The coupling and correlation degree between aircraft systems is higher, and the diagnosis and prognosis of aircraft are more complex. Building a platform for storing and analyzing the aviation big data becomes an important task for civil aviation. This paper proposes a civil aircraft health management big data architecture. The civil aircraft health management system includes airborne PHM, ground PHM, remote diagnosis system, portable maintenance assistant system, maintenance center, automatic test equipment, special test equipment. Airborne PHM collects data from multiple types of data sources. Ground PHM provides decision making support for civil aircrafts including real-time alarm, health management, maintenance plan, spare parts. The paper introduces deep learning algorithm and aircraft fault diagnosis and prognosis implementation.