基于有向无环图支持向量机的水轮发电机组故障诊断模型  

Fault Diagnosis Model for Hydropower Generating Unit Based on Directed Acyclic Graph Support Vector Machine

作　　者：兰飞[1] 唐玲[1] 

机构地区：[1]广西大学电气工程学院,广西壮族自治区南宁市530004

出　　处：《电网技术》2010年第2期115-119,共5页Power System Technology

基　　金：广西教育厅科研基金资助项目(200808LX163);广西大学科研基金项目(DD020015)的资助

摘　　要：提高水轮机组的状态监测与故障诊断系统的准确性和及时性,对电力系统的安全运行具有重大意义。针对神经网络收敛速度慢、容易陷入局部最优解等不足,提出了一种基于有向无环图支持向量机方法的水轮发电机组故障诊断方法。该方法能有效解决小样本、高维数、非线性等问题,从而能在较短的时间内准确地诊断故障。It is significant for secure operation of power grids to improve both accuracy and timeliness of status monitoring and fault diagnosis system for hydropower generating sets. To remedy the defects of neural network such as slow convergence rate and easy to sink into locally optimal solution, a fault diagnosis method for hydropower generating sets, which is based on directed acyclic graph support vector machine, is proposed. The proposed method can effectively solve such problems as small sample, high dimension and nonlinearity, thus the fault of hydropower generating sets can be accurately diagnosed in a shorter time period.

关 键 词：水轮发电机组 故障诊断 支持向量机 有向无环图 多分类支持向量机 

分 类 号：TM612[电气工程—电力系统及自动化]