疑病害分级报警机制依据超限等级实施限速、上报和记录等差异化处置，在确保行车安全的同时提升重载铁路线路养护与列车运行效率。

, authors=曹源教授¹, 李健¹, 孙永奎副教授^{**, 1}, 宿帅教授¹, 杨卫峰正高级工程师², 王文昆高级工程师², authorsList=曹源教授, 李健, 孙永奎副教授, 宿帅教授, 杨卫峰正高级工程师, 王文昆高级工程师, authorCompany=null, correspAuthors=孙永奎副教授, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=Ntq1Fc8Hc/iMnsE6zh+FrQ==, magXml=hDqQ/pDNDgkZ0X5A+6IgXw==, pdfUrl=null, pdf=sNyWX5JUQRTQ9Wo5yLXw6A==, pdfFileSize=1896263, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=UKtv8InnqleGI0tYDeNG1g==, mapNumber=null, fund=null)}, authors=[Author(id=1281627170619502743, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627169709338765, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=ycao@bjtu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281627170703388825, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627169709338765, authorId=1281627170619502743, language=EN, stringName=Yuan CAO, firstName=Yuan, middleName=null, lastName=CAO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹School of Automation and Intelligence, Beijing Jiaotong University, Beijing 100044, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281627170791469210, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627169709338765, authorId=1281627170619502743, language=CN, stringName=曹源教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹北京交通大学 自动化与智能学院，北京 100044, bio={"content":"

曹源（1982—），男，河南开封人，博士，教授，主要从事铁路系统运维方面的研究。E-mail: ycao@bjtu.edu.cn。

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曹源（1982—），男，河南开封人，博士，教授，主要从事铁路系统运维方面的研究。E-mail: ycao@bjtu.edu.cn。

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