Transformer oil dielectric loss regression prediction method based on multi-frequency ultrasonic detection

• Main Authors: LI YAQUAN, LI XIUMING, WANG XINGYAO, ZHOU QU, YANG HUAKUN, LIU MINGHUI, WANG RUIHU, SU YANG
• Format: Patent
• Language: Chinese; English
• Published: 02.11.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

The invention relates to a transformer oil dielectric loss regression prediction method based on multi-frequency ultrasonic detection, and belongs to the technical field of transformer detection. The method comprises the following steps: S1, carrying out multi-frequency ultrasonic detection; S2, performing multi-dimensional scale analysis (MDS); S3, establishing a back propagation neural network (BPNN); S4, obtaining a global optimal solution by using a particle swarm optimization (PSO) algorithm; and S5, establishing a transformer oil dielectric loss prediction model based on the MDS-PSO-BPNN. According to the invention, the relationship between the ultrasonic characteristic value and the transformer oil dielectric loss is established, so that the transformer fault can be detected by multi-frequency ultrasonic waves, the problems of huge and complex structure and tedious operation of a traditional detection system are solved, and the operation state of the transformer oil can be circularly monitored on line.