Risk Analysis And Early Warning Of Apron Operation Of Medium And Large Airports

With the rapid development of China’s civil aviation industry and the growing demand for national travel,the 14 th Five-Year Plan for the Development of Civil Aviation in China has put forward higher requirements for the safety development of civil aviation.As the apron undertakes the main maintenance and guarantee tasks for inbound and outbound flights,with the continuous increase of airport business,the resource utilization of the apron increases while also increasing the operational risk of the apron,and the safety hazards in operation also increase,which brings certain pressure to the safety management of the airport.Therefore,it is especially important to analyze and warn the risks of the apron and reduce the occurrence of unsafe incidents on the apron.This thesis focuses on the apron operation safety management of medium and large airports.Based on actual data,the following research work is carried out for risk analysis and unsafe event prediction in operation security operations.Firstly,the complete apron operation and guarantee operation process was sorted out.The apron accident classification criteria and level classification were summarized through the relevant norms of the bureau guidelines on unsafe events,and the object of subsequent data mining was clarified.On this basis,the safety characteristics of apron operation were analyzed in combination with typical apron ground accidents.Secondly,through the qualitative analysis of accident tree theory,a causal analysis model applicable to apron was established by combining HFACS human cause analysis model,which has 3 levels and 14 sub-categories,and comprehensively summarizes the factors affecting apron safety from indirect to direct causes.In terms of prediction model establishment,an orderly weighted combination prediction model of IOWA operator based on gray GM(1,1)residual correction model and cubic exponential smoothing model combined with Markov process was established to achieve dynamic determination of weight coefficients.Finally,the apron unsafe events of a large domestic hub airport for the past 12 seasons were used as the original data to analyze and warn the operational risk using the abovementioned causal analysis model and combined prediction model.The cardinality test and concession ratio analysis show that there are 11 groups of causal factors associated with this airport,and there are 7 complete potential paths of apron unsafe events,among which improper route organization procedures-inadequate work preparation-operational errors are the key paths of influence.In terms of future trend prediction,the reliability of the combined model developed in this thesis was verified by comparing it with the error of the single prediction model in the prediction of apron unsafe events,and using it to calculate the rate of unsafe events for the next two seasons,the results showed that the rate of apron unsafe events at this airport only decreased slightly,and there is a need for further improvement.Combining the analysis and prediction results,corresponding preventive measures are proposed for the apron of this airport to reduce the occurrence of apron unsafe events.