电磁发射系统改进FAHP-神经网络健康评估方法

准确定量评估电磁发射系统发射前的健康状态意义重大。针对模糊层次分析方法(Fuzzy Analytic Hierarchy Process, FAHP)在评估电磁发射系统串行结构同级元素健康值时存在较大偏差,且无法适用系统非线性变权重需求的缺陷,提出改进FAHP-神经网络方法。通过在计算同级元素健康指数时构造能够满足串行结构健康评估的非线性函数进行计算,并在数学上证明该方法的有效性；通过引入神经网络系统,在已有的系统先验信息和测量数据的基础上训练模型解决系统健康评估非线性变权重需求。基于电磁发射系统脉冲成形网络系统建立健康评估模型,开展评估试验。结果表明,提出的方法健康评估精度较高,在各种系统健康状态下,评估结果均符合系统实际的健康状况；对比传统的FAHP,提出的改进方法评估精度大幅提升,且在评估试验中没有出现故障误报和漏报的情况,从而验证了提出方法的可行性和工程实用价值。

Improved FAHP-neural network health evaluation method for electromagnetic launch system

It is of great significance to accurately and quantitatively evaluate the health status of electromagnetic emission system before launch. Focusing on the large deviation of health value in evaluating the serial structure of electromagnetic emission system when applying the FAHP(fuzzy analytic hierarchy process) method, which fails to meet the requirement of nonlinear variable weight of the system, an improved FAHP-neural network health assessment method was proposed. The improved method can be calculated by constructing a nonlinear function that can satisfy the serial structure health assessment when calculating the health index of the same-level elements, and the effectiveness of the method was testified from the aspect of mathematics. On the basis of the known prior information and measured data, the neural network model was introduced to solve the nonlinear variable weight requirement of system health evaluation. An improved health evaluation model based on the pulse forming network system of an electromagnetic launch system was established and evaluation experiments were carried out. The results show that the proposed evaluation method has high assessment accuracy, and the results are in line with the actual health status of the system under various health conditions. Compared with the traditional FAHP method, the proposed method can greatly improve the accuracy of evaluation, and have no error and leakage, which verifies the feasibility and practicability of the method.