A Novel Approach of Transformer Oil Quality Analysis Using Image Processing

Electrical energy is the paramount need in a nation’s development. To cater for large demand for electricity there is a need for reliable and proficient power system. For a power system to work reliably, the role of Transformers is critical. Health of the transformer mainly depends on its insulation. Among the different insulating material used in transformers, mineral oil is the most widely used as insulating medium in oil filled transformers. The performance of the transformer depends on the quality of the insulating oil. Hence, the oil quality analysis becomes essential. Traditionally chemical diagnostic criteria are used for oil quality evaluation. However, this conventional method is expensive and time consuming. Extensive experimental evaluation has been fruitful to establish the acidity and tanδ of the transformer oil. Here, we are proposing Image processing technique to estimate the oil properties, which is inexpensive and effective technique. Namely Texture Entropy is extended to compute the Neutralization Number (NN) or Acidity and tanδ (Dissipation factor). Further they compared.