舰载武器智能自适应诊断测试技术研究

Research on intelligent adaptive diagnostic testing technology for ship weapons

传统武器故障诊断和测试依托于人员经验和测试仪器,难以适应现代化舰船的故障测试要求。本文对大数据技术和自适应诊断测试技术进行研究,设计舰船武器智能自适应诊断测试系统,重点设计了舰船武器故障特征提取模块和诊断测试模块。使用支持向量机对故障特征进行分类,通过原始数据融合、故障特征融合以及决策融合,系统根据采集的故障特征信息可以作出综合性判断,因而具有较高的可靠性。

The fault judgment and maintenance of ship weapons is crucial to ensuring the combat capability of ships.Traditional weapon fault diagnosis and testing rely on personnel experience and test instruments,which is difficult to adapt to the fault testing requirements of modern ships.This paper elaborates and analyzes big data technology and adaptive diagnostic test technology,designs an intelligent adaptive diagnostic test system for ship weapons,and focuses on designing a fault feature extraction module and a diagnostic test module for ship weapons.The support vector machine is used to classify the fault characteristics,and through the original data fusion,fault feature fusion and decision fusion,the system can make a comprehensive judgment according to the collected fault feature information,so it has high reliability.