A Transformer Internal Fault Identification Method Based on Mathematical Statistical Probability Model

Abstract

The invention relates to a mathematical statistical probability model based method for identifying internal faults of a transformer and belongs to the field of a power system. The method comprises thefollowing steps: S1, collecting vibration signals of the transformer and establishing a mathematical model of the vibration signals of transformer faults; S2, extracting acceleration signals from the vibration signals of the transformer; S3: importing the extracted transformer vibration acceleration signals into LabVIEW for data processing and then importing into the established mathematical model for analysis; S4, importing vibration signals of different faults of the transformer into the established mathematical model, and determining a vibration signal cumulative probability distributionfunction diagram under different fault conditions of the transformer; S5: performing least square fitting on the cumulative probability distribution function under different fault conditions of the transformer, and judging transformer faults according to a slope relation. The method of the invention optimizes a prior transformer fault identification method to a certain extent, and provides a new idea for the development of the transformer fault identification field.

Description

technical field [0001] The invention belongs to the field of electric power systems, and in particular relates to a transformer internal fault identification method based on a mathematical statistical probability model. Background technique [0002] With the rapid development of my country's economy, people's demand and dependence on electricity are constantly increasing. Therefore, how to effectively ensure the security of the power grid system has become increasingly important, and at the same time, higher standards and requirements have been put forward for the control of security issues in the power grid system. [0003] The transformer is one of the important power transmission and transformation equipment in the power grid, and its operation reliability directly affects the stable operation of the power system. Due to the long-term operation of the transformer, there will always be different degrees of damage and latent faults. Under the impact of overload operation a...

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Problems solved by technology

[0005] However, when using the vibration method to monitor the working conditions of transformers at this stage, there are certain limitations in the detection of minor faults inside the transformer and the noise reduction and impurity removal of vibration signals:

[0006] On the one hand, the acquisition of vibration signals and the processing of stray noise are relatively complicated. Traditional detection methods need to perform noise reduction processing on the collected vibration signals. In order to achieve the purpose of noise reduction, multiple filtering units are usually required, and large data volume The technology of sampling and then averaging is used for error correction, which leads to a cumbersome process for noise reduction, which greatly increases the economic cost

[0007] On the other hand, in the case of unsatisfactory noise reduction, the vibration method cannot quickly and accurately identify the early minor faults of the transformer, resulting in the inability to deal with potential safety hazards of the transformer in time, reducing the safety and reliability of the power grid operation

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