基于本体推理的单一飞行员驾驶模式自适应切换方法

doi:10.12305/j.issn.1001-506X.2025.10.21

Abstract

Abstract:

Single-pilot operation （SPO） mode has the characteristics of a large amount of domain knowledge, complex system, and difficulty in reuse, which leads to problems such as inconsistent domain knowledge cognition and vague definition of adaptive intelligent driving mode. In order to solve these problems, firstly, the organizational structure of the SPO mode collaborative flight is analyzed, and the domain related knowledge is sorted out, and a multi-domain semantic network ontology model for the SPO model is constructed based on Protégé. Secondly, combined with the reasoning framework and process of SPO mode adaptive switching method, ontology semantic feature rules and numerical feature rules are defined based on ontology and semantic web rule language （SWRL）, in order to infer high-matching adaptive driving modes in different operating scenarios. Finally, the quality of the SPO mode domain ontology model is quantitatively analyzed based on the index system. The evaluation results show that the SPO mode domain ontology model has the characteristics of high cohesion and low coupling. The constructed typical flight scenario case verifies the feasibility of the adaptive switching logic of the SPO mode, the consistency of the ontology and the correctness of switching the adaptive driving mode.

Key words: single-pilot operation （SPO） mode, ontological reasoning, semantic web rule language （SWRL）, intelligent driving mode, adaptive switching

CLC Number:

V 328

Lei DONG, Yongyue YU, Jiachen LIU, Xi CHEN. Single-pilot operation mode adaptive switching method based on ontological reasoning[J]. Systems Engineering and Electronics, 2025, 47(10): 3367-3377.

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References 31

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生理参数	数值/语义特征规则
体温/℃	略感不便：36.5~37.5
	感到不适：38.0~38.5（持续≤20min）
	执行任务能力下降：38.0~38.5（持续＞20min）
	永久生理损伤：>38.5
心率/BPM	晕眩乏力：<40
	正常：40~100
	感到压力、焦虑：100~140
	激动、发热、可能昏厥：>140

环境参数	数值/语义特征规则
氧气含量/mmHg	过多：148~160
	适中：125~148
	较少：92~107
	极少：<92
振动均方根/g	弱：0~0.064
	中：0.064~0.101
	强：0.101~0.163
	极强：0.204~0.400
天气雷达降水强度/dBZ	弱：<30
	中：30~40
	强：40~50
	极强：>50

类别	OWL描述
类	<Declaration> < Class IRI=”#SinglePilot”/> </ Declaration>
属性	<Declaration> <ObjectProperty IRI=”# hasTakeAction”/> </ Declaration> <ObjectPropertyDomain> <ObjectProperty IRI=”# hasTakeAction”/> < Class IRI=”# SinglePilot”/> </ObjectPropertyDomain >
对象属性	<ObjectPropertyRange> <ObjectProperty IRI=”# hasTakeAction”/> < Class IRI=”# PilotOperation”/> </ObjectPropertyRange > <FunctionObjectPropertyRange> <ObjectProperty IRI=”# hasTakeAction”/> </ FunctionObjectPropertyRange >
实例	<ClassAssertion> < Class IRI=”# SinglePilot”/> <NamedIndividual IRI=”#复飞”/> </ ClassAssertion>

类型	编号	SWRL规则
单一飞行员状态推理	Rule-1	S-PF（?A） ^ CoreTemperature（?A，?X） ^ greaterThan（?X，38） → hasLoadClass （?A，Class I Load）
单一飞行员状态推理	Rule-2	S-PF（?A） ^ BlinkFrequency（?A，?X） ^ lessThanOrEqual（?X，5） → hasLoadClass （?A，Class I Load）
飞机运行环境推理	Rule-3	S-PF（?A） ^ ExternalEnvironment（?p） ^ WindShear（?p，?c） ^ greaterThanOrEqual（?c，0.1） → hasEnvironmentalState（?p，UnusualEnvironment）
飞机运行环境推理	Rule-4	S-PF（?A） ^ ExternalEnvironment（?p） ^ CockpitVibration（?p，?c） ^ greaterThanOrEqual（?c，0.101） → hasEnvironmentalState（?p，UnusualEnvironment）
飞机性能参数推理	Rule-5	S-PF （?A） ^ FlightPhase（?A，?C） ^ Approach（?C） ^ Vrtg（?A，?O） ^ greaterThan（?O，1.1） ^ Altr（?A，?N） ^ greaterThan（?N，2.74） ^ hasManipulation（?A，?X） ^ Land（?X） → hasStatus（?A，AbnormalOperation）
飞机性能参数推理	Rule-6	S-PF （?A） ^ FlightPhase（?A，?C） ^ Approach（?C） ^ Vrtg（?A，?O） ^ greaterThan（?O，3.04） ^ hasManipulation（?A，?X） ^ Land（?X） → hasStatus（?A，AbnormalOperation）
复合推理规则	Rule-7	S-PF（?A）^CoreTemperature（?A,?X）^greaterThan（?X,38）^ExternalEnvironment（?P）^CockpitVibration（?P,?C） ^ greaterThanOrEqual（?C，0.101） ^ FlightPhase（?A，?K） ^ Approach （?K） ^ Vrtg（?A，?O） ^ greaterThan（?O，1.1） ^ Altr（?A，?N） ^ greaterThan（?N，2.74） ^ hasManipulation（?A，?U） ^ Land（?U） → hasLoadClass （?A，Class I Load） ^ hasEnvironmentalState（?p，AbnormalEnvironment） ^ hasStatus（?A，AbnormalOperation）

模块	类数量	关系最短距离	层次结构数关系	非层次结构数	NSHR	NSNR	Coh（M_k）	Coup（M_k）
M₁	8	（1,13）（2,5）	7	4	3	0	0.554	0.300
M₂	9	（1,14）（2,13）	8	7	2	0	0.569	0.175
M₃	12	（1,21）（2,19）	13	9	3	0	0.462	0.161

Single-pilot operation mode adaptive switching method based on ontological reasoning

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[1]	. Adaptive MIMO mode switching algorithm based on improved AMC in LTE system [J]. Journal of Systems Engineering and Electronics, 2013, 35(1): 191-195.
[2]	ZHAO Jiabao，TAN Xiaojie，JIAO Xiaocheng，ZHANG Liang. Design and implementation of Ontology-based industrial integrated alarm management system [J]. Journal of Systems Engineering and Electronics, 2010, 32(10): 2145-2150.