no code implementations • 14 Feb 2022 • Zhaoyang Qu, Xiaoyong Bo, Tong Yu, Yaowei Liu, Yunchang Dong, Zhongfeng Kan, Lei Wang, Yang Li
Taking account of the fact that the existing knowledge-driven detection process for FDIAs has been in a passive detection state for a long time and ignores the advantages of data-driven active capture of features, an active and passive hybrid detection method for power CPS FDIAs with improved adaptive Kalman filter (AKF) and convolutional neural networks (CNN) is proposed in this paper.
