Method for predicting service life of transformer by using multiple parameters
A technology for life prediction and transformers, applied in biological neural network models, computer-aided design, design optimization/simulation, etc., can solve problems such as difficulty in transformer operation life, and achieve high prediction accuracy
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[0049] Example: such as figure 1 As shown, a flow chart of a multi-parameter transformer life prediction method, the specific steps are as follows:
[0050] S1. Using the transformer state data to evaluate the state of the transformer.
[0051] S11, such as figure 2 As shown, the transformer status data is composed of transformer electrical test item data, dissolved gas analysis data in oil, transformer oil characteristic data and working condition data, specifically: electrical test item data includes insulation resistance, absorption ratio, leakage current, DC resistance Balance coefficient; analysis data of dissolved gas in oil are hydrogen, methane, ethane, ethylene, acetylene, carbon monoxide, carbon dioxide; transformer oil characteristic data are water content, acid value, breakdown voltage, oil dielectric loss; working condition data are transformer Load rate and transformer operating environment level; recorded as a state vector:
[0052] Y=(y 1 ,y 2 ,...,y i ,...
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