航空专用离心喷头雾化性能试验与影响因子研究

针对航空施药模式下喷头喷雾参数与雾化参数关系不明确的问题,本文结合喷雾性能测试与建立代理数学模型,讨论了CN1215型航空专用离心喷头主要工作参数对雾滴体积中径(Dv50)、喷幅的影响规律。标定了离心喷头喷雾参数对应的供液系统工作参数,在室内无风环境下测试了不同喷头流量(100～350 m L/min)、喷头转速(8 000～10 000 r/min)下的雾滴中径及喷幅。以喷头喷雾参数(喷头流量、喷头转速)作为试验因素,以航空离心喷头雾化后雾滴体积中径Dv50、对应喷幅为响应因数,分别采用四阶响应面法(Response surface method,RSM)、克里金法(Kriging)、椭球基神经网络(Ellipsoidal basis function neural network,EBFNN) 3种数学方法逼近试验因素与响应因数之间的关系,建立了喷头雾化参数(Dv50、对应喷幅)与喷头喷雾参数(喷头流量、喷头转速)之间的代理数学模型,3种代理模型对Dv50的决定系数R~2分别为:0. 705、0. 718、0. 925,3种代理模型关于Dv50对应喷幅的决定系数R~2分别为:0. 819、0. 890、0. 930。基于EBFNN隐式代理数学模型建立了两个雾化参数的响应面,实现了喷雾参数影响下的雾滴Dv50、喷幅的快速预测。

Atomization Performance Test and Influence Factors of Aviation Special Centrifugal Nozzle

Aiming at the unclear relationship between spray parameters of nozzle and atomization parameters in the aviation spray mode, and considering the urgent need of precision aerosol spray, spray performance test and agent mathematical model modeling method were combined to discuss the influence of main working parameters on atomized particle size and spray width for the CN1215 special aviation centrifugal nozzle. The operating parameters of the liquid supply system corresponding to the spray parameters of the centrifugal nozzle were calibrated, and then the variation laws of droplet size and spray width under the influence of the working parameters (flow rate range was 100~350mL/min, nozzle rotating speed was 8000~10000r/min) were also analyzed in an indoor windless environment. Secondly, taking the spray parameters of the nozzle (nozzle flow, nozzle speed) as the test factor, and taking the droplet diameter (Dv50) and the spray width corresponding to droplet diameter (Dv50) as response factor, three kinds of mathematical methods, including fourth order response surface method (RSM), Kriging method and ellipsoidal basis function neural network (EBFNN), were used to approximate the relationship between experimental factors and response factors respectively. The agent mathematical models between the nozzle atomization parameters (Dv50, and corresponding spray width) and nozzle operating parameters (nozzle flow, nozzle speed) were established. The decisive coefficients R2 of the three agent models for the particle size Dv50 were 0.705, 0.718 and 0.925, and the decisive coefficients R2 of the three agent models for the Dv50 corresponding spray width were 0.819, 0.890 and 0.930, respectively. Based on the EBFNN implicit proxy mathematical model, the response surface of two atomization parameters was established, the rapid prediction of droplet Dv50 and spray width under the influence of working parameters was achieved. Based on the EBFNN implicit proxy mathematical model, the response surfaces of two atomization parameters were established, which realized the rapid prediction of droplet Dv50 and spray amplitude under the influence of spray parameters. It was of great significance for accelerating the development of aviation precision pesticide application.