故障逻辑与贝叶斯时变评价网络融合的民机空调系统健康评估方法

doi:10.12305/j.issn.1001-506X.2026.03.13

系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (3): 859-871.doi: 10.12305/j.issn.1001-506X.2026.03.13

• 系统工程 • 上一篇

故障逻辑与贝叶斯时变评价网络融合的民机空调系统健康评估方法

冯蕴雯¹^,²^,*, 吕世春¹^,², 柯倩云³, 王锐¹^,², 刘晚移¹^,²

1. 西北工业大学航空学院，陕西西安 710072
2. 飞行器基础布局全国重点实验室，陕西西安 710072
3. 上海飞机客户服务有限公司技术出版物部门，上海 200241

收稿日期:2025-06-18 出版日期:2026-03-25 发布日期:2026-04-13
通讯作者: 冯蕴雯
作者简介:吕世春（2001—），男，硕士研究生，主要研究方向为飞机运行支持、飞机维修性工程
柯倩云（1989—），女，高级工程师，硕士，主要研究方向为航空类故障隔离
王　锐（1999—），男，博士研究生，主要研究方向为可靠性分析、维修性工程
刘晚移（1998—），男，博士研究生，主要研究方向为飞机可靠性、飞机维修性工程
基金资助:
上海民用飞机健康监控工程技术研究中心基金(GCZX-2024-02)资助课题

Health assessment method for civil aircraft air conditioning system integrating fault logic and Bayesian time-varying evaluation network

Yunwen FENG¹^,²^,*, Shichun LYU¹^,², Qianyun KE³, Rui WANG¹^,², Wanyi LIU¹^,²

1. School of Aeronautics，Northwestern Polytechnical University，Xi’an 710072，China
2. National Key Laboratory of Aircraft Configuration Design，Xi’an 710072，China
3. Technical Publications Department，COMAC Shanghai Aircraft Customer Service Co，Ltd，Shanghai 200241，China

Received:2025-06-18 Online:2026-03-25 Published:2026-04-13
Contact: Yunwen FENG

摘要/Abstract

摘要：

为实现少样本下民机空调系统的有效健康评估，解决空调系统时间维度下状态评估这一难题，提出一种融合故障逻辑与贝叶斯时变评价网络的评估方法。首先，基于系统工作原理构建“监测指标–部件–系统”三级评价框架，以故障逻辑图明确监测指标与部件状态的关联关系。其次，引入时间因子和信息熵–独立性权重系数耦合赋权策略，建立时变?综合赋权模糊综合评价方法，实现部件时间维度下的健康状态量化。然后，结合博弈均衡驱动的贝叶斯网络，将部件状态映射至系统状态，形成贝叶斯时变耦合赋权模糊综合评估模型（Bayesian time-varying coupling weighted fuzzy comprehensive evaluation model, BTCW-FCEM），实现系统级健康状态的动态评估。最后，基于国产民机空调系统运行监测数据开展单部件与复合部件故障案例分析，验证模型在健康状态动态评估中的高精度与高效率表现。结果表明，BTCW-FCEM在多类故障场景下的准确率、精确度、召回率和F1分数均优于多种对比模型，为民机空调系统的健康监测与故障预警提供了可靠的技术支撑。

关键词: 贝叶斯网络, 民机空调系统, 健康评估, 故障逻辑图, 模糊评价

Abstract:

To effectively achieve health assessment of civil aircraft air conditioning system under limited sample conditions and address the challenge of evaluating state in the time dimension of air conditioning system, an assessment method that integrates fault logic with a Bayesian time-varying evaluation network is proposed. Firstly, based on the system operating principles, a three-level evaluation framework of “monitoring indicators–components–system” is constructed, and a fault logic diagram is employed to clarify the relationships between monitoring indicators and component states. Secondly, a time-varying comprehensively weighted fuzzy comprehensive evaluation method is established by introducing a temporal factor and information entropy independence weight coefficient coupling weighting strategy, enabling quantify health status of components in the time dimension. Thirdly, a game-equilibrium-driven Bayesian network is incorporated to map component states to the system state, forming the Bayesian time-varying coupling weighted fuzzy comprehensive evaluation model （BTCW-FCEM） for dynamic assessment of system-level health. Finally, case studies on single component and composite component faults are conducted using operational monitoring data from a domestic civil aircraft air conditioning system, validating the high accuracy and efficiency of model in dynamic health assessment. The results show that the BTCW-FCEM outperforms multiple comparative models in terms of accuracy, precision, recall, and F1 score in various fault scenarios, providing reliable technical support for health monitoring and fault warning of civil aircraft air conditioning systems.

Key words: Bayesian network, civil aircraft air conditioning system, health assessment, fault logic diagram, fuzzy evaluation

中图分类号:

V 271.1

冯蕴雯, 吕世春, 柯倩云, 王锐, 刘晚移. 故障逻辑与贝叶斯时变评价网络融合的民机空调系统健康评估方法[J]. 系统工程与电子技术, 2026, 48(3): 859-871.

Yunwen FENG, Shichun LYU, Qianyun KE, Rui WANG, Wanyi LIU. Health assessment method for civil aircraft air conditioning system integrating fault logic and Bayesian time-varying evaluation network[J]. Systems Engineering and Electronics, 2026, 48(3): 859-871.

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序号	客舱管路温度/℃	客舱温度	组件出口温度
1	25.3	24.3	42.5
2	25.4	24.2	45.3
$\vdots $	$\vdots $	$\vdots $	$\vdots $
n	25.5	24.3	48.2

指标名称	TVGMF
组件入口温度	偏小型TVGMF A₁（x）
组件入口压力	中间型TVGMF A₃（x）
组件入口流量	中间型TVGMF A₃（x）
组件压气机出口温度	偏小型TVGMF A₁（x）
组件出口压力	偏大型TVGMF A₂（x）
组件出口温度	偏小型TVGMF A₁（x）

指标名称	TVGMF
组件出口温度	偏小型TVGMF A₁（x）
客舱管路温度	偏小型TVGMF A₁（x）
客舱温度	中间型TVGMF A₃（x）

征兆层	状态层	关联强度
1号制冷组件B	制冷组件状态D	P（D=T \|B=T,C=T）=1 P（D=T \|其他）=0
2号制冷组件C	制冷组件状态D	P（D=T \|B=T,C=T）=1 P（D=T \|其他）=0
配平空气组件E	空调系统状态A	P（A=T \|D=F,E=F）=0 P（A=F \|其他）=1

概率	1号制冷组件	2号制冷组件	配平空气组件
P_prior-false	0.00025	0.00025	0.00035
P_{posterior-false}	0.06669	0.06669	0.09266

故障逻辑与贝叶斯时变评价网络融合的民机空调系统健康评估方法

Health assessment method for civil aircraft air conditioning system integrating fault logic and Bayesian time-varying evaluation network

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图/表 25

参考文献 39

相关文章 15

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对比指标	单部件故障准确率	单部件故障精确度	单部件故障召回率	单部件故障F1分数	复合部件故障准确率	复合部件故障精确度	复合部件故障召回率	复合部件故障F1分数
基准模型	BTIE- FCEM	BTIE- FCEM	BTIWC- FCEM	BTIE- FCEM	BCW- FCEM	BCW- FCEM	BCW- FCEM	BCW- FCEM

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