摘要
船舶柴油机是船舶的有效动力,涡轮增压系统能够使得船舶燃料得到充分的利用,节省航行成本。对涡轮增压系统进行及时的故障诊断非常重要。本文通过改进传统的模糊聚类算法,得到模糊核聚类算法,并将其应用于船舶涡轮增压系统故障检测中,最后通过对比实验说明本文算法识别率高、检测消耗的时间少。
Marine diesel engine is the effective power of the ship. The turbocharger system could make full use of the ship fuel,saving the cost of navigation. Fault diagnosis timely for turbocharging system was very important. This paper improved the traditional fuzzy clustering algorithm and got fuzzy kernel clustering algorithm. And its was applied on the ship turbocharger system fault detection. Finally through the contrast experiment showed that the algorithm had high recognition rate,less time consumption of detection.
出处
《舰船科学技术》
北大核心
2016年第14期52-54,共3页
Ship Science and Technology
基金
河南省"十二五"规划资助项目([2014]-JKGHC-0188)
关键词
模糊聚类
涡轮增压
故障检测
fuzzy clustering
turbocharging systems
fault detection
