摘要
针对航空发动机结构复杂、运行工况恶劣、监测参量众多等因素,导致对其健康状态难以准确识别问题,提出了基于主元分析的健康状态识别监测方法;首先,对通过专业试验平台采集的试验数据进行预处理,在此基础上,采用主元分析方法对其进行深入分析,运用主元贡献率计算主元个数,并据此构建状态识别模型,确定T2统计量和SPE统计量;以确定的T2统计量和SPE统计量作为航空发动机气路系统状态健康与异常识别的标志,对航空发动机气路系统健康与否进行识别研究;研究结果表明,该方法可以很好识别出航空发动机气路系统的运行状态,对航空发动机实际运行状态的识别具有重要的工程应用价值。
It is difficult to identify the aero engine health status problem accurately for complicated structure,bad operation condition,a lot of monitoring parameters and other factors,so the monitoring health state recognition method is presented based on principal component analysis.Firstly,the paper has been standardized treatment for these data which come from the professional test platform.Second,the paper has been the principal component analysis,and this can calculate the number of principal components through the principal component contribution.Therefore,this can construct a state recognition model,and can determine.Lastly,the paper takes the statistics of T2 and statistics of SPE as the sign for the aero engine gas path system health status and anomaly recognition.So the paper uses the statistic of T2 and statistic of SPE to finish the research of the aero engine gas path system health identification.The study result shows that the method can well identify the running state of the aero engine gas path system.And this method has important engineering application value for the actual operation of the aero engine and the recognition of the state.
出处
《计算机测量与控制》
2015年第11期3849-3852,共4页
Computer Measurement &Control
基金
辽宁省自然科学基金资助项目(2014024003)
航空科学基金资助项目(2010ZD54012)
国防技术基础科研项目(Z052012B002)
关键词
航空发动机
主元分析
T2统计量
SPE统计量
健康状态识别
aero engine
principal component analysis
statistic of T2
The statistic of SPE
health state recognition
