Risk Warning Method for Transmission Site Operations Based on Convolu-tional Neural Networks
Due to the limited features that traditional alarm methods can only extract,the accura-cy of detecting anomalies in power transmission site operations is low.To address the above is-sues,a risk warning method for on-site transmission operations based on convolutional neural networks is proposed.By analyzing the distribution characteristics of fault time in on-site trans-mission operations,we can understand the occurrence of faults.Secondly,by obtaining the ab-normal distance of the transmission site operation,the abnormal situation of the transmission site operation is extracted.Using the extracted abnormal features,establish a convolutional neural network-based anomaly detection model for power transmission on-site operations to detect ab-normal situations in power transmission on-site operations.Finally,timely remind relevant per-sonnel to take corresponding measures through risk warnings for on-site transmission opera-tions.The experiment proves that this method can accurately detect abnormal situations in pow-er transmission site operations,timely detect risks,and improve the accuracy of risk warning for power transmission line operations.
Convolutional neural networkTransmission site operationsTransmission linesRisk warning
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