A Novel Method to Compress Real-time Process Data

摘要

Most existing real-time data compressing algorithms are focused on dynamic and inconstancy of the process data,but a basic observation is ignored with some unexpectedness:on condition that sampling interval is not large,difference between amplitudes of real-time process data from two neighboring samples is relatively small,and most of data amplitudes are in the same range.In this paper we propose a compression algorithm based on the observation and experimentally evaluate the proposed approach and demonstrate that our algorithm is promising and efficient.