|本期目录/Table of Contents|

[1]孙瑞山,李重锋.基于k-SC聚类的飞行操作模式及危险性分析[J].中国安全生产科学技术,2021,17(9):150-155.[doi:10.11731/j.issn.1673-193x.2021.09.024]
　SUN Ruishan,LI Chongfeng.Analysis of flight operation patterns and risk based on k-SC clustering[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2021,17(9):150-155.[doi:10.11731/j.issn.1673-193x.2021.09.024]
点击复制

基于k-SC聚类的飞行操作模式及危险性分析
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
17
期数:
2021年9期
页码:
150-155
栏目:
职业安全卫生管理与技术
出版日期:
2021-09-30

文章信息/Info

Title:
Analysis of flight operation patterns and risk based on k-SC clustering
文章编号:
1673-193X(2021)-09-0150-06
作者:
孙瑞山; 李重锋
（中国民航大学 安全科学与工程学院，天津 300300）
Author(s):
SUN Ruishan;  LI Chongfeng
（College of Safety Science and Engineering，Civil Aviation University of China，Tianjin 300300，China)
关键词:
飞行安全; 飞行数据; 飞行员操作特征; 数据挖掘; K-W检验
Keywords:
flight safety;  flight data;  pilot operation characteristics;  data mining;  K-W test
分类号:
X949
DOI:
10.11731/j.issn.1673-193x.2021.09.024
文献标志码:
A
摘要:
为挖掘飞行数据中的高危险性操作模式，采用k-SC时间序列聚类算法，并基于K-W检验分析聚类结果与不安全事件之间的关系。以特定条件下某机队着陆阶段的驾驶杆操作数据和长着陆事件为例进行模型验证。结果表明：机队有5类不同的驾驶杆操作模式；不同操作模式的着陆平飘距离分布具有显著性差异，且长着陆的危险性最高可达68.18%。研究结果可为提升航空公司飞行员操作能力、分析飞行员操作特性及其他不安全事件（如重着陆、擦机尾等）提供理论参考。
Abstract:
In order to mine the high risk operation patterns of flight data,the k-SC time series clustering algorithm was used to analyze the relationship between clustering results and unsafe events based on the K-W test.The model was verified by taking the operation data of control column and long landing events during the landing stage of a certain fleet under specific conditions as an example.The results showed that the selected fleet had five different operation patterns of control column.There were significant differences in the landing drift distance distribution under different operation patterns,and the risk of long landing could reach up to 68.18%.The model provides theoretical support for further research on improving the operating capabilities of airline pilots,analyzing operating characteristics of pilots,and other unsafe events such as heavy landing and tail wiping.

参考文献/References:

［1］中国民航航空安全报告(2019年)［R］.北京:中国民用航空局航空安全办公室,2020.
［2］孙瑞山,肖亚兵.基于QAR记录数据的民航飞行员操作特征指标结构研究［J］.中国安全生产科学技术,2012,8(11):49-54. SUN Ruishan,XIAO Yabing.Research on indicating structure for operation characteristic of civilaviation pilots based on QAR data［J］.Journal of Safety Science and Technology,2012,8(11):49-54.
［3］董传亭.基于QAR数据的飞行操作技能评价研究［D］.天津:中国民航大学,2020.
［4］祁明亮,邵雪焱,池宏.QAR超限事件飞行操作风险诊断方法［J］.北京航空航天大学学报,2011,37(10):1207-1210. QI Mingliang,SHAO Xueyan,CHI Hong.Flight operations risk diagnosis method on quick-access-record exceedance［J］.Journal of Beijing University of Aeronautics and Astronautics,2011,37(10):1207-1210.
［5］汪磊,郭世广,蒋引,等.基于曲线相似度的飞行着陆操作评价方法［J］.交通信息与安全,2019,37(6):63-69. WANG Lei,GUO Shiguang,JIANG Yin,et al.A method of landing operation evaluation based on curve similarity［J］.Journal of TransportInformation and Safety,2019,37(6):63-69.
［6］郑磊,池宏,邵雪焱.基于QAR数据的飞行操作模式及其风险分析［J］.中国管理科学,2017,25(10):109-118. ZHENG Lei,CHI Hong,SHAO Xueyan.Flight operation mode and its risk analysis based on QAR data［J］.Chinese Journal of Management Science,2017,25(10):109-118.
［7］郑磊,池宏,许保光,等.飞机重着陆预警分析方法［J］.数学的实践与认识,2019,49(3):56-72. ZHENG Lei,CHI Hong,XU Baoguang,et al.Analysis method of aircraft heavy landing pre-warning［J］.Journal of Mathematics in Practice and Theory,2019,49(3):56-72.
［8］WANG L,WU C X,SUN R S.An analysis of flight Quick Access Recorder (QAR)data and its applications in preventing landing incidents［J］.Reliability Engineering & System Safety,2014,127:86-96.
［9］WANG L.Effects of flare operation on landing safety:astudy based on ANOVA of real flight data［J］.Safety Science,2018,102:14-25.
［10］MATTHEWS B,DAS S,BJADURI K,et al.Discovering anomalous aviation safety events using scalable data mining algorithms［J］.Journal of Aerospace Computing Information & Communication,2013,10(10):467-475.
［11］KRAEMER A D,VILLANI E,ARJONI D H.Aircraft FDI and human factors analysis of a take-off maneuvre using SIVOR flight simulator［J］.IFAC-PapersOnLine,2019,51(34):184-189.
［12］YAMG J,LESKOVEC J.Patterns of temporal variation in online media［C］// Proceedings of the Forth International Conference on Web Search and Web Data Mining.New York:Association for Computing Machinery,2011:177-186.
［13］BATISTA G E,KEOGH E J,TATAW O M.An efficient complexity-invariant distance for time series［J］.Data Mining and Knowledge Discovery,2013,28(3):634-669.
［14］王潇笛,刘俊勇,刘友波,等.采用自适应分段聚合近似的典型负荷曲线形态聚类算法［J］.电力系统自动化,2019,43(1):110-118. WANG Xiaodi,LIU Junyong,LIU Youbo,et al.Morphological clustering algorithm for typical load curve based on adaptive piecewise aggregation approximation［J］.Automation of Electric Power Systems,2019,43(1):110-118.
［15］王子一.基于特征提取的时间序列分类方法的研究［D］.南京：南京大学，2019.
［16］THORNDIK R L.Who belongs in the family?［J］.Psychometrika,1953,18(4):267-276.
［17］孙瑞山,韩文律.基于差异检验的飞行超限事件参数特征分析［J］.中国安全生产科学技术,2011,7(2):22-27. SUN Ruishan,HAN Wenlyu.Analysis on parameters characteristics of flight exceedance events based on distinction test［J］.Journal of Safety Science and Technology,2011,7(2):22-27.
［18］BOEING.Statistical summary of commercial jet airplane accidents worldwide operations 1959-2018［R］.Seattle,USA:Boeing Company,2019.
［19］WANG L,WU C X,SUN R S.Pilot operating characteristics analysis of long landing based on flight QAR data［C］//International Conference on Engineering Psychology and Cognitive Ergonomics.Berlin:Springer,2013:157-166.

相似文献/References:

[1]孙瑞山,刘〓露.中美两国民航事故发展趋势对比分析[J].中国安全生产科学技术,2012,8(9):154.
　SUN Rui shan,LIU Lu.Comparative analysis on accident trend of civil aviation between China and America[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2012,8(9):154.
[2]甘旭升,端木京顺,丛伟,等.基于支持向量机的飞行安全隐患危险性评价[J].中国安全生产科学技术,2010,6(3):206.
　GAN Xu-sheng,DUANMU Jing-shun,CONG Wei,et al.Fatalness assessment of flight safety hidden danger based on support vector machine[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2010,6(9):206.
[3]高扬,王向章.基于SPA-Markov的飞行安全态势评估与预测研究[J].中国安全生产科学技术,2016,12(8):87.[doi:10.11731/j.issn.1673-193x.2016.08.014]
　GAO Yang,WANG Xiangzhang.Research on assessment and prediction of flight safety situation based on SPA-Markov[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2016,12(9):87.[doi:10.11731/j.issn.1673-193x.2016.08.014]
[4]王永刚,左笑颖.飞行安全技术影响因素及其作用机制研究[J].中国安全生产科学技术,2019,15(4):186.[doi:10.11731/j.issn.1673-193x.2019.04.029]
　WANG Yonggang,ZUO Xiaoying.Research on the factors affecting flight safety technology and its mechanism[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2019,15(9):186.[doi:10.11731/j.issn.1673-193x.2019.04.029]
[5]王永刚,苏明清.基于因子分析与突变级数法的飞行安全状态评价研究[J].中国安全生产科学技术,2018,14(3):187.[doi:10.11731/j.issn.1673-193x.2018.03.028]
　WANG Yonggang,SU Mingqing.Research on evaluation of flight safety situation based on factor analysis and catastrophe progression method[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2018,14(9):187.[doi:10.11731/j.issn.1673-193x.2018.03.028]
[6]王永刚,左笑颖,韩文娟.飞行员飞行作风内在影响因素及对策研究*[J].中国安全生产科学技术,2020,16(9):173.[doi:10.11731/j.issn.1673-193x.2020.09.027]
　WANG Yonggang,ZUO Xiaoying,HAN Wenjuan.Study on intrinsic influencing factors and countermeasures for flying style of pilots[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2020,16(9):173.[doi:10.11731/j.issn.1673-193x.2020.09.027]
[7]孙瑞山,李重锋.基于随机森林的飞机长着陆预警方法[J].中国安全生产科学技术,2021,17(5):182.[doi:10.11731/j.issn.1673-193x.2021.05.028]
　SUN Ruishan,LI Chongfeng.Early-warning method of aircraft long landing based on random forest[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2021,17(9):182.[doi:10.11731/j.issn.1673-193x.2021.05.028]

备注/Memo

备注/Memo:
收稿日期： 2021-02-10
作者简介： 孙瑞山，博士，教授，主要研究方向为民航安全管理、航空人因工程、飞行原理和飞机飞行性能。
通信作者： 李重锋，硕士研究生，主要研究方向为民航安全管理、飞行数据挖掘。
更新日期/Last Update: 2021-10-02