A Novel Method to Compress Real-Time Process Data
Xiao Jian Zheng · Advanced materials research · 2012
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.