A multi-factor fuzzy analysis method for identifying insulation paper abnormalities of transformers

Abstract

The invention relates to a multi-factor fuzzy analysis method for identifying insulation paper abnormalities of transformers, comprising the following steps: S1, determining the abnormal state of thetransformer insulation paper; S2, determining abnormal characteristic value of transformer insulation pap and its interval; S3, determining that abnormal characteristic value of the transformer gas and the interval thereof; S4: constructing a relative membership function of the paper factor to the abnormal state of the paper; S5, constructing a relative membership degree function of the gas factorto the abnormal state of the paper; S6, constructing a relative membership degree matrix of the paper factor; S7: constructing the relative membership matrix of the gas factor; 8, constructing a generalized weight distance function; S9: constructing an abnormality identification function of the insulating paper and identifying the abnormality. The invention can evaluate the abnormal state of theinsulation oil, reflect the uncertainty of the characteristic value of the abnormal state of the insulation oil, provide theoretical guidance for the identification of the abnormal state of the insulation oil, and provide necessary technical support for the operation and maintenance of the distribution network.

Description

technical field [0001] The invention relates to the technical field of power systems and automation thereof, in particular to a multi-element fuzzy analysis method for abnormal identification of transformer insulation paper. Background technique [0002] Subsequent maintenance and regular planned maintenance of traditional distribution network main equipment often require a lot of manpower and material resources, and the cost performance of maintenance is not high. With the improvement of equipment automation, the failure mode of time-related equipment only accounts for 6% of all failure modes of equipment, so the time-based periodic maintenance strategy is only effective for 6% of equipment failure modes. Based on regular maintenance combined with experience to determine the maintenance method to extend or shorten the maintenance cycle, and achieved certain results. [0003] With the increasing number of power equipment, the relationship between equipment is becoming more ...

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Problems solved by technology

[0010] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a multi-element fuzzy analysis method for abnormal identification of transformer insulation paper. Aiming at how to deal with the big data problems involving many types, large quantities and complex relationships involved in the identification of insulation abnormalities, in Based on the establishment of a large database, the principle of data clustering is used to process and analyze the big data; for the random and fuzzy uncertain parameters involved in the identification of insulation anomalies, the theory of probabilistic fuzzy sets is used to process and analyze; thus solving the problem of traditional methods using Experience, a small number of parameters or data are likely to cause low evaluation accuracy and lead to problems such as over-repair or disrepair

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