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Dissolved Gas Analysis (DGA) has already gained its popularity in fault diagnosis for the oil-immersed transformers. However, owing to the fuzziness and uncertainty between the failure phenomena and failure mechanisms, power equipment failure reasons are very complicated and the accuracy of existing algorithms is low. Diagnostic methods based on artificial intelligence are commonly introduced in the...
This paper proposes an algorithm of failure diagnosis for electronic device. This algorithm can train existed failure diagnosis parameter sample sets, analysis internal relationship of diagnosis parameters and obtain the final result for device diagnosis, which achieves diagnosis adaptation about further sample parameter of device failure diagnosis. The advantage of algorithm is to optimize training...
The fault diagnosis for large oil-immersed power transformer is generally carried out through preventive test data. However, the preventive test data must be obtained until power-off time, and the amounts and accuracy of the field data is limited. When a fault occurs in the running time, it always accompanies by the variations of the appearance such as color, sound, temperature and oil level, etc...
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