Improved matter-element model based on cloud model and its application in power transformers fault diagnosis

Because matter-element theory´s shortcoming in ignoring the uncertainty of boundary values when setting up a fault diagnosis model, the diagnosing results are deviated from the actual situation. Considering cloud model theory can be applied to represent the uncertainty of the boundary, we combine cloud model theory with matter-element to propose a new diagnosing model. Meanwhile, by using data such as the concentration of dissolved gases, gas production rate and the ratio between gases in oil, the proposed diagnosing model is tested. Compared with other techniques for transformer diagnosing with case analysis, the new proposed model has a higher diagnosing precision.