EEMD-based multi-scale fuzzy entropy OLTC fault diagnosis method

Abstract

The invention discloses an EEMD-based multi-scale fuzzy entropy OLTC fault diagnosis method. The method comprises steps: (1) an accelerating vibration sensor is placed on the top cover of an on-load tap changer, the vibration signals generated during the action process of the on-load tap changer in a normal state, a contact loose state, a contact wear state and a contact burnout state are acquiredrespectively, and multiple groups of vibration signals under each state are collected respectively; (2) the original vibration signals are subjected to EEMD to obtain IMF components; (3) first multiple IMF components are selected, and the fuzzy entropy of the selected IMF components is calculated; and (4) the calculated fuzzy entropy is used as a feature vector and is inputted to an SVM for training, an SVM classifier is obtained, and the SEn value of an IMF component of a test sample is inputted to the SVM classifier for working state recognition. The method can monitor the working state ofthe transformer on-load tap changer in real time, and the requirements of OLTC real-time fault diagnosis are met.

Description

technical field [0001] The invention relates to a fault diagnosis method for electric power equipment, in particular to an OLTC fault diagnosis method based on EEMD multi-scale fuzzy entropy. Background technique [0002] On-load tap-changer (OLTC) is an important part of power transformer, and its operation status is directly related to the stability and safety of transformer and system. OLTC is one of the components with the highest failure rate of transformers. Its failure not only directly affects the operation of the transformer, but also affects the quality of the power grid and the operation of the power grid. According to the statistics of the data in the trench, the accidents caused by OLTC faults account for about 28% of the total transformer accidents, and the types of faults are basically mechanical faults, such as contact looseness, contact falling off, mechanism jam, sliding gear, refusal to move, etc. Mechanical failures can directly damage the OLTC and the t...

AI Technical Summary

Problems solved by technology

The power outage maintenance period of on-load tap-changers is often long, and it is difficult to detect early mechanical failures in time. Failures and damages often occur before power outage maintenance, and power outage maintenance affects the normal operation of the transformer, which requires a lot of manpower, material and financial resources

On-line monitoring methods mainly include thermal noise-based diagnosis method and vibration-based on-line monitoring, etc. The thermal noise-based diagnosis is that the thermal noise generated by the heat generated after the transformer tap-changer breaks down spreads to the outside of the transformer, and is detected by installing a noise sensor on the transformer shell. To diagnose the fault of the tap changer, but when the thermal noise is transmitted to the sensor, the energy loss is too large, and various noises interfere with the engineering application, which is difficult to realize

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