A study on the diagnosis of power transformer winding faults considering power and voltage characteristics

Abstract

As a critical component of power systems, the operational status of power transformers directly affects the safety and reliability of the power grid. Addressing the challenge that traditional methods struggle to achieve online monitoring of winding deformation faults, this paper proposes a novel method for online detection of transformer winding deformation based on Lissajous figure trajectories. This method involves collecting voltage and current signals from both the highand low-voltage sides, constructing voltage-squared and instantaneous power characteristics, and generating corresponding Lissajous curves. By establishing a mapping relationship between changes in the mechanical structure of the windings and electrical parameter characteristics, the method enables the qualitative identification and quantitative assessment of axial and radial deformation in the windings. Experimental results demonstrate that this method can detect minor winding deformation (deformation amount = 3%) and exhibits higher sensitivity in detecting radial winding deformation compared to the frequency response analysis method. This study provides a new technical approach for online monitoring of transformer winding deformation and holds significant engineering application value for enhancing the condition monitoring and intelligent operation and maintenance of power grid equipment.