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Status Detection Evaluation Method of Distribution Network Fault Indicator Based on Artificial Intelligence
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Abstract
In order to solve the problem of status detection evaluation of field operation fault indicator, a status detection evaluation method of distribution network fault indicator based on artificial intelligence is proposed. Firstly, the fault indicator status detection evaluation model is established, and the result information of fault indicator detection using portable detector is described by fault indicator status detection information matrix. Secondly, based on the principle of “3 selection 2”, the fault indicator status detection comprehensive result table is established. Then, the same factory fault indicator status detection evaluation matrix and the fault indicator single state detection comprehensive evaluation matrix are established to evaluate the 10 functional detection results of a single fault indicator of a manufacturer. Secondly, the fault indicator sub-detection comprehensive evaluation matrix is established to describe the evaluation results of all fault indicators in the same plant on different sub-function detection. Finally, the comprehensive evaluation results of all fault indicator detection in the same plant are evaluated by means of the average method. The example analysis shows that the method described in this paper can evaluate the status detection results of fault indicators from three aspects: individual, sub-item and comprehensive, which has good practical significance.
Title: Status Detection Evaluation Method of Distribution Network Fault Indicator Based on Artificial Intelligence
Description:
Abstract
In order to solve the problem of status detection evaluation of field operation fault indicator, a status detection evaluation method of distribution network fault indicator based on artificial intelligence is proposed.
Firstly, the fault indicator status detection evaluation model is established, and the result information of fault indicator detection using portable detector is described by fault indicator status detection information matrix.
Secondly, based on the principle of “3 selection 2”, the fault indicator status detection comprehensive result table is established.
Then, the same factory fault indicator status detection evaluation matrix and the fault indicator single state detection comprehensive evaluation matrix are established to evaluate the 10 functional detection results of a single fault indicator of a manufacturer.
Secondly, the fault indicator sub-detection comprehensive evaluation matrix is established to describe the evaluation results of all fault indicators in the same plant on different sub-function detection.
Finally, the comprehensive evaluation results of all fault indicator detection in the same plant are evaluated by means of the average method.
The example analysis shows that the method described in this paper can evaluate the status detection results of fault indicators from three aspects: individual, sub-item and comprehensive, which has good practical significance.
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