摘要
利用主元分析方法对舰船机械设备运行过程信息提取特征信号,采用Q和HotellingsT2统计量生成控制限,通过对过程变量贡献图的分析确定故障源。对实验室舰船舱段模型内机械设备的试验结果分析表明:主元分析故障诊断模型能够有效地对设备状态进行监测,并能较准确地诊断设备运行中发生的故障。
The feature signals of operational machine on ship were extracted by the principal component analysis method. The control limits were built with Q and Hotelling's statistic. In this way the fault sources could be identified through analyzing the figure of variable contribution. The experiment of machine equipments in ship model results showed that PCA is an efficient method to monitor the condition of machine,and can detect the operational machine's faults exactly.
出处
《船海工程》
2009年第1期93-97,共5页
Ship & Ocean Engineering
基金
国防"十一五"预研项目(51310030201)
国家自然科学基金(50775218)
关键词
多元统计过程控制
故障诊断
主元分析
过程监控
multivariate statistical process control
fault diagnosis
principal component analysis
process monitor