基于有向网络的航空安全事故风险识别与评估

doi:10.12305/j.issn.1001-506X.2024.06.17

Abstract

Abstract:

Aiming at the identification and evaluation problem of aviation safety accident risk, based on the aviation safety accidents in 2019, the causal relationship between risk events is analyzed with event tree analysis method, and a directed weighted aviation safety risk network model is established. The infectious disease model is introduced to model the network risk propagation with the spread of aviation safety risk, and the risk events are ranked to identify aviation safety risk. The aviation safety risk network risk index and the aviation safety accident occurrence risk index are proposed to evaluate the aviation system safety risk. The results show that managers should be concerned about poor visibility, aircraft system failures, insufficient equipment maintenance, illegal operations, fatigue, improper resource allocation, improper emergency response measures, insufficient flight readiness, and insufficient education and training.

Key words: aviation system, aviation accident, network modeling, infectious model, risk identification, risk evaluation

CLC Number:

Han ZHANG, Qiang WANG. Aviation safety accident risk identification and evaluation based on directed networks[J]. Systems Engineering and Electronics, 2024, 46(6): 1995-2001.

Figures/Tables 9

Fig.1

Table 1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

References 31

1	ZIMMERMANN N , MENDONCA F A C . The impact of human factors and maintenance documentation on aviation safety: an analysis of 15 years of accident data through the PEAR framework[J]. The Collegiate Aviation Review International, 2021, 39 (2) doi: 10.22488/okstate.22.100230
2	BASTOLA D P . The relationship between leadership styles and aviation safety: a study of aviation industry[J]. Journal of Air Transport Studies, 2020, 11 (1): 71- 102. doi: 10.38008/jats.v11i1.155
3	DE VOOGT A , KALAGHER H , SANTIAGO B , et al. Go-around accidents and general aviation safety[J]. Journal of Safety Research, 2022, 82, 323- 328. doi: 10.1016/j.jsr.2022.06.008
4	BYRNES K P , RHOADES D L , WILLIAMS M J , et al. The effect of a safety crisis on safety culture and safety climate: the resilience of a flight training organization during COVID-19[J]. Transport Policy, 2022, 117, 181- 191. doi: 10.1016/j.tranpol.2021.11.009
5	LEDERER P J , NAMBIMADOM R S . Airline network design[J]. Operations Research, 1998, 46 (6): 785- 804. doi: 10.1287/opre.46.6.785
6	ZHANG X G , MAHADEVAN S . Ensemble machine learning models for aviation incident risk prediction[J]. Decision Support Systems, 2019, 116, 48- 63. doi: 10.1016/j.dss.2018.10.009
7	ZHANG X G , MAHADEVAN S . Bayesian network modeling of accident investigation reports for aviation safety assessment[J]. Reliability Engineering & System Safety, 2021, 209, 107371.
8	胡召音. 灰色理论及其应用研究[J]. 武汉理工大学学报(交通科学与工程版), 2003, 27 (3): 405- 407. doi: 10.3963/j.issn.2095-3844.2003.03.036
	HU Z Y . Gray theories and its application[J]. Journal of Wuhan University of Technology(Transportation Science & Engineering), 2003, 27 (3): 405- 407. doi: 10.3963/j.issn.2095-3844.2003.03.036
9	CHEN C C , CHEN J , LIN P C . Identification of significant threats and errors affecting aviation safety in Taiwan using the analytical hierarchy process[J]. Journal of Air Transport Ma-nagement, 2009, 15 (5): 261- 263.
10	ALE B , VAN-GULIJK C , HANEA A , et al. Towards BBN based risk modelling of process plants[J]. Safety Science, 2014, 69, 48- 56. doi: 10.1016/j.ssci.2013.12.007
11	ANCEL E , SHIH A T , JONES S M , et al. Predictive safety analytics: inferring aviation accident shaping factors and causation[J]. Journal of Risk Research, 2015, 18 (4): 428- 451. doi: 10.1080/13669877.2014.896402
12	ROSE R L , PURANIK T G , MAVRIS D N . Natural language processing based method for clustering and analysis of aviation safety narratives[J]. Aerospace, 2020, 7 (10): 143. doi: 10.3390/aerospace7100143
13	XU B , WU Q , XI C , et al. Recognition of the fatigue status of pilots using BF-PSO optimized multi-class GP classification with sEMG signals[J]. Reliability Engineering & System Safety, 2020, 199, 106930.
14	ZHOU D , ZHUANG X , ZUO H F , et al. A model fusion strategy for identifying aircraft risk using CNN and Att-BiLSTM[J]. Reliability Engineering & System Safety, 2022, 228, 108750.
15	余稼洋, 郭建胜, 周楚涵, 等. 基于Bow-tie-DT-FTA的航空安全事故预防措施决策分析[J]. 火力与指挥控制, 2022, 47 (8): 158- 164. doi: 10.3969/j.issn.1002-0640.2022.08.026
	YU J Y , GUO J S , ZHOU C H , et al. Decision-making analysis of preventive measures for aviation safety accidents based on Bow-tie-DT-FTA[J]. Fire Control & Command Control, 2022, 47 (8): 158- 164. doi: 10.3969/j.issn.1002-0640.2022.08.026
16	LUXHØJ J T , CHOOPAVANG A , ARENDT D N . Risk assessment of organizational factors in aviation systems[J]. Air Traffic Control Quarterly, 2001, 9 (3): 135- 174. doi: 10.2514/atcq.9.3.135
17	TAMASI G , DEMICHELA M . Risk evaluation techniques for civil aviation security[J]. Reliability Engineering & System Safety, 2011, 96 (8): 892- 899.
18	WILKE S , MAJUMDAR A , OCHIENG W Y . A framework for assessing the quality of aviation safety databases[J]. Safety Science, 2014, 63, 133- 145. doi: 10.1016/j.ssci.2013.11.005
19	徐吉辉, 王晓琳, 王瑛, 等. 基于证据理论的Bow-tie航空风险评估方法及应用[J]. 火力与指挥控制, 2019, 44 (10): 1- 7. doi: 10.3969/j.issn.1002-0640.2019.10.001
	XU J H , WANG X L , WANG Y , et al. Research on method and application of Bow-tie analysis based on D-S evidence theory[J]. Fire Control & Command Control, 2019, 44 (10): 1- 7. doi: 10.3969/j.issn.1002-0640.2019.10.001
20	MIYAMOTO A , BENDARKAR M V , MAVRIS D N . Natural language processing of aviation safety reports to identify inefficient operational patterns[J]. Aerospace, 2022, 9 (8): 450. doi: 10.3390/aerospace9080450
21	鲍晗, 左洪福, 蔡景, 等. 基于概率风险分析的航空发动机控制系统故障风险评估[J]. 四川兵工学报, 2018, 39 (10): 38- 43.
	BAO H , ZUO H F , CAI J , et al. Risk assessment of aeroengine control system based on probability risk analysis[J]. Journal of Ordnance Equipment Engineerin, 2018, 39 (10): 38- 43.
22	STAMATELATOS M, DEZFULI H, APOSTOLAKIS G, et al. Probabilistic risk assessment procedures guide for NASA ma-nagers and practitioners[R]. Hanover MD: NASA, 2011.
23	CUI L J , ZHANG J K , REN B , et al. Research on a new aviation safety index and its solution under uncertainty conditions[J]. Safety Science, 2018, 107, 55- 61. doi: 10.1016/j.ssci.2018.04.001
24	KHAN B , KHAN F , VEITCH B . A dynamic Bayesian network model for ship-ice collision risk in the Arctic waters[J]. Safety Science, 2020, 130, 104858. doi: 10.1016/j.ssci.2020.104858
25	KAPTAN M , UGURLU O , WANG J . The effect of nonconformities encountered in the use of technology on the occurrence of collision, contact and grounding accidents[J]. Reliability Engineering & System Safety, 2021, 215, 107886.
26	王岩韬, 刘毓. 基于复杂网络的航班运行风险传播分析[J]. 交通运输系统工程与信息, 2020, 20 (1): 198- 205.
	WANG Y T , LIU Y . Flight operation risk propagation based on complex network[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20 (1): 198- 205.
27	MA X X , DENG W Y , QIAO W L , et al. A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN[J]. Reliability Engineering & System Safety, 2022, 221, 108334.
28	Flight Safety Foundation. Aviation safety network[EB/OL]. [2023-03-05]. https://aviation-safety.net/.
29	WU M Y , DAI W , LU Z Y , et al. The method for risk evaluation in assembly process based on the discrete-time SIRS epidemic model and information entropy[J]. Entropy, 2019, 21 (11): 1029. doi: 10.3390/e21111029
30	LV C C , YUAN Z W , SI S B , et al. Cascading failure in networks with dynamical behavior against multi-node removal[J]. Chaos, Solitons & Fractals, 2022, 160, 112270.
31	STARR J R A W . Integrating fatigue management with safety management systems for commercial flightcrew operations[J]. International Journal of Aviation, Aeronautics, and Aerospace, 2017, 4 (1) doi: 10.15394/ijaaa.2017.1143

类别	节点
顶事件	㊳航空安全事故
触发事件	①疲劳; ②压力; ③自满大意; ④技能不足; ⑤程序选择不当; ⑥违规操作; ⑦特情处置不力; ⑧设备维护不足; ⑨飞机系统故障; ⑩鸟害; ⑪风切变; ⑫能见度差; ⑬协调沟通不顺; ⑭组织指挥混乱
风险传播演化事件	⑮报警系统未保持常开; ⑯可疑事件未认真对待; ⑰忽视警告; ⑱忽视潜在风险; ⑲过度依赖驾驶系统; ⑳应急响应措施不当; ㉑航行计划执行得不好; ㉒低估环境的影响; ㉓未对危险做出充分估计; ㉔没有紧急措施; ㉕机上通讯工具选择错误; ㉖问题救治不彻底; ㉗不遵守引航计划; ㉘丧失感知能力; ㉙资源未充分利用; ㉚教育培训不足; ㉛作业环境不良; ㉜法规程序管理混乱; ㉝工具设备管理不当; ㉞飞行准备不足; ㉟资源配置不当; ㊱监督检查不严; ㊲岗位资格管理不严

[1]	SHI Zhijian, WANG Huawei, WANG Xiang. Risk state evaluation of aviation maintenance based on multiple connection number set pair analysis [J]. Systems Engineering and Electronics, 2016, 38(3): 588-594.
[2]	LI Ting-peng, LI Yue, XU Yong-cheng, QIAN Yan-ling. Modeling and analysis of operation support progress of equipment based on improved PERT [J]. Systems Engineering and Electronics, 2015, 37(7): 1575-1580.
[3]	LIU Dong-liang, XU Hao-jun, MIN Gui-long. Stability analysis of aeronautic man-machine complex system risk evaluation by extremum theory [J]. Journal of Systems Engineering and Electronics, 2012, 34(12): 2504-2508.

Aviation safety accident risk identification and evaluation based on directed networks

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 31

Related Articles 3

Recommended Articles

Metrics

Comments