Intelligent Fault Detection System for State Grid IoT Equipment Based on Edge Computing
Xin Li, Ji Lai, Zhongtao Chen, Gang Chen, Xue Gao, Chenglong Shi · 2019 IEEE 3rd International Electrical and Energy Conference (CIEEC) · 2019
At present, the amount of data generated by IoT terminal devices has become extremely large. The traditional centralized data processing model centered on the cloud computing model has been unable to support the current power IoT system. This paper proposes an intelligent fault detection system for power IoT devices based on edge computing for the defects of the cloud center computing model. The system model is divided into cloud center layer, edge layer, and field layer. In the field layer, the DTW complement algorithm is used to complement the sensor data; the DNN algorithm is used to implement the fault primary classification in the edge layer, and the classification result is uploaded to the cloud center layer; the correlation between the data is used in the cloud center layer to realize the fault classification. After that, an experiment was designed to verify the efficacy of the modified model.