The present application relates to an early degradation diagnosis method for ultrasonic power supply power devices, aiming at the problem of insufficient accuracy and timeliness of traditional insulation deterioration and local
short circuit precursor detection, a multi-
modal feature diagnosis method is proposed, which fuses cold-state
resistance mutation, high-speed gray space evolution and near-
infrared spectrum response. The method uses synchronous high-speed current sensing,
image capture and near-
infrared spectrum acquisition to construct the original multi-dimensional
sensing data set, through
time domain slope analysis, space brightness
diffusion and spectrum peak correction, the insulation deterioration and heat accumulation characteristics are extracted, and through the lightweight
decision tree model, the four-level degradation state classification is realized, the graded early warning and closed-loop
risk control are completed. The
system has the advantages of strong environmental adaptability, intuitive state criterion and high diagnosis precision, and can realize early identification of insulation problems such as
gate oxide layer micro-breakdown, effectively improving the safety and reliability of power device operation.