基于SDG模型的风力发电机故障诊断方法  

FAULT DIAGNOSIS APPROACH FOR WIND TURBINE BASED ON SIGNED DIRECTED GRAPH

作　　者：刘友宽 苏适 杨洋 尧俊平 

机构地区：[1]云南电力试验研究院(集团)有限公司电力研究院,昆明650217

出　　处：《机械强度》2013年第5期583-588,共6页Journal of Mechanical Strength

摘　　要：基于符号有向图SDG(Signed Directed Graph)的故障诊断方法在化工、钢铁等大型工业系统中已广泛运用。针对传统的风力发电机组故障诊断方法诊断耗时长、诊断过程复杂等缺点,提出基于符号有向图(SDG)模型的风力发电机组故障诊断方法。研究风力发电机组结构,建立风力发电机组SDG模型。利用关联算法通过风力发电机组分布输入矩阵对候选故障源节点进行筛选、排序。案例诊断结果表明,该方法能及时有效地检测风力发电机组的故障,提高风力发电机组故障诊断的效率。Fault diagnosis based on SDG（ Signed Directed Graph） method has been widely used in the chemical, steel and other large industrial systems. The traditional fault diagnosis methods for wind turbines are time consuming and of complex process shortcomings. Firstly, composition of the wind turbine is studied. Secondly, signed directed graph model for the fault diagnosis of wind turbine is formulated. Finally, the failure source candidates are screened and ranked by the association algorithm according to the distribution matrix for wind turbines. The case studies show that the proposed method is effectively and promptly in detection faults of wind turbine. Moreover, efficiency of fault diagnosis for wind turbine is improved.

关 键 词：符号有向图 故障诊断 风力发电机组 风力发电 数学模型 

分 类 号：TP306.3[自动化与计算机技术—计算机系统结构]