摘要
文章对S11-M-500/35kV变压器A相绕组进行连续5次短路冲击试验(B、C两相未单独进行冲击试验),使A相绕组产生较其他两相更严重的形变,获取短路冲击前后变压器A相绕组对应油箱壁的振动数据。通过变压器油箱壁振动信号分析变压器绕组的变形程度,利用小波包分解原理,将振动信号分解到不同频段中,计算各频段的能量熵值,得出不同程度的绕组形变对能量熵值变化的影响。试验结果表明:与离线短路电抗法判断绕组形变相比,振动分析法小波包能量熵特征提取方法不但具有在线诊断绕组故障的优点,且更灵敏的体现出绕组状态变化,对及时反映绕组形变,对带电或在线监测判断绕组变形故障具有重要意义。
Five short-circuit impact tests are done consistently on the A phase winding of the S11-M-500/35 kV transformer(both B and C phase are not independently tested) to make the deformation of A phase winding more serious than the other two phases,obtaining the vibration data of A phase winding before and after the impact tests.The deformation degree of transformer winding is analyzed based on the of vibration signals of transformer oil tank.On the basis of wavelet packet decomposition principle,vibration signal is decomposed into different frequency bands and the energy spectrum entropy of different frequency bands are calculated,obtaining the effect of different degree of winding deformation on energy entropy change.Experimental results show that compared with the method of off-line short-circuit impedance,the proposed method not only has the advantages of online winding fault diagnosis,but also can reflect the change of the winding state more sensitive,which is significant for reflecting the winding deformation in time and online winding fault diagnosis.
出处
《供用电》
2015年第11期59-65,共7页
Distribution & Utilization
基金
国家电网公司科技项目(GY71-14-009):电力变压器在线多信息融合状态评估方法研究~~
关键词
变压器
绕组
振动
小波包
能量熵
transformers
winding
vibration
wavelet packet
energy entropy