基于多源数据驱动的机体结构运维优化技术OA

To meet the predictive and condition-based maintenance requirements for the airframe structures of large passenger aircraft,a multi-source data fusion driven system for air route maintenance is developed.This system inte-grates engineering data from the model type development phase,including flight test measured loads,full-aircraft finite element internal forces,structural fatigue damage assessment,airworthiness limitation items,and their associated maintenance requirements.By employing methods such as data cleaning,sample reconstruction,data modeling,damage accumulation analysis,and maintenance customization optimization,the system enables comprehensive condition-based maintenance support.Through application to a specific domestic large passenger aircraft,it has re-solved key challenges in data modeling accuracy and prediction efficiency for airframe structure maintenance.The sys-tem achieves rapid single-flight prediction of"flight parameters-loads-stress-damage"for critical wing regions.Based on comparison between theoretical damage per flight and actual damage values at 95%confidence level,preliminary estimates indicate that the repeat inspection interval for high-frequency eddy current inspections can be extended as follows:from 5 000 to 8 091 flight cycles for stringer hole edges at the skin-stringer splice detailed position of the lower wing panel,and from 5 500 to 8 900 flight cycles for skin hole edges.