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

Abstract

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.

Description

technical field [0001] The invention belongs to the technical field of transformer detection and relates to a regression prediction method for transformer oil dielectric loss based on multi-frequency ultrasonic detection. Background technique [0002] The oil-immersed power transformer is the core equipment of the power system and plays an important role in power supply and distribution and power conversion. Long-term studies have shown that the safe and reliable operation of transformers mainly depends on the state of insulation, and maintaining a good insulation state is a key factor for safe and stable operation of transformers. Oil-immersed power transformers use insulating oil as the insulation and cooling medium, which has many advantages compared with air: high insulation strength, which can provide insulating materials with an air-isolated environment and reduce corrosion exposed to the air; the ratio of transformer oil The heat is larger than that of air, and its g...

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Problems solved by technology

However, due to the large and complex structure of the Xilin bridge measurement system, the operation is cumbersome, and a certain amount of dissolved gas will be produced during the high-frequency induction heating process, which will affect the transformer oil. This system is not conducive to the realization of recirculating online monitoring of transformer oil.

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