The present application relates to the technical field of power generation motor, and discloses a power generation
motor insulation state prediction method and
system. The method collects three-phase
stator current signals and
operation mode identification signals of the power generation motor, and constructs an insulation degradation characteristic vector. The power generation mode and the motor mode are distinguished based on window average active power, and an
operation mode variable and a
mode change indicator are constructed. The basic
coupling coefficient between the degradation characteristics is calculated, the
coupling weight is adjusted by introducing a mode sensitivity function, an adaptive
adjacency matrix driven by the
operation mode is constructed, and the event-driven update of the graph structure is realized. Based on the adaptive graph structure, spatial
feature extraction and time dimension fusion are carried out, and a normalized insulation
health index is output for state evaluation and
trend analysis. The method can weaken the influence of the difference between the two working conditions on the
coupling relationship of the characteristics, improve the stability and reliability of the insulation degradation evaluation, and is suitable for online monitoring and early warning of the power generation motor of the pumped storage unit.