Power transformer fault diagnosis system based on expert database

Abstract

The invention discloses a power transformer fault diagnosis system based on an expert database, and the system comprises a data input module, a reasoning module, a knowledge obtaining and explanation module, and a man-machine interaction interface, wherein the data input module, the reasoning module, the knowledge obtaining and explanation module and the man-machine interaction interface are connected sequentially. The reasoning module is connected with an expert database module, and the expert database module comprises a diagnosis basis database module, a conclusion fact database module and a fault rule database module, wherein the diagnosis basis database module is used for storing the basis of system diagnosis. The conclusion fact database module is used for recording set fault information. The fault rule database module is used for storing diagnosis rule, and completes the combination of rules through reading detection data and combining a conclusion fact database. The system provided by the invention can judge the operation state of a transformer through a reasoning mode and the knowledge of an expert system according to operation parameters of the transformer, gives possible fault types, achieves the automatic diagnosis of a fault, and improves the operation scientificity and use efficiency of a power transformer.

Description

technical field [0001] The invention relates to the technical field of transformer fault on-line monitoring, in particular to a power transformer fault diagnosis system based on an expert database. Background technique [0002] The power transformer is one of the important equipment in the power industry. Whether it can operate safely is related to the safety of the power system connected to it. Its working efficiency represents the financial income of the power department. In order to ensure the safe and stable operation of the power transformer, the traditional method is to carry out Regular preventive tests, such as insulation characteristic tests, withstand voltage tests, etc., such maintenance programs may usually produce the following situations: maintenance is performed when no maintenance is required, which accelerates the process of equipment damage and aging, and when maintenance is required due to fixed If the maintenance cycle is not up, the failure will be aggra...

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Problems solved by technology

[0002] The power transformer is one of the important equipment in the power industry. Whether it can operate safely is related to the safety of the power system connected to it. Its working efficiency represents the financial income of the power department. In order to ensure the safe and stable operation of the power transformer, the traditional method is to carry out Regular preventive tests, such as insulation characteristic tests, withstand voltage tests, etc., such maintenance programs may usually result in the following situations: maintenance is performed when no maintenance is required, which accelerates the process of equipment damage and aging, and when maintenance is required due to fixed If the maintenance cycle is not up, the failure will be aggravated, resulting in equipment damage and even serious accidents. Therefore, the fault diagnosis of power transformers is also an important part of realizing smart substations, so it is necessary to carry out status and fault diagnosis of power transformer faults. diagnostic techniques for research

[0003] The structure of power transformers is complex, and there are many types of faults. According to common fault conditions, they can be divided into short-circuit faults, discharge faults, insulation faults, iron core faults, tap changer faults, and oil flow electrification faults. Many of these faults are difficult to express their models mathematically. Secondly, the operating environment, load nature, and network structure of each operating transformer are different, and the probability of failure and the characteristics of the failure are also different, which increases the uncertainty of the diagnosis process. In addition, the generation and development of the fault often have a gradual process, which increases the The complexity of its fault diagnosis makes it often need to rely on the experience of experts to solve

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