Study On Aircraft FCV Fault Data Analysis And Maintenance Interval Optimization

The successful test flight of the domestic large aircraft C919 marks that civil aviation industry of China has entered a new stage of development.As an important guarantee for the healthy and sustainable development of the civil aviation industry,aircraft maintenance capability has become one of the key factors to improve the competitiveness of aviation companies.At present,the major domestic airlines only carry out maintenance work according to the maintenance intervals recommended in the initial aircraft maintenance program,which may increase additional operating costs due to“under-maintenance”or“over-maintenance”.Through the large amount of data generated by the aircraft operation and maintenance process,the reliability data analysis method is used to establish a quantitative maintenance optimization model,and a more reasonable maintenance interval is established to save maintenance costs,which has great research value.This paper is based on the MSG-3 maintenance method to determine the important maintenance items,fault type and maintenance task type,and establish a reliable life inference equation for different fault impact types.For the fault data obeying the three-parameter weibull distribution,the improved MLE method is used for data analysis to obtain the model parameter estimates.For the non-safety type of faults,based on the distribution of the model,the preventive maintenance cost rate model and the availability model under the reliability constraint are studied.The genetic algorithm is used to solve the model and develop an optimal maintenance interval that meets the reliability requirements.Finally,taking the flow control valve of Airbus A320 aircraft air conditioning system as an example,the above reliability analysis method is used to evaluate and analyze the collected fault data.Then,the reliability evaluation results are substituted into two maintenance models,and the obtained two maintenance interval optimization results are analyzed to provide the proposed maintenance interval optimization method.