Increasing the Efficiency of Power Transformer Condition Diagnostics

In recent years, the understanding of the efficiency of technical diagnostics of electrical equipment has increased significantly. The main reasons for this are that more than half of the equipment in operation has exhausted its estimated service life; the rate of equipment aging exceeds the rate of its renewal due to limited funds for technical maintenance, as well as due to the transition to repairs based on technical condition. High quality and timely diagnostics improve the objectivity of assessing the technical condition of high-voltage electrical equipment. All this allows planning and timely execution of necessary maintenance and repair operations, which makes the operation of electrical equipment more reliable, extends its service life, saves money, and reduces the risk of damage. One of the factors influencing the efficiency of diagnostics of the condition of electrical equipment is the noticeable shortage of qualified specialists in the field of technical diagnostics. A method for assessing the moment of occurrence of a change in the growth of concentration of gases dissolved in oil has been developed, which allows to establish the presence of a developing transformer defect, the main gases, the probable type of defect and the nature of its manifestation. A method and algorithm for predicting the time of occurrence of a faulty state of power transformers based on data of chromatographic analysis of gases (CADG) dissolved in transformer oil are proposed. The recommended algorithm for calculating the time of occurrence of a defect, the intensity and duration of the impact of operational factors on the change in the concentration of dissolved gases according to the CADG data will improve the objectivity of comparing similar indicators of gases dissolved in oil at the initial stage of wear changes. The proposed methodology for assessing the statistical significance of the considered features and their varieties allows us to ensure the objectivity of calculating these indicators. It has been established that the main indicator should be considered the calculated time interval before the defect occurs.

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