基于可靠性基因库的民用飞机故障智能诊断网络框架设计
|
摘要
作为典型的复杂产品,大型民用飞机是工业化国家科技水平的综合体现,其运营过程中的故障问题是关系其商业成功的重要影响方面。传统的针对此类产品的故障诊断模型大多都以数据为驱动,忽略了大型民用飞机内部的组成结构和运行逻辑关系,在一定程度上影响了故障诊断的准确性和智能性。针对此问题,本文从大型民机系统的自身物理结构、可靠性框图以及运行逻辑关系出发,运用相关的数学、计算机和大数据技术,首先搭建了大型民用飞机全寿命周期可靠性基因库,并解析了可靠性基因的遗传、更新、演化等机制;其次基于大型民用飞机的故障模式设计了相应的故障诊断算法;然后构建了整个民用飞机故障智能诊断网络框架;最后通过案例研究,表明本文所提框架的实用性和有效性。
As a typical complex product,the large civil aircraft is a comprehensive embodiment of technology for industrialized countries.Fault diagnosis is a key factor which can determinate the business success of its operation.However,most of the conventional fault diagnosis models for such products are driven by data,ignoring the internal structure and operational logic relationship of large civil aircraft,which can adversely affect the accuracy and intelligence of fault diagnosis.Actually,considering the operation state of the whole equipment and subsystems,the state analysis and intelligent fault diagnosis can improve the accuracy and intelligence of fault diagnosis.To solve this problem,the objective of this paper is to give a deep insight into the large civil aircraft system's physical structure,reliability diagram and operation logic relationship and construct the reliability gene bank of large civil aircraft for the whole life cycle on the basis of mathematics,computer and big data technology.The mechanism of heredity,renewal and evolution of the reliability gene is also analyzed.Then,effective fault diagnosis algorithms are designed for some common failure modes of large civil aircraft,based on which the whole civil aircraft fault intelligent diagnosis network framework is constructed.At last,the practicability and effectiveness of the proposed framework is demonstrated through a case study.The network framework of intelligent diagnosis for civil aircraft fault is put forward by building the reliability gene bank.It is a new breakthrough in the theory of civil aircraft fault diagnosis.The followup study will focus on the practical application of the network framework,constantly improve and refine its applicability.
As a typical complex product,the large civil aircraft is a comprehensive embodiment of technology for industrialized countries.Fault diagnosis is a key factor which can determinate the business success of its operation.However,most of the conventional fault diagnosis models for such products are driven by data,ignoring the internal structure and operational logic relationship of large civil aircraft,which can adversely affect the accuracy and intelligence of fault diagnosis.Actually,considering the operation state of the whole equipment and subsystems,the state analysis and intelligent fault diagnosis can improve the accuracy and intelligence of fault diagnosis.To solve this problem,the objective of this paper is to give a deep insight into the large civil aircraft system's physical structure,reliability diagram and operation logic relationship and construct the reliability gene bank of large civil aircraft for the whole life cycle on the basis of mathematics,computer and big data technology.The mechanism of heredity,renewal and evolution of the reliability gene is also analyzed.Then,effective fault diagnosis algorithms are designed for some common failure modes of large civil aircraft,based on which the whole civil aircraft fault intelligent diagnosis network framework is constructed.At last,the practicability and effectiveness of the proposed framework is demonstrated through a case study.The network framework of intelligent diagnosis for civil aircraft fault is put forward by building the reliability gene bank.It is a new breakthrough in the theory of civil aircraft fault diagnosis.The followup study will focus on the practical application of the network framework,constantly improve and refine its applicability.
引文
[1]张辉.我国大型民用飞机产业发展战略研究[D].上海:上海交通大学,2008.
[2]林忠钦,来新民,金隼,等.复杂产品制造精度控制的数字化方法及其发展趋势[J].机械工程学报,2013,49(6):103-113.
[3]刘远.“主制造商—供应商”模式下复杂产品供应链质量管理模型及应用研究[D].南京:南京航空航天大学,2012.
[4]李亚平,刘思峰,方志耕,等.复杂产品质量参数总体设计PBS-STA-HoQ网络架构设计[J].工业工程与管理,2016,21(6):95-102.
[5]李亚平,刘思峰,方志耕,等.多质量特性产品参数设计灰靶模型[J].中国机械工程,2016,27(8):1078-1083.
[6]李亚平,刘思峰,方志耕,等.基于随机灰靶模型的多质量特性产品参数选择[J].工业工程与管理,2017,22(3):49-54.
[7]周瑜,寇纲,尔古打机.某大型装置现场可靠性的贝叶斯分析[J].中国管理科学,2016,24(11):170-176.
[8]王烨.民机产品可靠性评估技术研究[D].南京:南京航空航天大学,2009.
[9]祝硕,许保光,刘世骞.周转件构成的可修复系统的可靠性分析[J].中国管理科学,2014,22(7):67-75.
[10]曹颖赛,刘思峰,方志耕,等.系统可靠性退化的单元责任Shapley值分配模型[J].机械工程学报,2017,53(20):202-208.
[11]曹颖赛,刘思峰,方志耕,等.多态系统可靠性分析广义灰色贝叶斯网络模型[J].系统工程与电子技术,2018,40(1):231-237.
[12]何正嘉,蔡改改,申中杰,等.基于机械诊断信息的设备运行可靠性研究[J].中国工程科学,2013,15(1):9-14.
[13]曹惠玲,赵明,曲春刚,等.可靠性数据在民机故障诊断中的应用研究[J].中国安全科学学报,2011,21(10):95-101.
[14]孙利娜,黄宁,仵伟强,等.基于T-S模糊故障树的多态系统性能可靠性[J].机械工程学报,2016,52(10):191-198.
[15]Hess A,Fila L.The Joint Strike Fighter(JSF)PHM concept:Potential impact on aging aircraft problems[C]//Proceedings of IEEE,Aerospace Conference,Big Sky,MT,USA,9-16March,2002.
[16]Janasak K M,Beshears R R.Diagnostics to prognostics-A product availability technology evolution[C]//Proceedings of 2007 Annual Reliability and Maintainability Symposium,Orlando,FL,USA,22-25Jan,2007.
[17]Byington C S,Roemer M J.Prognostic enhancements to diagnostic systems for improved condition-based maintenance[military aircraft][C]//Proceedings of IEEE,Aerospace Conference,Big Sky,MT,USA,9-16March,2002.
[2]林忠钦,来新民,金隼,等.复杂产品制造精度控制的数字化方法及其发展趋势[J].机械工程学报,2013,49(6):103-113.
[3]刘远.“主制造商—供应商”模式下复杂产品供应链质量管理模型及应用研究[D].南京:南京航空航天大学,2012.
[4]李亚平,刘思峰,方志耕,等.复杂产品质量参数总体设计PBS-STA-HoQ网络架构设计[J].工业工程与管理,2016,21(6):95-102.
[5]李亚平,刘思峰,方志耕,等.多质量特性产品参数设计灰靶模型[J].中国机械工程,2016,27(8):1078-1083.
[6]李亚平,刘思峰,方志耕,等.基于随机灰靶模型的多质量特性产品参数选择[J].工业工程与管理,2017,22(3):49-54.
[7]周瑜,寇纲,尔古打机.某大型装置现场可靠性的贝叶斯分析[J].中国管理科学,2016,24(11):170-176.
[8]王烨.民机产品可靠性评估技术研究[D].南京:南京航空航天大学,2009.
[9]祝硕,许保光,刘世骞.周转件构成的可修复系统的可靠性分析[J].中国管理科学,2014,22(7):67-75.
[10]曹颖赛,刘思峰,方志耕,等.系统可靠性退化的单元责任Shapley值分配模型[J].机械工程学报,2017,53(20):202-208.
[11]曹颖赛,刘思峰,方志耕,等.多态系统可靠性分析广义灰色贝叶斯网络模型[J].系统工程与电子技术,2018,40(1):231-237.
[12]何正嘉,蔡改改,申中杰,等.基于机械诊断信息的设备运行可靠性研究[J].中国工程科学,2013,15(1):9-14.
[13]曹惠玲,赵明,曲春刚,等.可靠性数据在民机故障诊断中的应用研究[J].中国安全科学学报,2011,21(10):95-101.
[14]孙利娜,黄宁,仵伟强,等.基于T-S模糊故障树的多态系统性能可靠性[J].机械工程学报,2016,52(10):191-198.
[15]Hess A,Fila L.The Joint Strike Fighter(JSF)PHM concept:Potential impact on aging aircraft problems[C]//Proceedings of IEEE,Aerospace Conference,Big Sky,MT,USA,9-16March,2002.
[16]Janasak K M,Beshears R R.Diagnostics to prognostics-A product availability technology evolution[C]//Proceedings of 2007 Annual Reliability and Maintainability Symposium,Orlando,FL,USA,22-25Jan,2007.
[17]Byington C S,Roemer M J.Prognostic enhancements to diagnostic systems for improved condition-based maintenance[military aircraft][C]//Proceedings of IEEE,Aerospace Conference,Big Sky,MT,USA,9-16March,2002.