基于多方法组合诊断模型的大型变压器故障诊断

电力变压器故障征兆与故障原因之间的关系错综复杂,而单项诊断方法由于信息特征独特、考虑角度单一,往往很难满足故障诊断的要求.因此,提出了在变压器故障诊断中采用多种方法组合诊断的思想,以克服单种方法的偏好对最终诊断结果所产生的影响.该方法采用模糊C均值聚类(FCM)诊断法、BP神经网络诊断法、粗糙集理论故障诊断法和IEC 60599推荐的三比值法这4种诊断方法作为独立的单项诊断方法,根据各自诊断的误判率,按照诊断误差平方和最小的原则计算出各个诊断方法的最优权重,形成最优投票组合模型,再求出最大发生概率的故障类型.诊断结果表明,该方法与单项方法相比,大大降低了诊断误判的风险,提高了故障诊断的准确率,增强了故障诊断的稳健性.

Large Power Transformer Fault Diagnosis Based on a Diagnosis Model Combined with Several Methods

The relationships between fault symptoms and fault reason of oil-immersed electrical power transformer are very complicated.One single fault diagnostic method cannot always achieve the true result due to its particular information used for diagnostic and specific approaches used.Therefore,a new algorithm,which synthesizes several conventional transformer fault diagnosis methods,is put forward to eliminate the influence of a single method's preference on the final diagnosis result.Fuzzy C-means clustering(FC...