Abstract:The scientific maintenance support strategy for complex equipment is the basis for ensuring the reasonable use and on-condition repair of equipment, and is the prerequisite for the effective lifetime support of complex equipment, and is related to the effective performance of equipment tasks. Based on the condition-based maintenance strategy of aviation equipment, the turboshaft engine which is widely used in helicopters is the research object in this paper. First, based on the massive information of the maintenance process of equipment, the methods are raised to construct the life and health management of knowledge of the turboshaft engine and its key components; Then, combined with the cycle life statistics method and the K-means clustering algorithm of turboshaft engine, the quantitative analysis strategy of spare parts of turboshaft engines applied in different conditions is explained in this paper; Further, based on the typical failure mode analysis and cause analysis (FMECA) of key components and quantitative analysis of engine core spare parts considering failure probability, the quantitative analysis strategy of spare parts of the key components of turboshaft engine are raised. Finally, based on the above research results, the system architecture of the auxiliary decision-making platform for turboshaft engine maintenance support is described. The relevant research results in this paper can be used to construct the maintenance support strategy for complex equipment systems such as aero engine and its engineering application.
