The abnormalities in the host device protection sampling loops of smart substations are difficult to detect due to their characteristics of concealment,transience,and instability.Here,we propose an early warning scheme for the abnormal sampling loops of the host device protection in smart substations based on homologous waveform recording data.First,the occurrence of abnormal sampling loops is determined by reasonably setting the early warning thresholds and waveform analysis criteria.Second,a knowledge graph for the operation and maintenance of the sampling loops is constructed based on information of the equipment operation and maintenance manual related to the sampling loops,to realize the aided decision-making for handling abnormal sampling loops.Finally,a case study is carried out based on an actual defect in a substation.The results show that the scheme is effective in detecting the abnormalities in the sampling loops,and the constructed knowledge graph can provide decision-making references for operation and maintenance personnel in handling abnormalities,significantly reducing manual workload.