Transformer fault comprehensive diagnosis system and diagnosis method based on fuzzy association rules

Abstract

The disclosure provides a transformer fault comprehensive diagnosis system based on a fuzzy association rule. The system includes a transformer fault type diagnosis module, a transformer fault location diagnosis module, and a transformer fault comprehensive diagnosis module based on case-based reasoning. The disclosure also provides a transformer fault comprehensive diagnosis method based on a fuzzy association rule. The diagnosis system diagnoses the fault type, the fault location and the fault cause of a transformer, can help the field staff to complete discrimination, and is suitable for the diagnosis of a variety of transformer faults.

Description

technical field [0001] The invention relates to the field of transformer fault diagnosis, in particular to a transformer fault comprehensive diagnosis system and diagnosis method based on fuzzy association rules. Background technique [0002] The power transformer is one of the important equipment in the power system. Its operating status is closely related to the safe and reliable operation of the power grid. How to accurately and effectively diagnose and maintain the power transformer has an important role and significance. For the latent faults of power transformers, there is a close relationship between the types of internal defects of equipment and their fault symptoms and fault modes, and they have the characteristics of multi-dimensionality, complexity, and redundancy. Research hotspots and difficulties. With the rapid development of my country's power grid construction, various types of detection technologies and methods are emerging, and the status data of power eq...

AI Technical Summary

Problems solved by technology

However, the existing research results mainly focus on the detection and analysis of the specific parameters of the single characteristic of the transformer equipment, or use the macroscopic parameter changes of the equipment to infer the internal fault type of the equipment. Efficient way to synthesize relationships between states

At present, there is no mature comprehensive diagnosis system suitable for the type, location and cause of transformer faults using multi-source parameters, which cannot further meet the requirements of reliable and safe operation and maintenance of transformers

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