SPO risk evolution based on improved functional resonance analysis method

doi:10.16265/j.cnki.issn1003-3033.2024.06.1428

Abstract

Abstract:

To fully identify the interaction and coupling effects between the subsystem elements in SPO mode, an improved FRAM was developed to propose a quantitative analysis model based on the risk evolution mechanism. Firstly, the fuzzy comprehensive evaluation method was used to evaluate the functional variability of system functional modules. Then, the concept of structural importance was introduced to analyze upstream and downstream coupling variability of functional modules of the computational system and determine the coupling effect mechanism between various functional elements of the system. Finally, the Monte Carlo simulation method was used to calculate the functional resonance risk index for SPO-specific scenarios, analyze potential functional resonance situations, and set effective functional barriers. The results showed that the improved functional resonance analysis method can explain the nonlinear coupling situation of SPO. The functional variability coupling change index of modules such as air traffic control and services, pilot cognitive state, and captain control was relatively high with a value of more than 2.5. In the approach and landing scenario, eight functions (e.g., crew technical training, important meteorological information, air traffic control services, and ground information support) were prone to functional resonance. Combined with the functional resonance results, the physical, symbolic, functional, and invisible functional safety barrier measures were set to provide specific operational suggestions.

Key words: functional resonance analysis method (FRAM), single pilot operation (SPO), risk evolution, coupling changes, functional variability

CLC Number:

X949

SHI Tongyu, MA Yusen, CAO Yujie, FU Yuxiang, WANG Yantao. SPO risk evolution based on improved functional resonance analysis method[J]. China Safety Science Journal, 2024, 34(6): 29-38.

Figures/Tables 16

Fig.1

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Fig.4

Table 1

Functional change time /accuracy score

功能可变性指标	定义	评分
时间变化 $V T$	准时	1
	过早	2
	过晚	3
	不发生	4
精度变化 $V P$	精确	1
	可接受	2
	不精确	3

Table 1

Table 2

Table 3

Fig.5

Table 4

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Table 7

Fig.6

Table 8

Table 9

Table 10

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功能可变性指标	定义	输入I	资源R	前提P	时间T	控制C
时间输出变化	准时	阻尼	阻尼	阻尼	阻尼	阻尼
	过早	无影响	阻尼	阻尼	放大	放大
	过晚	放大	放大	放大	放大	放大
	不发生	放大	放大	放大	放大	放大
精度输出变化	精确	阻尼	阻尼	阻尼	阻尼	阻尼
	可接受	无影响	无影响	无影响	无影响	无影响
	不精确	放大	放大	放大	放大	放大

功能名称	进行程序转弯
描述	由输入操纵飞机进行程序转弯
输入I	飞机操纵动作指令已完成
输出O	程序转弯已完成
前提条件P	已检查进近检查单
资源R	无
控制C	无
时间T	无

要素	S₁	S₂	S₃	S₄	S₅	S₆	S₇	S₈	S₉	S₁₀
层级	10	10	9	8	9	9	11	10	8	6
要素	S₁₁	S₁₂	S₁₃	S₁₄	S₁₅	S₁₆	S₁₇	S₁₈	S₁₉	S₂₀
层级	6	7	6	5	4	3	2	1	3	3

功能模块	S₁	S₂	S₃	S₄	S₅	S₆	S₇	S₈	S₉	S₁₀
结构重要度	0.042 9	0.056 7	0.027 4	0.038 7	0.034 7	0.071 3	0.119 2	0.093 2	0.060 3	0.027 8
功能模块	S₁₁	S₁₂	S₁₃	S₁₄	S₁₅	S₁₆	S₁₇	S₁₈	S₁₉	S₂₀
结构重要度	0.018 6	0.069 4	0.014 1	0.029 4	0.013 8	0.024 1	0.010 1	0.006 0	0.001 2	0.001 2

模块	时间变化概率				精度变化概率
模块	适时	过早	过迟	未发生	精确	可接受	不精确
S₁	0.75	0.15	0.08	0.02	0.76	0.17	0.07
S₂	0.71	0.20	0.05	0.04	0.83	0.12	0.05
S₃	0.65	0.21	0.12	0.02	0.76	0.21	0.03
︙	︙	︙	︙	︙	︙	︙	︙
S₁₉	0.72	0.12	0.14	0.02	0.61	0.27	0.12
S₂₀	0.66	0.18	0.11	0.05	0.52	0.38	0.10