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2017
DOI: 10.1049/iet-gtd.2016.0968
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Novel protection scheme for residual current device‐based electric fault time detection and touch current identification

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Cited by 11 publications
(7 citation statements)
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“…Under the action of the alternating magnetic flux, the induced electromotive force E2 is generated on the secondary side of the transformer [2]. This signal enters the single-chip microcomputer through the sampling resistor and the signal conditioning circuit to perform the leakage protection function after being sampled and processed.…”
Section: Electromagnetic Current Transformer Methodmentioning
confidence: 99%
“…Under the action of the alternating magnetic flux, the induced electromotive force E2 is generated on the secondary side of the transformer [2]. This signal enters the single-chip microcomputer through the sampling resistor and the signal conditioning circuit to perform the leakage protection function after being sampled and processed.…”
Section: Electromagnetic Current Transformer Methodmentioning
confidence: 99%
“…Literature [7–11] combines wavelet packet transform, energy entropy, quantum genetics, and other artificial NN to establish a related classification model, which provides theoretical support for effective recognition types. In [12], the least squares SVM can accurately identify the electric shock current of the birth object from the total leakage current. Based on the principle of adaptive filtering, the literature [13] establishes an adaptive electric shock current detection model with good noise robustness and can effectively eliminate the dead zone of protection action.…”
Section: Bioelectrical Shock Current Sample Collection and Related mentioning
confidence: 99%
“…Literature [7][8][9][10][11] combines wavelet packet transform, energy entropy, quantum genetics, and other artificial NN to establish a related classification model, which provides theoretical support for effective recognition types. In [12], the least squares SVM can accurately identify the electric shock current of the birth object IET Cyber-Phys. Syst., Theory Appl.…”
Section: Bioelectrical Shock Current Sample Collection and Related Workmentioning
confidence: 99%
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“…To identify the residual current defect in low voltage distribution networks, a cooperative training classification model based on an upgraded squirrel search method for a semi-supervised SVM and the k-nearest neighbor is applied in 29 . A protection strategy based on least squares-SVM is designed and developed for residual current and touch current 30 . All aforementioned study deal with SVM based different strategies for fault detection in different systems where the proposed system developed rule-based classifiers for detecting sensor fault and load current fault and MSVM is applied for leakage current fault through proper classification in a household environment.…”
Section: Introductionmentioning
confidence: 99%