基于关联规则的汽轮机叶片振动研究

研究了汽轮机叶片振动测试的数据采集方法,采用光栅光纤及电阻应变片分别测量手段进行叶片振动实验。模拟汽轮机运行状态进行了转子运行实验,提出了实验方案,通过实验测试采集了振动信号数据集。应用Apriori算法对数据集进行分析,使用WEKA平台进行数据处理,定位了转子在这一状态下的易损部位,并发现了与叶片振动相关的关联规则。研究表明,应用Apriori算法可有效发现汽轮机叶片振动问题,将其应用于更多工况下汽轮机运行振动优化具有一定指导作用。

Vibration of Steam Turbine Blade Based on Association Rules

The data collection method of turbine blade vibration test was studied, steam turbine blade vibration test was carried out by using the grating fiber and resistance strain gauge measurement method. Rotor running experiment was finished by simulating steam turbine operation state, the experimental program was put forward. Vibration signal data set was collected on the basis of experi-mental. Apriori algorithm was applied to analyze the data sets by using WEKA platform. Steam turbine rotor vulnerable parts was located in this state, and the blade vibration associated with association rules was found. Research result show the turbine blade vibration prob-lems can be discovered by applying Apriori algorithm, it has the important effect of turbine operational vibration optimization.