航空电机温升智能预测研究

Research on Forecast of Surface Temperature Rise for Aviation Electric Motor Based on Artificial Intellectual

针对航空电机发热、散热受电机功率、结构以及由于海拔高度改变带来的大气温度、粘度、压力变化等众多因素影响和温升模型难以准确建立的问题,通过已有试验数据,建立起遗传算法—神经网络表面温升模型。实验表明,该模型实现了对航空电机温升的智能预测。

There are so many factors power, structure, atmosphere temperature also influenced with the height above sea le affect the aviation electric motor temperature rise, such as , viscosity and pressure variety. The last three parameters are vel changes, so the model of motor temperature rise could not established accurately. This paper sets up a mathematical model to calculate the surface temperature rise of aviation electric motor based on a experiments data and artificial neural network-genetic algorithm. The experiment results demonstrate that this model realizes the forecast the temperature rise.