Abstract: Electric energy data acquire equipment（EDA） refers to devices that collect electricity consumption data from distribution transformers, end-users, and other devices. Its operating status will directly affect the stability of customer electricity consumption data collection. To solve the problem of low accuracy in the evaluation of the operation status of EDA due to the lack of abnormal cause tracing analysis, a fault factor based method for evaluating the status of EDA is proposed. Firstly, a hidden Markov model is used to extract the red line information in the evaluation rules and regulations of EDA, and the data of EDA is preprocessed to eliminate the impact of abnormal data on the evaluation; secondly, density clustering is performed on the abnormal causes of EDA to form evaluation indicators for the operation status of EDA and the weight of fault impact factors, and evaluation is carried out. Finally, it is validated at a metrology center in a certain province, and the accuracy of its operational status evaluation is 99.56%. The proposed method can effectively improve the evaluation accuracy of electricity collection equipment.