基于文本分类的火控系统故障诊断研究

Research on Fault Diagnosis for Fire Control System Based on Text Classification

以某型装备火控系统为例,将文本分类技术同基于支持向量机的故障诊断方法结合,通过建立故障特征词库、采用布尔模型形成故障向量库,运用SVM算法对该装备火控系统的故障进行了训练评估,并获得了较理想的试验结果,最大识别率达到了70%。通过这种方法进行装备故障诊断,对于装备维修特别是战场抢修有极其重要的意义,使维修人员从繁琐的仪器检查中解脱出来,通过已有的故障库快捷简便地确定故障检测点,实现装备的快速抢修,为抢夺战场主动权创造有利条件。

Taking the fire control system of some equiment as an example, combining text classification technique and fault diagnos method based support vector machines, through founding fault feature thesaurus, generating fault vector thesaurus by adopting Boolean Models, trainning and evaluating fault of fire control system for this equipment by SVM algorithm, the better test result was acquired, whose fault recognition rate reached up to 70%. For equipment maintenance, especially for battlefield repair, it was very significant that making fault diagnosis for equipment with this method. By this method, maintenance personals was extricated themselves from cockamamiecheck with instrument, so that fault ispecting points were confirmed in faults thesaurus rapidly and conveniencely, and rush repairs for equipment would come true, which would create favorable conditions for snatching the initiative on the battlefield.