基于BP神经网络的导弹故障自动诊断研究

精确制导空空导弹是一个复杂系统，及时、准确的识别和诊断导弹故障是化解风险的重要措施。由于导弹故障模式复杂，对其故障进行识别和诊断的难度很大。文中以某型空空导弹测试问题为例，提出一种基于BP神经网络算法的导弹故障自动识别与诊断技术。通过对导弹测试数据的采集和整理形成数据样本，利用神经网络系统的学习和判断能力自动识别及诊断导弹故障，并使用Matlab神经网络工具箱进行仿真验证。验证结果证明，该技术能够快速、准确的识别和诊断导弹故障。

Research on a Technology of Missile Fault Automatic Diagnosis Based on BP Neural Network

Given that the precision-guided airborne missile is a sophisticated system, timely and accurate fault identification and diagnosis for missiles are crucial measures to address and prevent risks. Due to the complexity of the missile failure mode, it is difficult to identify and diagnose them. Taking a typical testing problem of a airborne missile as an example, this paper proposed a BP-neural network-based approach of automated fault identification and diagnosis for missiles. By collecting and sorting the missile test data, a data sample was formed. The learning and judgment ability of the neural network system was used to automatically identify and diagnose missile faults. A Matlab neural network toolbox was adopted to verify stimulation for this approach, which showed that the technology could identify and diagnose missile faults quickly and accurately.