A Compression Approach of Power Quality Monitoring Data Based on Two-dimension DCT

A compression approach of power quality monitoring data based on two-dimension Discrete Cosine Transform (DCT) is presented to deal with huge data about power quality event detection. The monitoring data was truncated and recomposed in multiple cycles to transform the one-dimension data into the two-dimension data, which was a matrix in essence. The matrix was divided into some sub-blocks all of which were 8×8 matrices. These matrices were performed two-dimension DCT. The elements at the same location of all sub-matrices form a new matrix, and the elements were at the equivalent energy level. The energy levels of new matrices were measured by average energy, and quantitative matrix was obtained by a threshold of average energy. The new matrices and quantitative matrix were used to represent the monitoring data set.