一种多参数耦合关联性数据分析方法

A Multi-Parameter Coupled Correlation Data Analysis Method

为分析发动机组件性能降低引起的故障与哪些特征参数有关,找到重要的影响因素以便于进一步开展设计试验验证等工作,对收集到的发动机组件的所有测量数据进行了数据分析。对可能引起故障的众多参数进行重要度排序,识别出影响性能下降的重要因素,利用挑选出的关联度高的重要特征参数进行故障建模和预测,并应用于多个组件的飞行和试验数据的分析中,形成了一种多参数耦合关联性数据分析方法。由于数据量所限,目前的研究工作主要集中在多参数小数据量的故障参数分析、识别、建模和预测等方面,后续可进一步添加生产加工、试验飞行等数据进行进一步分析和验证。

In order to identify and analyze the parameters relevant to the faults caused by the performance degradation of the engine components and to find out the key influencing factors in order to conduct further works such as design tests and verification,we ran data analysis on all collected measurement data of engine components.Specifically,we sorted the importance of various parameters that may cause fault and identified the important factors that affect performance degradation.The identified important factors are used in the analysis of flight and test data of many modules to form a method for multi-parameter coupling and correlation data analysis.Due to the limited amount of data,the research works of fault parameter analysis,identification,modeling,and prediction are mainly concentrated on the multi-parameter with a small amount of data;we suggest that further analysis and verification of production,processing,testing,and flight data should be added.