Research On Optimization Of Pressure Surface Cleaning Parameters Of Aircraft Engine Fan Blades

At present,the pressure surfaces of the fan blades of aircraft engines are all manually cleaned.The working hours are long and the labor intensity is high,which can damage the health of workers.At the same time,due to human subjective factors,there will be problems such as substandard cleaning effect,which can easily cause great flight safety hazards.Therefore,in order to solve the above problems,it is of great value to study a fast,efficient,environmentally friendly and healthy cleaning method for the pressure surface of the fan blade of an aircraft engine,which can replace the manual work,and at the same time to design the cleaning process and optimize the parameters involved in the cleaning process.Firstly,by comparing the current industrial cleaning methods and studying the aircraft engine fan blade pressure surface maintenance manual,the automatic cleaning method of the pressure surface of aircraft engine fan blade is determined.Then design the tooling fixture of the pressure surface of the aircraft engine fan blades that can realize automatic cleaning,and design the overall structure of the cleaning mechanism.In order to achieve the purpose of automatic cleaning,the whole cleaning process is defined according to the designed mechanism.Secondly,in order to improve the cleaning effect of the pressure surface of the fan blades of aircraft engines,appropriate ultrasonic cleaning parameters must be selected.Therefore,it is necessary to analyze the key factors affecting the pressure surface cleaning of aircraft engine fan blades.In order to obtain the optimal cleaning parameter combination for the pressure surface of the aircraft engine fan blades,the BP neural network set prediction model is established in this paper.The neural network test data is obtained from the orthogonal test,and the non-linear relationship between the process parameters and the quality index is mapped out;the hybrid algorithm of the simulated annealing algorithm and the improved genetic algorithm is used for the global optimization,so as to achieve the goal of ultrasonic cleaning aircraft engine fan blade pressure surface efficient and energy saving goals.Then,according to the optimization results of the pressure surface cleaning process parameters of the aircraft engine fan blade,combined with the ultrasonic cleaning process of the pressure surface of the aircraft engine fan blade,the overall hardware system and related software system of the automatic cleaning and lubrication equipment of the aircraft engine fan blade pressure surface are designed.Finally,in view of the current manual detection method of blade pressure surface cleaning effect,which is characterized by large standard difference,low efficiency and low degree of automation,image processing method is adopted to detect the cleaning effect of aircraft engine fan blades,so as to realize the standardization and digitalization of the cleaning effect detection.The cleaning parameters are obtained by comparing the current common parameter optimization algorithm and the mixing algorithm,and it is verified that the BP-SA-GA mixing algorithm can really improve the cleaning effect and improve the cleaning efficiency,so as to provide a reliable basis for the automatic cleaning of the pressure surface of the aircraft engine fan blade.