The invention relates to the technical field of calibration tests, in particular to an intelligent metering calibration method and
system, and the method comprises the following steps: calculating the similarity between data points, constructing a
similarity matrix, further calculating the fitting degree, carrying out the spectral
decomposition, extracting a
feature vector, carrying out the dimension reduction, mapping to a low-dimensional space, carrying out the
data point clustering based on a
feature vector matrix, and carrying out the calibration of the data points. An error cluster is identified and an error pattern is determined. According to the method, by calculating the similarity between the data points and mapping the similarity to the low-dimensional space, the error
modes can be efficiently recognized and classified, the error correction path can be dynamically adjusted, error correction is more flexible and real-time, the
error analysis depth is improved through spectral
decomposition and
feature vector extraction, and the
error analysis accuracy is improved. Therefore, the error trends of the equipment under different conditions are accurately identified, the
measurement precision and stability are remarkably improved, the error correction path parameters are updated in real time, the adaptability of the
system to the operation change of the equipment is enhanced, and the calibration time is effectively shortened.