基于偏最小二乘法的风力发电机组故障诊断方法研究

Feng Lv, Zeyu Zhang, Kun Zhai, Xiyuan Ju
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引用次数: 2

摘要

针对大型风力发电机组系统结构复杂和运行过程变量的特点,提出了一种基于多元统计的故障诊断方法。该数学模型基于偏最小二乘法,不需要复杂的模型。PLS算法通过原始数据建立输入输出变量之间的关系,得到监测模型。计算机仿真结果表明,该方法能有效地降低数据维数,实现故障诊断。与主成分分析相比,PLS更充分地利用了样本空间信息,有效地提高了故障诊断的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on fault diagnosis method of wind turbine based on partial least square method
In view of the complex structure of large wind turbine system and the characteristics of the operation process variable, this paper puts forward a fault diagnosis method based on multivariate statistics. The mathematical model based on partial least squares (PLS) without the need of complex model. Through the original data PLS algorithm built the relationship between input and output variables and get the monitoring model. Computer simulation results show this method can effectively reduce the dimension of data and realize the fault diagnosis. Compared with PCA, PLS are more fully use the sample space information, improve the accuracy of fault diagnosis effectively.
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