Abstract
General aircrafts are very complicated to analyze from the perspective of structure and system, which means the maintenance task is very heavy. The traditional “broken-then- repair” and “planned repair” methods have serious shortcomings in dealing with the ever-changing new situation. “Maintenance depending on the situation” and “predictive maintenance” will nip the fault in the bud and become the direction of future system maintenance strategy development. This research studies three key technologies: general aircraft intelligent monitoring technology, general aircraft health assessment and prediction method based on multi-source big data fusion, and general aircraft operation and maintenance process visualization evolution simulation technology. Built on these technologies, a General Aviation Health Supervision platform is developed. This supervision platform is of great significance to improve the safety and reliability of general aviation aircraft, reduce operation and maintenance costs, and promote the development of the local navigation industry. The research outcome is tested on the Ararat SA60L light sport aircraft manufactured by Hunan Shanhe Technology Co., Ltd. The test confirms that the general aviation health supervision platform, successfully provides real-time, systematic and intelligent solution for the monitoring and health supervision of general aviation aircrafts. It is expected that the new platform will create a revenue of more than 50 million yuan in the first three years of commercialization, with an annual growth rate of over 20%.
Published Version
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