Abstract: 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.

Key words: civil aircraft, reliability gene pool, fault intelligent diagnosis, network framework