Article(id=1156963927830651744, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2403449, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1715270400000, receivedDateStr=2024-05-10, revisedDate=1735488000000, revisedDateStr=2024-12-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1753771295745, onlineDateStr=2025-07-29, pubDate=1742227200000, pubDateStr=2025-03-18, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753771295745, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753771295745, creator=13701087609, updateTime=1753771295745, updator=13701087609, issue=Issue{id=1156963927277003616, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='8', pageStart='3079', pageEnd='3528', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753771295613, creator=13701087609, updateTime=1753777038876, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1156988016305726153, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1156988016305726154, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156963927277003616, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3089, endPage=3101, ext={EN=ArticleExt(id=1156963928401077093, articleId=1156963927830651744, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Research Progress on Oil and Gas Pipeline Robots, columnId=1156963928296219492, journalTitle=Science Technology and Engineering, columnName=Petroleum and Natural Gas Industry, runingTitle=null, highlight=null, articleAbstract=

With the increasing number and aging of in-service oil and gas pipelines in China, issues such as corrosion, aging, and geometric deformation have become increasingly apparent. Due to the limitations of manual inspections, such as complex spatial environments and narrow pipe diameters, the use of pipeline robots for inspection and maintenance has emerged as a dominant trend in both domestic and international research. To address the risks of pipeline failure after prolonged service, understanding the latest advancements in pipeline robotics is crucial for setting forward-looking development goals and minimizing redundant research efforts. A comprehensive review of recent developments in in-service pipeline robotics was provided, these robots were divides into two main types based on their movement mechanisms and working environments: internal (passive and active) and external pipeline robots. By examining specific examples of each type, their overall performance were compared and highlighted key considerations for field applicability. Furthermore, the future directions were explored for pipeline robotics, emphasizing the importance of multi-parameter integration in ensuring the safe operation of oil and gas pipelines in the future.

, correspAuthors=Jie ZHENG, 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, authorCompany=null, fund=null, authors=null, authorsList=Yun-bin MA, Zu-yue SHANG, Jie ZHENG, Bo-yu ZHOU, Sheng-yong MU, Xu YANG, Hua-dong SONG, Xing-qiao JIANG), CN=ArticleExt(id=1156964038707078069, articleId=1156963927830651744, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=油气管道机器人研究进展, columnId=1154013913785032705, journalTitle=科学技术与工程, columnName=石油、天然气工业, runingTitle=null, highlight=null, articleAbstract=

随着中国在役油气管道数量的增加、时间的增长,管道腐蚀、老化、几何变形等缺陷逐步显现而出。由于人工检测受空间复杂、管径窄小等因素限制,应用管道机器人进行检测等作业已成为国内外研究的主流趋势。针对油气管道长时间服役后存在的失效风险,掌握油气管道机器人的最新研究趋势,有助于制定前沿性的发展目标并减少研究重复的可能性。对近年来在役油气管道机器人的研究现状进行详细阐述,根据运动结构、工作环境将管道机器人分为管道内(被动式、主动式)、管道外机器人两大类,通过详细举例各类型管道机器人,对比分析各运动结构的综合性能,提出现场适用性需要考虑的关键点,研究管道机器人的未来发展方向,提出管道机器人实现多参数融合,将对未来油气管道的安全服役有重要意义。

, correspAuthors=郑杰, authorNote=null, correspAuthorsNote=
*郑杰(1987—),男,汉族,甘肃平凉人,博士(后),副教授。研究方向:管道机器人、井下智能装备设计与研发。E-mail:zhjoil@163.com。
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马云宾(1984—),男,汉族,山东聊城人,硕士,高级工程师。研究方向:油气管道智能技术建设智能感知及安全监测。E-mail: myb01@pipechina.com.cn。

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马云宾(1984—),男,汉族,山东聊城人,硕士,高级工程师。研究方向:油气管道智能技术建设智能感知及安全监测。E-mail: myb01@pipechina.com.cn。

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马云宾(1984—),男,汉族,山东聊城人,硕士,高级工程师。研究方向:油气管道智能技术建设智能感知及安全监测。E-mail: myb01@pipechina.com.cn。

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articleId=1156963927830651744, language=EN, label=Fig. 11, caption=Peristaltic piping robot ${}^{\left\lbrack {54}\right\rbrack }$, figureFileSmall=BqSejCZJk60mpX4vlZyKfQ==, figureFileBig=zduxyUzOSaCqU0OaGrjWug==, tableContent=null), ArticleFig(id=1156986856937181659, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=CN, label=图11, caption=蠕动式管道机器人 ${}^{\lbrack {54}\rbrack }$, figureFileSmall=BqSejCZJk60mpX4vlZyKfQ==, figureFileBig=zduxyUzOSaCqU0OaGrjWug==, tableContent=null), ArticleFig(id=1156986857033650654, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=EN, label=Fig. 12, caption=Thesbot-Dual serpentine pipe robots ${}^{\left\lbrack {65}\right\rbrack }$, figureFileSmall=eyCH9WX52nksZ8RD72i9sg==, figureFileBig=1VgbIm1sjvuKOVf/ajOXsQ==, tableContent=null), ArticleFig(id=1156986857113342432, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, 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label=Fig. 14, caption=Magna pipeline external inspection robot ${}^{\left\lbrack {101}\right\rbrack }$, figureFileSmall=NORWZ69GIKazNl3eBsJ64w==, figureFileBig=xjTSe2dpDOtmKGRr1rgElg==, tableContent=null), ArticleFig(id=1156986857557938666, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=CN, label=图14, caption=Magna 管道外检测机器人 ${}^{\left\lbrack {101}\right\rbrack }$, figureFileSmall=NORWZ69GIKazNl3eBsJ64w==, figureFileBig=xjTSe2dpDOtmKGRr1rgElg==, tableContent=null), ArticleFig(id=1156986857620853228, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=EN, label=Fig. 15, caption=Riser external robot ${}^{\left\lbrack {102}\right\rbrack }$, figureFileSmall=O5nKBNQ4yTWfFheqHIBDyw==, figureFileBig=RN1TqiZExVuE8AeoKkjYDw==, tableContent=null), ArticleFig(id=1156986857692156397, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=CN, label=图15, caption=立管管外机器人 ${}^{\left\lbrack {102}\right\rbrack }$, figureFileSmall=O5nKBNQ4yTWfFheqHIBDyw==, figureFileBig=RN1TqiZExVuE8AeoKkjYDw==, tableContent=null), ArticleFig(id=1156986857755070960, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=EN, label=Fig. 16, caption=Eddy current inspection pipeline external robot ${}^{\left\lbrack {104}- {105}\right\rbrack }$, figureFileSmall=WDSOvAfSNUfb0RFAVj4jCw==, figureFileBig=YKc/g+Frz0R17p9WcpgPRg==, tableContent=null), ArticleFig(id=1156986857801208307, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=CN, label=图16, caption=涡流检测管道外机器人 ${}^{\left\lbrack {104}- {105}\right\rbrack }$, figureFileSmall=WDSOvAfSNUfb0RFAVj4jCw==, figureFileBig=YKc/g+Frz0R17p9WcpgPRg==, tableContent=null), ArticleFig(id=1156986857851539957, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=EN, label=Table 1, caption=Comparison of advantages, disadvantages, and applicability of various walking mechanisms of pipeline robots, figureFileSmall=null, figureFileBig=null, tableContent=
序号 运动方式 原理 适用范围 优点 缺点
1 轮式 采用电机直接驱动机器 人轮子 大部分平直干净的管道 运动速度调节方便、运动 灵活 轮子与管壁的摩擦力有限, 不适于油气管道内
2 履带式 采用电机直接驱动机器 人履带 大管径、复杂管道 可有效地提高机器人牵 引力、越障能力 机器人的结构变得复杂, 控 制难度加大,体积增大,灵活 性受到影响
3 蠕动式 不断重复收缩和伸长 运动 小管径、短距离管道 与管壁摩擦较小、越障性 能好 驱动牵引力有限,能量损失 较大
4 螺旋驱动式 驱动轮轴线与管道轴线 之间形成夹角,沿管壁某 一螺旋线行走 适应小范围管径变化 轴向驱动力大,速度快慢 的调整方便 设计制造复杂、成本高
5 多足式 如动物腿式结构实现管 内爬行 十分精密的管道或特殊 要求 行走灵活,能完成许多复 杂的运动 需要非常复杂的机械结构和 多组驱动器,制造难度、控制 难度大
6 被动式 管内流体给足够压力 驱动 原油管道、天然气集输 管道 不需要外界给与动力 条件 受管内流动介质影响,运动 较难控制
), ArticleFig(id=1156986857910260215, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156963927830651744, language=CN, label=表1, caption=管道机器人各行走机构优缺点及适用范围对比, figureFileSmall=null, figureFileBig=null, tableContent=
序号 运动方式 原理 适用范围 优点 缺点
1 轮式 采用电机直接驱动机器 人轮子 大部分平直干净的管道 运动速度调节方便、运动 灵活 轮子与管壁的摩擦力有限, 不适于油气管道内
2 履带式 采用电机直接驱动机器 人履带 大管径、复杂管道 可有效地提高机器人牵 引力、越障能力 机器人的结构变得复杂, 控 制难度加大,体积增大,灵活 性受到影响
3 蠕动式 不断重复收缩和伸长 运动 小管径、短距离管道 与管壁摩擦较小、越障性 能好 驱动牵引力有限,能量损失 较大
4 螺旋驱动式 驱动轮轴线与管道轴线 之间形成夹角,沿管壁某 一螺旋线行走 适应小范围管径变化 轴向驱动力大,速度快慢 的调整方便 设计制造复杂、成本高
5 多足式 如动物腿式结构实现管 内爬行 十分精密的管道或特殊 要求 行走灵活,能完成许多复 杂的运动 需要非常复杂的机械结构和 多组驱动器,制造难度、控制 难度大
6 被动式 管内流体给足够压力 驱动 原油管道、天然气集输 管道 不需要外界给与动力 条件 受管内流动介质影响,运动 较难控制
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油气管道机器人研究进展
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马云宾 1, 2 , 尚祖跃 3 , 郑杰 3, * , 周博宇 4 , 慕生勇 5 , 杨旭 5 , 宋华东 6 , 蒋兴桥 6
科学技术与工程 | 石油、天然气工业 2025,25(8): 3089-3101
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科学技术与工程 | 石油、天然气工业 2025, 25(8): 3089-3101
油气管道机器人研究进展
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马云宾1, 2 , 尚祖跃3, 郑杰3, * , 周博宇4, 慕生勇5, 杨旭5, 宋华东6, 蒋兴桥6
作者信息
  • 1 西安交通大学 软件学院 西安 710048
  • 2 国家石油天然气管网集团 科学技术研究总院分公司 天津 300457
  • 3 西安石油大学 机械工程学院 西安 710065
  • 4 天津中油渤星工程科技有限公司 天津 300451
  • 5 西安特种设备检验检测院 西安 710065
  • 6 沈阳仪表科学研究院有限公司 沈阳 110032
  • 马云宾(1984—),男,汉族,山东聊城人,硕士,高级工程师。研究方向:油气管道智能技术建设智能感知及安全监测。E-mail: myb01@pipechina.com.cn。

通讯作者:

*郑杰(1987—),男,汉族,甘肃平凉人,博士(后),副教授。研究方向:管道机器人、井下智能装备设计与研发。E-mail:zhjoil@163.com。
Research Progress on Oil and Gas Pipeline Robots
Yun-bin MA1, 2 , Zu-yue SHANG3, Jie ZHENG3, * , Bo-yu ZHOU4, Sheng-yong MU5, Xu YANG5, Hua-dong SONG6, Xing-qiao JIANG6
Affiliations
  • 1 School of Software Engineering Xi'an Jiaotong University Xi'an 710048 China
  • 2 PipeChina Institute of Science and Technology Tianjin 300457 China
  • 3 School of Mechanical Engineering Xi'an Shiyou University Xi'an 710065 China
  • 4 CNPC Tianjin Bo-Xing Engineering Science & Technology Co., Ltd. Tianjin 300451 China
  • 5 Xi'an Special Equipment Inspection Institute Xi'an 710065 China
  • 6 Shenyang Institute of Instrument Science Co., Ltd. Shenyang 110032 China
出版时间: 2025-03-18 doi: 10.12404/j.issn.1671-1815.2403449
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随着中国在役油气管道数量的增加、时间的增长,管道腐蚀、老化、几何变形等缺陷逐步显现而出。由于人工检测受空间复杂、管径窄小等因素限制,应用管道机器人进行检测等作业已成为国内外研究的主流趋势。针对油气管道长时间服役后存在的失效风险,掌握油气管道机器人的最新研究趋势,有助于制定前沿性的发展目标并减少研究重复的可能性。对近年来在役油气管道机器人的研究现状进行详细阐述,根据运动结构、工作环境将管道机器人分为管道内(被动式、主动式)、管道外机器人两大类,通过详细举例各类型管道机器人,对比分析各运动结构的综合性能,提出现场适用性需要考虑的关键点,研究管道机器人的未来发展方向,提出管道机器人实现多参数融合,将对未来油气管道的安全服役有重要意义。

油气管道  /  管道机器人  /  管道缺陷  /  多参数融合

With the increasing number and aging of in-service oil and gas pipelines in China, issues such as corrosion, aging, and geometric deformation have become increasingly apparent. Due to the limitations of manual inspections, such as complex spatial environments and narrow pipe diameters, the use of pipeline robots for inspection and maintenance has emerged as a dominant trend in both domestic and international research. To address the risks of pipeline failure after prolonged service, understanding the latest advancements in pipeline robotics is crucial for setting forward-looking development goals and minimizing redundant research efforts. A comprehensive review of recent developments in in-service pipeline robotics was provided, these robots were divides into two main types based on their movement mechanisms and working environments: internal (passive and active) and external pipeline robots. By examining specific examples of each type, their overall performance were compared and highlighted key considerations for field applicability. Furthermore, the future directions were explored for pipeline robotics, emphasizing the importance of multi-parameter integration in ensuring the safe operation of oil and gas pipelines in the future.

oil and gas pipelines  /  pipeline robots  /  piping defects  /  multi-parameter fusion
马云宾, 尚祖跃, 郑杰, 周博宇, 慕生勇, 杨旭, 宋华东, 蒋兴桥. 油气管道机器人研究进展. 科学技术与工程, 2025 , 25 (8) : 3089 -3101 . DOI: 10.12404/j.issn.1671-1815.2403449
Yun-bin MA, Zu-yue SHANG, Jie ZHENG, Bo-yu ZHOU, Sheng-yong MU, Xu YANG, Hua-dong SONG, Xing-qiao JIANG. Research Progress on Oil and Gas Pipeline Robots[J]. Science Technology and Engineering, 2025 , 25 (8) : 3089 -3101 . DOI: 10.12404/j.issn.1671-1815.2403449
在现代管道运输的应用领域中,石油、天然气等燃料的管道运输占有很大的比例, 根据发改委、 国家能源局印发的《中长期油气管网规划》, 到 2025 年,全国油气管网规模达到${24}\times {10}^{4}\mathrm{\;{km}}$,全国省区市成品油、天然气管道全部联通。,网络覆盖进一步扩大,结构更加优化,储运能力大幅提升${}^{\left\lbrack 1\text{-}3\right\rbrack }$。服役于油气运输中的管道由于长期处于油、气及其混合物、硫化氢等环境中, 极易造成管道产生应力导致的裂纹或其他形式损伤[4-7],油气管道产生缺陷轻则导致管道无法正常运输, 重则引发爆炸或者火灾等重大安全事故。因此, 定期对管道进行检测和维修的必要性已成为油气输送行业的共识[8]。传统的人工检测方法效率低、成本高、受管道空间狭小等限制,工作人员无法全方位检测。因此,管道机器人应运而生[9-11]
管道机器人是一种能够替代人工在管道内、外行走, 搭载多种检测装置或维修装置的机电一体化设备,用于完成对管道内部的缺陷检测、管壁清洗、 管内修复等任务${}^{\left\lbrack {12}\text{-}{15}\right\rbrack }$。管道机器人由机械结构模块、控制模块、供能模块和作业模块等组成。管道机器人的机械结构模块包括行走机构、变径机构、转向机构及其他辅助机构,其中行走机构是管道机器人的核心结构之一, 它决定了管道机器人的整体性能。根据管道机器人在管道内运动的供能方式及运动可控性, 将其运动方式分为被动式和主动式两大类, 被动式管道机器人主要是以管道输送介质压差为驱动源的管道猪(PIG);主动式管道机器人按行走机构的不同,主要划分为轮式、履带式、蠕动式、螺旋驱动式和多足式[15-21]。在一些特殊工况中,管道内检测机器人因受管道结构、长度等因素限制不能全方位检测,而管道外检测机器人以非接触性、非破坏性的特点, 能够快速覆盖大范围的管道区域, 提供全面的检测数据, 避免了对管道内部设备的干扰和破坏。管道机器人依靠快速运动、灵活操纵、准确判断和低成本等优点, 已成为当下中外研究的热点。
对近年来在役油气管道机器人的研究现状进行详细阐述, 根据运动结构、工作环境将管道机器人分为管道内 (被动式、主动式)、管道外机器人,通过详细举例各类型管道机器人,对比分析各运动结构的综合性能, 提出了现场适用性需要考虑的关键点, 研究管道机器人的未来发展方向, 提出管道机器人实现多参数融合, 将对未来油气管道的安全服役有重要意义。
与传统的主动机器人相比,被动式管道机器人不需要外部能源供给或主动的动力装置, 利用管道内部的流体力学效应、重力或磁性等自然力来实现移动[22-24]。被动式管道机器人的移动速度相对较慢, 移动路径受到管道内流体条件和管道几何形状的限制。
Rosen 管道机器人[25] 作为目前被较为成熟应用的检测器,如图1${}^{\left\lbrack {25}\right\rbrack }$ 所示,由多组不同的单元组成,分别完成动力、检测和里程测量等多种功能。Vik 等[26-27] 研制了一种用于管道检测的高分辨率管道机器人,如图2${}^{\left\lbrack {26}\cdot {27}\right\rbrack }$ 所示,机器人前后设置盘状聚氨酯皮碗,可实现机器人的双向运动。此机器人可在线检测管道的弯头部位、测量管道的凹陷变形, 并且可以把检测结果与位置数据存储起来, 等测量结束后通过对数据的分析得到管道的损伤状态[28]
图3${}^{\left\lbrack {29}\right\rbrack }$ 为管内超声探测机器人,该机器人由多舱体单元承载不同功能模块, 可以通过检测管壁表面曲率来判断管壁损伤情况, 并将检测到的数据在中央处理模块中进行处理并储存在控制单元内。文献[30] 研发的管道检测系统拥有一个搭载传感器模块的机身和可以支撑在管壁上的支撑轮组,弹性密封与管道内壁紧靠, PIG 爬行时起到承压面作用。文献[31-32]研发的管道检测机器人前密封皮碗为检测机器人提供足够的驱动力, 后密封皮碗有开槽以便压力均衡通过。张续续[33] 针对提升流体差压驱动式管道机器人的驱动性能以及提升有效作业范围,提出了复合驱动管道机器人的驱动机构设计方案,如图4${}^{\left\lbrack {33}\right\rbrack }$ 所示,基于此开展的复合驱动能耗及节能运动控制策略研究成功研制出样机。
轮式机器人广泛运用于管道检测工作, 是目前商业开发较为成熟的一种管道机器人。轮式管道机器人驱动轮作为最基本的运动机构, 通过转动驱动轮来实现运动, 一般情况下驱动轮与电机直接连接。基于此所设计的管道机器人大多结构简单, 运动速度调节方便,但当机器人在遇到管道内部破损时驱动轮与管壁的摩擦力有限导致牵引力不足, 可能会出现打滑空转的现象,只适用于油气管道内大部分平直干净的管道[33-35]。除车轮式管道机器人外,支撑轮式机器人是在车轮式基础上发展起来的一种机器人,由支撑部分和行走部件共同配合工作,可实现在竖直管道中工作[36-37]
图5${}^{\left\lbrack {38}\right\rbrack }$ 为 McGinn 等[38] 设计的内支撑轮管道机器人,采用差速驱动的同时安装了离合器,根据不同管道情况选择合适的驱动方式以通过各种弯管。Lee 等[39] 发明的伊派克系列内窥监测机器人系统在工程应用中较为成熟,如图6${}^{\left\lbrack {39}\right\rbrack }$ 所示,采用伺服独立驱动技术和拖缆控制方式,可实现${\Phi 100}\sim$ ${2000}\mathrm{\;{mm}}$ 管径范围的管道内窥检测作业。Kim 等[40] 研制的 P350 管道机器人采用车轮式的驱动方式,主要应用于${200}\sim {1000}\mathrm{\;{mm}}$ 管径的各类管道,且最大运行长度为${250}\mathrm{\;m}$。卢泓方等[41] 研发一种拖缆内窥检测机器人如图7${}^{\left\lbrack {41}\right\rbrack }$ 所示,该机器人可实时进行设备遥控和视频影像监测记录, 也可根据检测需求搭载无损检测模块对管道缺陷进行进一步检测。唐德威等[42-43] 研制出一种三轴差速管道机器人,如图8${}^{\left\lbrack {42}- {43}\right\rbrack }$ 所示,该机器人在主体内部布置三轴差速装置, 驱动电机通过三轴差速装置将输出力传递到各驱动轮,各驱动轮所分配到的转速通过三轴差速装置反馈调节,以此适应管道机器人车轮所在轨迹的曲率变化, 能有效解决功率利用率低的问题。但该管道机器人的三轴差速装置轴向尺寸较大,不适用于较小管径的管道。闫宏伟等[44] 设计了自适应多功能智能管道机器人,主动轮外径可调节范围为${60.16}\sim {240.33}\mathrm{\;{mm}}$
履带是由主动轮驱动、围绕着主动轮、负重轮、 诱导轮和托带轮的柔性链环[45-46]。履带式管道机器人的履带作为行走机构,履带与管壁接触面积较大,能为机身提供稳定的附着力,爬坡和越障性能更好,即使在潮湿和粗糙的管内作业依旧有着良好的稳定性和通过性。但转向时易与管道发生干涉, 其结构比轮式管道机器人复杂, 需要更多的部件来维持履带张力[47-49]
Mishra 等[50] 开发的 PAROYS-II 有 3 个履带模块, 每个模块由前履带、后履带和可控连接部分组成。Kakogawa 等[51] 研发的机器人,如图${9}^{\left\lbrack {51}\right\rbrack }$ 所示, 配备了结构变化的轨道, 机器人在通过管道内的台阶或减速器时可保持其形状不变。Suryavanshi 等[52] 开发的机器人履带模块包含两个电机,分别用于滚动和驱动,如图10[52] 所示。其中 3 个模块三方向连接,适合分支管导航。Singh 等[53] 通过在全向可跟踪模块内放置两个活动关节,开发了具有弯曲功能的版本。3 个模块串联连接。验证了机器人通过垂直和弯曲管道的能力。Egorov 等[54] 开发的机器人具有控制履带模块之间角度的结构, 即使管道直径发生变化, 也可以根据内壁的半径改变角度使得机器人可以在平面上驱动。崔向贵等[55-56] 设计出一种自适应履带式管道机器人,能够在${\Phi 235}\sim$ ${280}\mathrm{\;{mm}}$ 的管道中工作,可跨越${2.5}\mathrm{\;{mm}}$ 的同心垂直台阶。文献[57-58]针对直径为${250}\sim {350}\mathrm{\;{mm}}$ 的无障碍管和障碍管管道环境,提出了一种结合丝杆螺母和弹簧机构的自适应支撑式履带结构, 可通过不高于${15}\mathrm{\;{mm}}$ 的环形台阶障碍。
蠕动式管道机器人是运用仿生学原理制造出的类似于蠕虫运动的机器人[59-61],具有结构简单、 对管道内壁的压强小的优点。它可以更好适应各种环境, 受到外界冲击后也不会产生大的伤害, 在空间狭小、非结构下的环境下都可以完成复杂的任务。但速度存在间歇性,管内流体对其影响较大, 阻碍机器人的运动速度,工作效率较低。目前市场上应用成熟广泛的仍是机械类机器人,绝大部分的蠕动式管道机器人都处于实验室阶段[62],在实际应用上还有待开发。通过材料和结构上的创新, 进一步提高机器人的鲁棒性和适应性, 蠕动式管道机器人将有更广泛的应用前景${}^{\left\lbrack {63}\text{-}{64}\right\rbrack }$
Egorov 等[54] 通过研究动物爬行的方式研发出一种蠕动式管道机器人,如图11[54] 所示,该管道机器人由多组运动单元组成, 通过协同配合在管道内移动, 可以输出较大的牵引力, 运行过程稳定, 也能爬升一定坡度的管道。Qi 等[65] 研制了一种能在${615.24}\mathrm{\;{mm}}$ 管径管道行走的蠕动式管道机器人,如图${12}^{\left\lbrack {65}\right\rbrack }$ 所示,该机器人通过前置摄像头进行管道周围环境的检测, 通过携带的传感器检测管道壁厚, 适用于弯管道多的管件。该机构采用多个关节串联结构,各部件独立控制,扭矩值${3.43}\mathrm{\;N}/\mathrm{m}$,最大角速度${400}^{\circ }/\mathrm{s}$,但操作复杂且不能在大斜坡、大直径的管道中工作。文献[66-67]提出了一种新型的双头结构的蠕动式管道机器人,该蠕动式管道机器人前后两机体由中间柔性软轴连接, 在管道中的驱动方式分为了两种,一是无动力的液压驱动行走,二是靠自身的驱动电机实现蠕动爬行。李文章等[68] 研制了一款全气动蠕动式管道机器人,机器人通过两气缸和撑杆的配合动作,可在${600}\sim {1050}\mathrm{\;{mm}}$ 易燃易爆的地下管道中进行检测和检修工作。Zhang 等[69] 研制了一种蠕动式气动软体管道机器人,可在不同直径,水,油,气环境的复杂管道爬行,能够承受自身重量超 10 倍的负载。刘洪斌等[70] 针对${\Phi 457}\mathrm{\;{mm}}$ 的天然气运输管道设计一款液压驱动蠕动式爬行管道检测机器人,运动速度可调且不低于${20}\mathrm{\;{mm}}/\mathrm{s}$,行进过程中能够安全越过$6\mathrm{\;{mm}}$ 环形障碍。
螺旋驱动式管道机器人的行走机构是机器人本体以螺旋的形式驱动并向前或向后移动[71-74]。由于车轮与管道的驱动方向不一致, 转子在驱动过程中发生旋转。该机构在弯曲管中不需要添加额外的控制, 即使使用一个执行器也可以通过弯头管驱动,结构简单,易于缩小尺寸[75-76]。螺旋式管道机器人的运动产生需要前部驱动单元持续旋转,相对于直进轮方式, 螺旋前进方式运动效率较低。
Patricio 等[77] 研制了基于螺旋驱动原理的管道机器人,能够在直径为${20}\mathrm{\;{mm}}$${50}\mathrm{\;{mm}}$ 的管道中行进。Tourajizadeh 等[78] 在输入最小化的前提下,采用线性二次型调节器方法对其进行最优控制。Selvarajan等[79] 基于螺旋驱动原理研制出一种可在管内行走的微型管道机器人,该管道机器人可以在管径为${\Phi 27}\mathrm{\;{mm}}$ 的管道中行走,最大行走速度为${34}\mathrm{\;{mm}}/\mathrm{s}$,最大驱动力为$6\mathrm{\;N}$。Chen 等[80] 开发的机器人用皮带代替轮子,该结构旨在实现高牵引力。文献[81-82] 开展螺旋管道机器人的工作原理、运动及力学行为研究,如图13 [81-82] 所示,建立了螺旋管道机器人通过直管与弯管的运动学模型, 提出了变螺旋角过弯理论及其实现方式。文献 [83-84] 针对管道内部缺陷检测困难的问题,以${\Phi 100}\sim {120}\mathrm{\;{mm}}$ 管道为对象, 基于主从控制方式设计了前后驱动的螺旋式管道检测机器人。
由于管道内环境复杂, 传统管道机器人在遇到复杂地形或障碍物时通过性不足,多足式机器人凭借出色的越障能力与灵活的机动性开始备受关注, 作为仿生结构的一种, 众多机构与学者模仿了足腿动物的移动方式研究出了多足式管道机器人[85-89]。多足式管道机器人采用多条足腿作为支撑点, 在松软或者崎岖不平的场合具有独特的性能优势, 并且不容易失控。但其控制系统非常复杂, 其需要进行多方位运动控制, 包括姿态控制、行动控制、力矩控制等;且能源消耗较大, 使得续航能力不足, 应用范围受到了限制。
Ostertag 等[90] 研制了一款利用刚毛与管壁之间摩擦差原理运动的多足式管道机器人。通过刚毛的末端与管道内壁之间的摩擦力差异, 使得管道机器人产生运动。Zhu 等[91] 对耦合系统内环进行了优化, 采用液压驱动研发了一款四足机器人, 优化后内环控制的响应速度明显提高。Suzuki 等[92] 使用脊椎动物的伸展运动作为模型行为,研发了一种采用交叉耦合感觉反馈控制的四足机器人。刘择明[93] 采用前后两个中间由虎克铰链实现柔性连接的四足机器人串联形式, 设计一款新型串联式多足机器人。潘剑锋等[94] 设计出一款自适应足式管道清洁机器人,通过丝杆螺母副机构解决了管径自适应问题, 机器人在管道内部时足腿与管壁始终接触,消除无效运动,提高行走效率。
随着油气管道机器人在管线领域的广泛应用, 随之衍生的种类也在不断增加, 现有管道机器人根据作业时所处位置不同,可分为管道内机器人和管道外机器人[95-97]。针对管道内机器人受空间、体积等限制,无法进入小管径油气管道内部实时检测, 同时考虑管道内机器人在长输管线作业时供能不足等问题, 传统的管道内机器人已经不能满足安全检测的需求。而管道外机器人无需将设备引入管道内部, 只需通过外部设备即可对管内缺陷进行检测[98-100],这表明机器人在作业时不再需要中断管道运行或排空管道,减少了停机时间和维护成本,对保障管道安全具有重要意义。
文献 [101] 研发出一款 Magna 海底管道智能检测机器人,如图${14}^{\left\lbrack {101}\right\rbrack }$ 所示,该机器人采用高速超声扫描对管道进行${360}^{\circ }$ 检测,能够发现沿管道周向${360}^{\circ }$ 的缺损异常情况,可检测出管道的外部和内部损伤,如点蚀、裂纹等一些潜在损伤。Ciszewski 等[102] 研发了 AURI (autonomous underwater riser inspection) 机器人,如图${15}^{\left\lbrack {102}\right\rbrack }$ 所示,可检测外径${190}\sim {360}\mathrm{\;{mm}}$ 立管外鞘上的损坏,该机器人由一対电驱推进器推动,已在实际工作中进行了测试。Rashid 等[103] 合作研发了 SIRIS (in situ riser inspection robotic system) 管外机器人, 该机器人由电机带动金属框架抱合在立管上, 由推进器带动机器人沿管道轴向运动进行检测。周兆明等[104] 、万夫等[105] 研制了一种涡流检测管道外机器人,如图16 [104-105] 所示,可 360° 全覆盖检测管道纵向和轴向缺陷,克服了漏磁检测方法只能检测碳钢中单向缺陷的局限性。闻暄等[106] 设计了一种环抱式管道检测机器人,基于对爬管爬壁机器人的结构原理的分析,利用机械手臂和手指进行夹紧环抱,通过主驱动轮的滚动实现沿管道爬行。
管道机器人在现场应用之前,必须通过测试验证机器人在油气管道的适用性,为确保其稳定性, 必须考虑以下因素。在实际的作业环境中, 机器人接触灰尘、铁锈等污染物尤为常见,防水防尘是关键的考虑因素。然而, 增加防护配件必然会增加机器人的体积, 应在机构设计阶段加以考虑。要在实际的工业现场使用, 必须建立一个最低限度的集成系统,如单板计算机、软件等电路方能使用,仅执行单个技术验证很难确保集成过程中发生的错误。
Matsuno 等[107] 开发的蛇形机器人通过将机器人本体包裹在海绵橡胶管中, 实现现场作业, 驾驶测试在各种环境中进行了安全测试以应用于真实环境, 并将地图和定位功能应用于机器人。Valls 等[108] 开发的管道机器人安装了涡流传感器来测量内壁的厚度,并开发了使用处理传感数据绘制$3\mathrm{D}$ 壁厚图的功能,共服役了$1\mathrm{\;{km}}$ 的埋地管道。Seet 等[109] 开发一种由 10 模块组成的模块化管道机器人,总质量约为${300}\mathrm{\;{kg}}$,使用超声波传感器和涡流传感器执行检测工作, 驱动模块配备 6 个可单独控制的轮子,因自重较大未能普及适用。Rollinson 等[110] 开发一款 Pipe Explorer 机器人,每个模块连接到滚动和节距接头, 用于牵引的运动模块具有一个壁挂式机构和一个用于驱动 3 个轮子的执行器。前后各有一个摄像头模块, 远程场涡流传感器是整个机器人检测系统的中心。Wu 等[111] 开发的机器人旨在检查直径为${40}\sim {70}\mathrm{\;{mm}}$ 城镇燃气管道,包含一个被动壁挂式机构,可以在垂直管道中移动。文献[112]开发的螺杆驱动机器人由两个驱动模块和一个摄像头模块组成, 该装置的特点是驱动电机和旋转部分之间的接头是一个万向节, 在弯曲的管道中行驶更便捷, 连接到摄像头模块的激光传感器检查管道的内表面。Cheng 等[113] 开发的机器人被设计用来使用附带的研磨机去除管道内的锈迹,为了减少工作过程中的振动, 使用线性致动器将内壁向 3 个方向施加压力, 消除无效运动。
管道机器人的行走机构决定机器人在工作时的稳定性与通过性, 每一种行走结构都各自适用于特定的工况, 各结构的优缺点如表1 所示。被动式行走机构受管内流动介质影响, 运动较难控制, 在检测过程中可能导致漏判误判的情况;轮式行走机构,尤其是支撑轮式,具有机构简单、牵引力大、运动速度快、运动部件可靠性高、控制简单、成本低廉等优点, 是管道机器人采用最多的行走方式之一; 履带式行走机构的牵引力强, 是一种在恶劣管道环境下有效的运动方式, 但结构尺寸难以小型化, 且转弯性能较差, 因此多应用于大口径管道; 蠕动式行走机构由于行走效率低、行走不连续,在研究和实际工程中采用较少;螺旋驱动式行走机构的驱动力大, 结构简单, 容易控制, 但运动效率不高, 越障能力差, 很难具备主动转向能力; 多足式的自由度较多,灵活性较好,对不同形状的管道均有一定的适应性, 但由于结构复杂, 造成控制较为困难, 且牵引力较小。
目前, 大多数开发出的管道机器人仅适用于特定的作业环境,通用性不强,被动式管道机器人 (PIG) 相对其他油气管道机器人的发展较为成熟, 但其受管内流动介质影响, 运动较难控制是一大难题。尽管中外学者开展了大量的研究与改进, 油气管道机器人仍处于由实验研究向实际应用过渡的阶段,面对管内复杂环境时机器人适应性不足,距离成熟的市场化应用还存在很大距离。随着中国国家基干管网基本形成,管道工程的飞速发展,油气管道机器人的深入研究有着极高的战略意义和经济价值。据此,对未来油气管道机器人领域的发展做出如下展望。
(1)供能问题。由于缆线与管壁之间存在较大摩擦, 有缆的供给方式导致机器人耗能增大, 严重限制运行距离。无缆的电池供电限制了机器人的工作时间,尤其是在长时间操作或远离充电设施的情况下, 导致对频繁充电的需求, 影响了机器人的效率和可靠性。未来管道机器人在研究中应结合不同能源来源, 如太阳能、微型燃料电池等, 提供更灵活的供能解决方案, 以应对不同的工作环境和任务需求。
(2)智能化问题。对油气管道作业时操作人员需要及时与管道机器人进行联系, 掌握机器人所在定位, 并对机器人的下一步动作发出指令。管道机器人常常工作在工况环境非常复杂的地方, 并且由于管内信号的屏蔽,可能造成通信不畅,无法及时给机器人下达指令, 因此未来管道机器人必须具备一定的智能化, 能够适应不同的工况环境。
(3)自适应性问题。目前油气管道机器人的大部分研究, 都是通过将油气管道简化为单一直管, 对变径管、弯管、“T”形管等研究甚少。如果机器人对多种形状管道不具备良好的通过性, 应用范围将会受到极大限制。所以未来的管道机器人必须具备良好的自适应能力,能够适应不同的工况环境。
(4)多参数融合问题。管道机器人通常配备多种传感器(如摄像头、激光测距仪、声纳、温度传感器等),多种传感器间存在数据异构性亟需解决,以便于有效融合信息。制定统一的数据格式和通信协议, 可以提升不同传感器和系统之间的兼容性, 简化多参数融合的过程;同时通过发展多模态传感器网络, 将各种传感器整合到一个统一的平台, 实现更高效的协作,推动数据融合的深度和广度,是未来管道机器人研究中的重要方向。
  • 西安市科技计划(24ZDCYISGG0045)
  • 陕西省技术创新引导计划(2024QCY-KXJ-019)
  • 陕西省市场监管科技计划项目(2023KY14)
  • 甘肃省技术创新引导计划(23CXGL0018)
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2025年第25卷第8期
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doi: 10.12404/j.issn.1671-1815.2403449
  • 接收时间:2024-05-10
  • 首发时间:2025-07-29
  • 出版时间:2025-03-18
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  • 收稿日期:2024-05-10
  • 修回日期:2024-12-30
基金
西安市科技计划(24ZDCYISGG0045)
陕西省技术创新引导计划(2024QCY-KXJ-019)
陕西省市场监管科技计划项目(2023KY14)
甘肃省技术创新引导计划(23CXGL0018)
作者信息
    1 西安交通大学 软件学院 西安 710048
    2 国家石油天然气管网集团 科学技术研究总院分公司 天津 300457
    3 西安石油大学 机械工程学院 西安 710065
    4 天津中油渤星工程科技有限公司 天津 300451
    5 西安特种设备检验检测院 西安 710065
    6 沈阳仪表科学研究院有限公司 沈阳 110032

通讯作者:

*郑杰(1987—),男,汉族,甘肃平凉人,博士(后),副教授。研究方向:管道机器人、井下智能装备设计与研发。E-mail:zhjoil@163.com。
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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