Successive projections algorithm based ridge regression analysis to predict of breakdown voltage for transformer oils samples in power industry using ATR-FTIR spectroscopy

Power transformers are critical components of transmission systems. They are a critical component of any transmission system or power generation system. The transformer’s quality is calculated based on the oil chemical, electrical, and physical properties. It is dependent on the transformer’s ability to withstand defeat. Specific essential tests must be performed on insulating oil samples [۱]. The current study proposes a novel analytical method for calculating the breakdown voltage (BV) of transformer oil samples considered as a significant method to assess the safe operation of power industry. To determine the ATR-FTIR spectroscopy analysis of transformer oil samples, ۳۳ samples from various Iranian oils from operation transformer on field were replicated ۳ times and subjected to chemometric analysis. As a result, the root mean square error (RMSE) and correlation coefficient for the training and test sets of oil samples are also calculated. In the SPA- ridge regression method, the squared correlation coefficient (R۲pred) and root mean square prediction error (RMSEP) are ۰.۹۸۹۱ and ۰.۲۸۷۴, respectively. The proposed method may be used in place of the commonly used ASTM standard procedures and provided a reliable method for predicting breakdown voltage analysis in oil samples in power industry.