基于改进WNN的作战飞机维修保障能力评估方法  

An Assessment Method of Maintenance and Support Capability of Combat Aircrafts Based on Improved Wavelet Neural Network

作　　者：游亮 王莉莉[1] 蔡忠义 魏杨沁 金建刚 YOU Liang;WANG Lili;CAI Zhongyi;WEI Yangqin;JIN Jiangang(Equipment Management and Unmanned Aerial Vehicle Engineering College,Air Force Engineering University,Xi’an 710051,China)

机构地区：[1]空军工程大学装备管理与无人机工程学院,西安710051

出　　处：《火力与指挥控制》2024年第10期74-81,共8页Fire Control & Command Control

摘　　要：针对现有作战飞机维修保障能力评估中评估结果误差较大、不确定性较高等问题,提出一种基于改进小波神经网络的飞机维修保障能力评估方法。依据IPO&E模型建立飞机维修保障能力评估指标体系;利用麻雀搜索算法提高小波神经网络的收敛稳定性与评估准确性;基于分级量化理论对原始数据进行处理,并开展作战飞机维修保障能力评估。算例分析表明,所提方法的评估结果与收集到的维修保障能力评估数据仅有2.4%误差,稳定性优于其他神经网络,可为作战飞机维修保障能力评估提供可行方法。Aiming at the problems of large errors and high uncertainty in the evaluation results of maintenance support capability of the existing combat aircrafts,a method of maintenance support capability evaluation method of aircrafts based on improved wavelet neural network is proposed.Based on IPO&E(Inputs,Process,Outputs and Environments,IPO&E)model,the evaluation index system of aircraft maintenance support capability is established.The sparrow search algorithm is used to improve the convergence stability and evaluation accuracy of wavelet neural network.Based on the hierarchical quantification theory,the original data are processed and the maintenance support capability of combat aircrafts is evaluated.The Example analysis shows that there is only 2.4%error between the evaluation results of the proposed method and the collected maintenance support capability evaluation data,which is more stable than that of other neural networks,and can provide a feasible method for maintenance support capability evaluation of combat aircrafts.

关 键 词：能力评估 小波神经网络 IPO&E模型 飞机维修保障 

分 类 号：E91[军事]