A method for early warning of latent faults in transformers based on trend analysis
A trend analysis and fault early warning technology, applied in the direction of analyzing materials, instruments, scientific instruments, etc., can solve the problems that it is difficult to consider individual differences in equipment, so as to improve the reliability of early warning, avoid missed and false positives, and ensure safe and stable operation Effect
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[0019] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0020] A transformer latent fault early warning method based on trend analysis, such as figure 1 shown, including:
[0021] Step 1: For the historical data of gas concentration in the normal operation state of the transformer, take the data of the most recent period (such as 30 days), smooth the historical data through non-parametric regression methods (such as kernel-smoothing), and detect the evaluation indicators through outliers, Obtain the optimal non-parametric regression method parameters and the corresponding upper and lower limit time series data;
[0022] Step 2: Using the upper and lower limits of the historical gas concentration data as historical data, establish an adaptive prediction model for the concentration of dissolved gas in transformer oil, and optimize the model parameters through intelligent optimization methods;
[0023] Step 3...
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