Transformer fault diagnosis method based on integrated learning Bagging algorithm
A transformer fault and integrated learning technology, applied in scientific instruments, instruments, calculations, etc., can solve problems such as complex calculation process and large diagnostic error, achieve the effect of improving accuracy and overcoming single classifier fault diagnosis technology
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[0035] The implementation process of the method of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.
[0036] Transformer operation data collection is the premise of fault diagnosis, and only accurate and sufficient data samples can ensure the effectiveness of fault diagnosis methods. For this reason, the present invention adopts the dissolved gas analysis technique DGA (Dissolved Gas Ahalysis) in the oil to collect the hydrogen H of each time monitoring point in the target transformer. 2 , carbon monoxide CO, methane CH 4 , Vinyl C 2 h 4 , ethane C 2 h 6 , acetylene C 2 h 2 and carbon dioxide CO 2 and other seven gases, and record the transformer operating status at each time monitoring point "normal, low-temperature overheating fault, medium-temperature overheating fault...
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