Article(id=1282034764303548527, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282034747870253265, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.10.1346, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745596800000, receivedDateStr=2025-04-26, revisedDate=1752595200000, revisedDateStr=2025-07-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1783590506864, onlineDateStr=2026-07-09, pubDate=1761580800000, pubDateStr=2025-10-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783590506864, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783590506864, creator=13701087609, updateTime=1783590506864, updator=13701087609, issue=Issue{id=1282034747870253265, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='10', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='1761580800000', pubDateStr='2025-10-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783590502946, creator='13701087609', updateTime=1783593819616, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282048659068006772, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282034747870253265, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282048659068006773, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282034747870253265, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=67, endPage=74, ext={EN=ArticleExt(id=1282034765989658736, articleId=1282034764303548527, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Civil aviation maintenance man-hour prediction method based on safe energy consumption, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

To accurately predict the standard man-hours of aircraft maintenance tasks, a predictive method based on safe energy consumption for aircraft maintenance standard man-hours was proposed. Firstly, a drivable virtual human was constructed based on the skeletal parameters of the human body and the computational rules of Euler quaternions. Subsequently, motion data during maintenance processes were captured using motion capture devices. The Roberson-Wittenburg and inverse dynamics methods were then employed to calculate the joint torques borne by the virtual human during the maintenance tasks, thereby estimating the energy consumption during the maintenance process. Based on the fatigue assessment of human energy consumption, preliminary standard maintenance man-hours conforming to safety energy consumption were calculated. The study demonstrates that prediction results based on safe energy consumption are closer to the manufacturer's recommended times, with a smaller root mean square error than modular arrangement of predetermined time standards(MOD) method, indicating that this approach better reflects the actual maintenance man-hours.

, authors=Qing GUO1, Jianghai ZHU1, Yu FU**, 1, Hongfu ZUO2, authorsList=Qing GUO, Jianghai ZHU, Yu FU, Hongfu ZUO, authorCompany=null, correspAuthors=Yu FU, 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=1282034766270677105, articleId=1282034764303548527, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于安全能耗的民航维修工时预测方法, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为了准确预测不导致疲劳积累的航空器维修标准工时,提出一种基于安全能耗的机务维修标准工时预测方法。首先,根据人体骨骼参数和欧拉四元数的运算规则构建可驱动的虚拟人,再使用动作捕捉设备采集维修过程中的运动数据;然后,采用Roberson-Wittenburg与逆动力学方法计算虚拟人在复现维修任务过程中关节承受的力矩,结合关节角度与时间数据,依次计算角速度、功率,并采用辛普森法则积分以确定能量消耗;最后,根据允许的能量消耗推算出符合安全能耗的标准维修工时。结果表明:基于安全能耗的预测结果与厂商推荐时间接近,均方根误差小于模特法(MOD)法,说明该方法能够更好地反映实际维修工时,从而有效控制工作强度、预防因长时间劳动而导致的疲劳积累、保障工作人员的健康与安全。

, authors=郭庆教授1, 朱江海1, 付宇副教授**, 1, 左洪福教授2, authorsList=郭庆教授, 朱江海, 付宇副教授, 左洪福教授, authorCompany=null, correspAuthors=付宇副教授, authorNote=

郭庆(1976—),男,湖南郴州人,硕士,教授,主要从事航空装备综合保障等方面的研究。E-mail:

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** 付宇(1984—),男,山西长治人,博士,副教授,主要从事航空发动机运行监控与故障诊断、微型航空发动机设计与制造方面的研究。E-mail:
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郭庆(1976—),男,湖南郴州人,硕士,教授,主要从事航空装备综合保障等方面的研究。E-mail:

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郭庆(1976—),男,湖南郴州人,硕士,教授,主要从事航空装备综合保障等方面的研究。E-mail:

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基于安全能耗的民航维修工时预测方法
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郭庆教授 1 , 朱江海 1 , 付宇副教授 **, 1 , 左洪福教授 2
中国安全科学学报 | 安全工程技术 2025,35(10): 67-74
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中国安全科学学报 |安全工程技术 2025 , 35 (10) : 67 -74
基于安全能耗的民航维修工时预测方法
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郭庆教授1 , 朱江海1, 付宇副教授**, 1 , 左洪福教授2
作者信息
  • 1中国民航大学 航空工程学院,天津 300300
  • 2南京航空航天大学 民航学院,江苏 南京 211106
通讯作者:
** 付宇(1984—),男,山西长治人,博士,副教授,主要从事航空发动机运行监控与故障诊断、微型航空发动机设计与制造方面的研究。E-mail:
作者简介:

郭庆(1976—),男,湖南郴州人,硕士,教授,主要从事航空装备综合保障等方面的研究。E-mail:

Civil aviation maintenance man-hour prediction method based on safe energy consumption
Qing GUO1 , Jianghai ZHU1, Yu FU**, 1 , Hongfu ZUO2
Affiliations
  • 1College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
  • 2College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing Jiangsu 211106, China
出版时间: 2025-10-28 doi: 10.16265/j.cnki.issn1003-3033.2025.10.1346
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为了准确预测不导致疲劳积累的航空器维修标准工时,提出一种基于安全能耗的机务维修标准工时预测方法。首先,根据人体骨骼参数和欧拉四元数的运算规则构建可驱动的虚拟人,再使用动作捕捉设备采集维修过程中的运动数据;然后,采用Roberson-Wittenburg与逆动力学方法计算虚拟人在复现维修任务过程中关节承受的力矩,结合关节角度与时间数据,依次计算角速度、功率,并采用辛普森法则积分以确定能量消耗;最后,根据允许的能量消耗推算出符合安全能耗的标准维修工时。结果表明:基于安全能耗的预测结果与厂商推荐时间接近,均方根误差小于模特法(MOD)法,说明该方法能够更好地反映实际维修工时,从而有效控制工作强度、预防因长时间劳动而导致的疲劳积累、保障工作人员的健康与安全。

安全能耗  /  维修工时  /  工时预测  /  标准工时  /  疲劳  /  虚拟人

To accurately predict the standard man-hours of aircraft maintenance tasks, a predictive method based on safe energy consumption for aircraft maintenance standard man-hours was proposed. Firstly, a drivable virtual human was constructed based on the skeletal parameters of the human body and the computational rules of Euler quaternions. Subsequently, motion data during maintenance processes were captured using motion capture devices. The Roberson-Wittenburg and inverse dynamics methods were then employed to calculate the joint torques borne by the virtual human during the maintenance tasks, thereby estimating the energy consumption during the maintenance process. Based on the fatigue assessment of human energy consumption, preliminary standard maintenance man-hours conforming to safety energy consumption were calculated. The study demonstrates that prediction results based on safe energy consumption are closer to the manufacturer's recommended times, with a smaller root mean square error than modular arrangement of predetermined time standards(MOD) method, indicating that this approach better reflects the actual maintenance man-hours.

safe energy consumption  /  maintenance hours  /  forecast of working hours  /  standard man-hours  /  fatigue  /  virtual human
郭庆教授, 朱江海, 付宇副教授, 左洪福教授. 基于安全能耗的民航维修工时预测方法. 中国安全科学学报, 2025 , 35 (10) : 67 -74 . DOI: 10.16265/j.cnki.issn1003-3033.2025.10.1346
Qing GUO, Jianghai ZHU, Yu FU, Hongfu ZUO. Civil aviation maintenance man-hour prediction method based on safe energy consumption[J]. China Safety Science Journal, 2025 , 35 (10) : 67 -74 . DOI: 10.16265/j.cnki.issn1003-3033.2025.10.1346
  • 国家自然科学基金资助(U2133202)
  • 中国民航大学中央高校基本科研项目资助(3122022046)
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doi: 10.16265/j.cnki.issn1003-3033.2025.10.1346
  • 接收时间:2025-04-26
  • 首发时间:2026-07-09
  • 出版时间:2025-10-28
补充材料
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出版历史
  • 收稿日期:2025-04-26
  • 修回日期:2025-07-16
基金
国家自然科学基金资助(U2133202)
中国民航大学中央高校基本科研项目资助(3122022046)
作者信息
    1中国民航大学 航空工程学院,天津 300300
    2南京航空航天大学 民航学院,江苏 南京 211106

通讯作者:

** 付宇(1984—),男,山西长治人,博士,副教授,主要从事航空发动机运行监控与故障诊断、微型航空发动机设计与制造方面的研究。E-mail:
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https://castjournals.cast.org.cn/joweb/zgaqkxxb/CN/10.16265/j.cnki.issn1003-3033.2025.10.1346
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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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