摘要
针对在线监测电容型设备的绝缘特性变化规律以及受外界因素影响的情况不明确,难以发现其变化来确定设备绝缘状况的问题,提出了基于小波能谱熵理论的数据规律分析方法。该方法利用小波分析具有时频局部化的特性和信息熵对系统状态表征的特性,将小波分析与熵结合起来对信号进行特征挖掘。计算小波能谱熵作为系统的特征参数来识别不同信号的变化趋势并将与tanδ变化最接近的因素作为主导因素来分析。实例分析表明,上述熵值能够反映在线监测tanδ和外界因素的系统变化,以此为参量来分析趋势并进行故障诊断是一种行之有效的方法。
Under the complicated locale circumstances, the insulation identity disciplinarian of on-line monitoring capacitive equipment and influence of some outside factors are ambiguous. In order to root out the change trend of tanδ to make sure insulation status and construe data regularity, a novel method is introduced in the paper. Wavelet entro- py combines wavelet analysis with information entropy theory to accomplish signal characteristic excavating by adop- ting the time-frequency localization ability of wavelet analysis and the ability of entropy to token system state. Wave- let energy entropy is calculated as system characteristic parameter and then distinguish from trend variety of different signals. Using the dominant variable which is the adjacent quantity to analyze tanδ It is verified by example results that wavelet entropy can reflect the system change of tanδ on-line monitoring data and environment factors. The way is effective for fault diagnosis by trend change analysis with wavelet energy entropy of upon parameter.
出处
《华北电力技术》
CAS
2010年第2期6-9,共4页
North China Electric Power
关键词
小波分析
信息熵
趋势
TANΔ
在线监测
wavelet transform
information entropy
trend
tanδ
on-line monitoring
