Transformer fault diagnosis method and system based on multi-source data fusion
The invention belongs to the technical field of transformer fault diagnosis, and discloses a transformer fault diagnosis method and system based on multi-source data fusion, and the method comprises the steps: collecting oil chromatographic analysis data, a high-voltage bushing infrared detection ma...
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Main Authors | , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
07.06.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The invention belongs to the technical field of transformer fault diagnosis, and discloses a transformer fault diagnosis method and system based on multi-source data fusion, and the method comprises the steps: collecting oil chromatographic analysis data, a high-voltage bushing infrared detection map, a discharge ultrasonic detection map and an ultrahigh frequency partial discharge detection map, and carrying out the feature extraction respectively; splicing to obtain a multi-source fusion feature vector; optimizing the weight of each layer of RBM network of the deep belief network by using a black widow optimization algorithm, inputting the multi-source fusion feature vector into the optimized deep belief network for training, and performing transformer fault diagnosis through the trained deep belief network; according to the method, the transformer fault diagnosis precision is improved, the deep belief network is optimized through the black widow optimization algorithm, and the problem that the deep belief |
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Bibliography: | Application Number: CN202410585153 |