Transformer fault diagnosis method based on case-based reasoning

A transformer fault and diagnosis method technology, applied in the electric power field, can solve problems such as insufficient solution to transformer faults, influence retrieval, difficulty in maintaining transformer case database, etc., and achieve the effects of convenient maintenance and easy operation, improved efficiency, and improved retrieval efficiency.

Inactive Publication Date: 2013-06-05
XIDIAN UNIV
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  • Abstract
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Problems solved by technology

The disadvantage of this method is that the maintenance of the transformer case library is difficult, which affects the efficiency of retrie...

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  • Transformer fault diagnosis method based on case-based reasoning
  • Transformer fault diagnosis method based on case-based reasoning
  • Transformer fault diagnosis method based on case-based reasoning

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Embodiment Construction

[0039] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0040] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0041] Step 1. Establish a fault case library

[0042] In the first step, fault information is extracted from a single real transformer fault case. Fault information refers to transformer fault description information, transformer fault symptom information, transformer fault cause information, and transformer fault case maintenance plan information.

[0043] In the second step, the fault information extracted from a single actual transformer fault case is represented by a fault information quadruple. The fault information quaternion refers to the description tuple of the transformer fault case corresponding to the fault information, the symptom tuple of the transformer fault case, the cause of the transformer fault case tuple, and the maintenance plan tu...

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Abstract

The invention discloses a transformer fault diagnosis method based on case-based reasoning. The implementation steps includes: (1), establishing a fault case base; (2), retrieving fault cases; (3), maintaining a transformer; (4), judging whether a fault case concentrated repair scheme can solve transformer faults, if not, turning to a step (5), and otherwise, turning to a step (9); (5), revising the fault cases; (6), maintaining the transformer by maintenance personnel through using a revised maintenance scheme; (7), judging whether the revised maintenance scheme can solve the transformer faults, if can, turning to a step (8), and otherwise, the step (5) is actuated; (8), updating the fault case base; and (9), learning the fault cases. According to the transformer fault diagnosis method based on the case-based reasoning, a fault case reversing and learning strategy idea is applied to the transformer fault diagnosis method, and compared with a prior transformer fault diagnosis method, the transformer fault diagnosis method has more strong adaptability and higher case retrieval efficiency.

Description

technical field [0001] The invention belongs to the field of electric power technology, and further relates to a transformer fault diagnosis method based on case reasoning applied in the field of electric power by artificial intelligence fault diagnosis technology. The invention can be used for judgment, identification and detection of transformer faults, and better assists fault diagnosis and maintenance of transformers. Background technique [0002] At present, in the field of transformer maintenance, traditional fault diagnosis mostly adopts RBR (rule based reasoning, rule-based reasoning), MBR (model based reasoning, mode reasoning) expert system technology. Since these traditional expert systems are based on model-driven (model-based diagnostic methods use deep knowledge such as the structure, behavior and function models of the diagnostic object for diagnostic reasoning), in terms of model construction, information acquisition, and information processing There are ser...

Claims

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Application Information

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IPC IPC(8): G01R31/00
Inventor 王保保张生林王瑾魏鹏
Owner XIDIAN UNIV
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