Fusing virtual sensing and mixed reality: a novel digital twin framework for visualizing DC field-induced moisture migration in transformer insulation

Online and distributed monitoring of moisture in the solid insulation of converter transformers remains a challenging task. To address this issue, a digital twin framework integrating virtual sensing and mixed reality (MR) is developed. Electro-thermal coupling experiments are conducted to examine the role of direct current (DC) electric fields, showing that they not only suppress moisture diffusion but also promote its accumulation in regions with higher field intensity. Based on these observations, a revised moisture equilibrium model for oil-paper insulation is established. Using this model as the underlying mechanism, a virtual sensing approach is formulated to reconstruct the 3D moisture distribution within solid insulation from measurable quantities such as oil moisture content and temperature. To facilitate intuitive interpretation, MR technology is introduced, where the reconstructed moisture distribution is overlaid onto the physical transformer through high-precision spatial anchoring. This enables a direct visualization of internal insulation states during operation. Case studies indicate that the predicted moisture distribution agrees well with indirect measurements derived from the degree of polymerization of insulating paper, with an average relative error below 3%. In addition, the system achieves millimeter-level registration accuracy while maintaining smooth interactive performance. Overall, the proposed framework provides a feasible means for non-destructive perception and visualization of otherwise inaccessible internal states, offering a practical pathway toward predictive maintenance of transformer insulation systems.