摘要
气体绝缘组合开关作为电力系统中的关键组件,其安全稳定运行是保障电力系统安全稳定的必要基础。针对现有诊断方法面对不平衡小样本数据表现不佳的问题,提出一种基于加权核极限学习机(WKELM)的GIS机械故障诊断模型。该方案先对GIS声音信号进行预处理并计算短时能量谱,再提取短时能量和能量熵等特征,构建WKELM机械故障诊断模型,挖掘特征向量与GIS运行状态之间的映射关系。实验表明,所提出的方法能有效提高面对不平衡小样本数据的诊断性能。
As a key component in the power system,the safe and stable operation of gas-insulated combined switch(GIS)is a necessary foundation to ensure the safety and stability of the power system.Aiming at the problem of poor performance of existing diagnostic methods in the face of unbalanced small sample data,this paper proposes a GIS mechanical fault diagnosis model based on WKELM.In this scheme,the GIS sound signal is preprocessed and the short-term energy spectrum is calculated,and then the short-time energy and energy entropy as features are extracted,the WKELM mechanical fault diagnosis model is constructed,and the mapping relationship between the feature vector and the GIS running state is mined.Experiments show that the proposed method can effectively improve the diagnostic performance in the face of unbalanced small sample data.
出处
《工业控制计算机》
2024年第9期90-92,共3页
Industrial Control Computer
