This paper proposes the EWM-EDTS algorithm for localizing errors in measurement loops of power system relay protection devices. The algorithm integrates Euclidean distance and Tanimoto similarity using the entropy weight method. Two sets of measurement data with correlated physical information are selected based on the power station's topology. The Euclidean distance and Tanimoto similarity algorithms are used to calculate a sequence of distance values that characterize the dispersion of the two sets of data. then the entropy power method is introduced to calculate the dynamic entropy value of the two sets of sequences, which serves as a distance value weighting and fuses to generate the distance value of the EWM-EDTS, and compares it with the distance threshold value constituted by the measurement data under the normal working condition to realize the error localization of the real-time measurement data. Real-time measurement data error localization.