基于卷积神经网络的柴油发电机健康评估

柴油发电机是水面无人艇(USV)的核心设备之一,其健康状态直接影响USV的航行状态。为了保证USV的健康航行,提出了一种基于卷积神经网络的健康评估方法。该方法以发电机基本参数作为特征参数,建立健康评估模型,得出发电机健康评估状态。以百吨级电力推进USV柴油发电机为实例进行模型验证,得出发电机的健康状态转换关系及健康阈值为0.03。与常用的BP神经网络进行对比,该模型的收敛速度、识别速度、评估准确率都有明显提升。

Health Assessment of Diesel Generator Based on Convolution Neural Network

Diesel generator is the core equipment of the surface unmanned boat (USV),its health status directly affects the navigation state of USV.In view of the health assessment of diesel generators,a method based on the convolution neural network was proposed.The health assessment model is established by using the basic parameters of the generator as the characteristic parameters,and the state of the motor health assessment is set out.Taking 100 ton electric propulsion USV diesel generator as an example,the model was verified,and the health state transition relationship and the health threshold of the starting motor are 0.03.Compared with the commonly used BP neural network,the convergence speed,recognition speed and accuracy of the model are obviously improved.