Abstract

Existing protocols (e.g., ASTM D 1275-B standard test method) applied to detect and monitor sulfur corrosion in transformer insulating oils are imprecise as it depends on visual observation. As a solution, thin-film sacrificial copper strips are proposed as a corrosive sulfur sensor. A two-level factorial design is utilized to investigate the significant effect of area and thickness upon the sensor’s transformation resistance values. Next, a regression model is developed to estimate the sensor’s transformation resistance values as functions of area and thickness. The resultant outputs from the two-level factorial design revealed that area, as a variable, exhibited higher significance at 90.19%, compared to either thickness or interaction between area and thickness. The proposed regression model obtained from two-level factorial design is significant in describing the trend displayed by the sensor’s transformation resistance values. Finally, this paper details the clear correlation between the sensor’s transformation resistance values and elemental sulfur concentration.

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