一种在轨卫星控制分系统风险等级预测方法

Prediction of Risk Levels for On-Orbit Satellite Control Subsystem

使用2009至2020年某卫星控制分系统质量案例数据,提出一种基于BP神经网络的在轨卫星控制分系统技术风险等级预测模型。挖掘历史相关数据,建立在轨卫星控制分系统风险评价体系。排除风险源中的冗余信息,将重要信息数据离散化后,以BP神经网络进行训练,最终得到在轨卫星控制分系统风险等级预测模型。通过试验验证该模型可准确有效预测在轨卫星控制分系统风险等级,为卫星在轨风险控制提供支持。

Based on the quality data of a certain satellite control subsystem from 2009 to 2020,a technical risk level prediction model for the on-orbit satellite control subsystem is proposed based on BP neural network.The risk assessment system of the on-orbit satellite control subsystem is established by mining historical data.After eliminating the redundant information in the risk source,the important information is discretized and trained by the BP neural network.Finally,the risk level prediction model for the on-orbit satellite control subsystem is obtained.The experimental results show that the model can accurately and effectively predict risk levels for the on-orbit satellite control subsystem,and provide support for on-orbit satellite risk control.