XGBoost-based electric power secondary equipment defect degree evaluation method
A secondary equipment and defect technology, applied in the field of evaluation of the defect degree of power secondary equipment based on XGBoost, can solve problems such as low efficiency and error-prone
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[0031] In order to describe the technical solution disclosed in the present invention in detail, further elaboration will be made below in conjunction with the accompanying drawings and specific embodiments.
[0032] Specifically, take the secondary equipment defect record data of a power plant from 2016 to 2018 as an example, with a total of 556 typical defect information. Among them: 147 cases of general defects, 256 cases of serious defects, and 153 cases of crisis defects. The data is randomly divided into training set and test set according to the ratio of 4:1.
[0033] Table 1 Specific distribution of sample data
[0034]
[0035] like figure 1 As shown, the method for evaluating the defect degree of power system secondary equipment based on the Apriori-XGBoost algorithm of the present invention, the specific implementation steps are as follows:
[0036] Step 1. Data collection
[0037] Collect historical defect data of secondary equipment through the power grid p...
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