摘要
机组状态参数的趋势分析及计算机表达是影响在线故障诊断的重要因素。文中运用奇异谱理论对状态参数的趋势进行了分析 ,运用人工神经网络完成对机组状态参数典型趋势的在线识别。该方法可以对机组状态参数 (如振动、温度、压力等 )进行有效的识别 ,为水轮机组的状态分析、状态评估和预测提供有效的辅助分析手段 ,从而为水电厂状态维修提供了参考。
Trend analysis and computerized expression of state parameters are two important factors in the on-line fault diagnosis. Singular spectrum theory is used in this paper to analyze the trend of state parameters. While the artificial neural network (ANN) is applied in the on-line identification of typical trends of state parameters. This method can identify the state parameters effectively, such as vibration, temperature, pressure and so on. So it could be an effective assistant analytical method for state analysis, state assessment and prediction of hydraulic generators as well as could be a powerful reference of state maintenance for hydroelectric plant.
出处
《电力系统自动化》
EI
CSCD
北大核心
2001年第14期29-32,共4页
Automation of Electric Power Systems
关键词
水轮发电机组
状态参数
在线识别
人工神经网络
hydroelectric plant
state maintenance
singular spectrum theory
artificial neural network
trend analysis
on-line identification
