Method and device for evaluating the credibility of electronic transformers based on the evidence set of the whole network
An electronic transformer and reliability technology, which is applied in the direction of measuring devices, instruments, and measuring electrical variables, etc., can solve problems such as difficult online detection work, power processing, and risk assessment of digital electric energy measurement applications that cannot be electronic transformers.
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Embodiment 1
[0042] Such as figure 1 As shown, a method for evaluating the credibility of electronic transformers based on the evidence set of the whole network, including steps:
[0043] Step 1, clustering the high-dimensional data sets of electronic transformers to obtain different clusters of the high-dimensional data sets of electronic transformers after clustering;
[0044] The high-dimensional data set of the electronic transformer is the load data and environmental data collected by the electronic transformer for the entire network domain of the smart substation, that is, the evidence set of the entire network domain. The environmental data includes ambient temperature, environmental humidity, and smart substation space. Magnetic field, electronic transformer operating environment vibration, load data include the measured current and voltage of the electronic transformer; the electronic transformer can be one or more electronic transformers of the same type in the smart substation; ...
Embodiment 2
[0074] An electronic transformer credibility probability evaluation device based on the evidence set of the whole network, characterized in that it includes:
[0075] The clustering module is used to cluster the high-dimensional data sets of electronic transformers, obtain different clusters of the high-dimensional data sets of electronic transformers after clustering, and remove noise point data;
[0076] The XGBoost model training module is used to train the pre-established XGBoost model according to the electronic transformer high-dimensional data set and the reliability probability of different clusters of the electronic transformer high-dimensional data set to obtain a trained XGBoost model;
[0077] The evaluation module is used to input the high-dimensional data set of the electronic transformer to be evaluated into the trained XGBoost model to obtain the predicted reliability probability, so as to judge whether there is a measurement error in the electronic transformer....
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