风电机组故障智能诊断技术及系统研究

被引：34

作者：

彭华东 ^{[1
]}

陈晓清 ^{[1
]}

任明 ^{[1
]}

杨代勇 ^{[1
]}

董明 ^{[1
,2
]}

机构：

[1] 电力设备电气绝缘国家重点实验室西安交通大学

[2] 西北电网有限公司博士后工作站

来源：

电网与清洁能源 | 2011年 / 27卷 / 02期

关键词：

风电机组; 状态监测; 故障诊断; 神经网络;

D O I：

暂无

中图分类号：

TM315 [风力发电机];

学科分类号：

080801 ;

摘要：

风电机组的状态监测和故障诊断是保证机组长期稳定运行和安全发电的关键。基于风电机组的基本结构,介绍了机组的故障类型和机理,论述了实际应用中机组的状态监测和故障诊断技术;基于BP神经网络的原理和优点,深入讨论了如何应用人工神经网络构建风电机组智能诊断系统,并给出了可行的系统设计方案和软件实现流程图。

引用

页码：61 / 66+70 +70

页数：7

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