【摘要】 时间序列的分析方法在许多工程领域得到了很多成功的应用 ,通过对实际的汽轮机组平稳过程振动数据的相关分析 ,对汽轮机组振动数据平稳时间序列的AR(p)模型的识别和建模进行了初步的探讨。为了验证AR(p)模型对于汽轮机组平稳过程振动数据分析的有效性 ,分别采用AR(10 )、AR(2 0 )和线性回归的模型 ,利用实际数据进行预测实验 ,实验结果表明利用AR(p)模型的预测效果明显优于传统的线性回归预测方法的预测结果 ,从而验证了AR(p)模型对汽轮机组平稳运行过程振动分析的有效性。更多还原

【Abstract】 Through the correlation analysis of vibration data of turbine unit’s stable process, the identification and modeling of the turbine’s unstable process with AR(p) model have been discussed. In order to verify the validity of this kind of model, three trend prediction experiments, which respectively use AR(10), AR(20) and linear regression analysis method, have been designed according to the fieldwork data. The results of the experiments show that the trend forecast results of AR(p) is much better than that of linear regression analysis method. A conclusion can be made that AR(p) model is effective way to analyze the vibration data of turbine unit’s unstable process.更多还原