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 follow--up study will focus on the practical application of the network framework, constantly improve and refine its applicability.
作者
方志耕
王欢
董文杰
曹颖赛
FANG Zhi-geng;WANG Huan;DONG Wen-jie;CAO Ying-sai(College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)
出处
《中国管理科学》
CSSCI
CSCD
北大核心
2018年第11期124-131,共8页
Chinese Journal of Management Science
基金
国家自然科学基金资助项目(71671091)
关键词
民用飞机
可靠性基因库
故障智能诊断
网络框架
civil aircraft
reliability gene pool
fault intelligent diagnosis
network framework
