Recorded waveform data processing method and recorded waveform data processing device

Abstract

The invention discloses a recorded waveform data processing method and a recorded waveform data processing device, wherein the recorded waveform data processing method comprises the steps of acquiring the number of periodical sampling points of recorded waveform data, wherein the recorded waveform data are electric energy quality monitoring data; and performing inter-cycle differential calculation on the sampling point data at the same position between the cycles for obtaining differential data, so that advantages of low subsequent processing data volume, high processing speed in compression or transmission, and the like are realized. The recorded waveform data processing method and the recorded waveform data processing device can reduce data volume of to-be-compressed data or to-be-transmitted data, thereby reducing compression calculation amount and data volume after compression, and improving compression rate. Furthermore the recorded waveform data processing method and the recorded waveform data processing device can relatively effectively reduce storage and/or transmission load of the mass recorded waveform data of an electric energy quality monitoring terminal.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a method and device for processing wave recording data. Background technique [0002] With the development of industry and the improvement of power technology, power quality monitoring has received more and more attention. The massive data collected by the power quality monitoring terminal has caused great pressure on storage and communication. In current applications, a large amount of original monitoring data, that is, wave recording data, is overwritten and discarded after being stored in the terminal device for a period of time, resulting in a huge waste of data resources. [0003] For massive terminal wave recording data, data compression can be used for compression processing, thereby reducing the data size and facilitating storage and transmission. Currently, commonly used compression methods include lossless compression and lossy compression. Lossy compression me...

AI Technical Summary

Problems solved by technology

Lossy compression methods can include Fourier transform and discrete wavelet transform, etc. Among them, Fourier transform can extract the frequency spectrum information of the data, but it cannot reflect the dynamic change information of the data; discrete wavelet transform can be converted through the adaptive window The way of size reflects the dynamic changes of data, but its calculation amount is relatively large, and because of lossy compression, some information of the data itself is discarded, which reduces the integrity of the data

Lossless compression methods, including GZIP, LZ77, Zlib, Haffman Coding (Haffman Coding) and Deflate and other compression methods, can retain all the information of the original data, but not enough consideration of the characteristics of the recording itself, that is, the periodicity of the data itself , The characteristics that the steady state accounts for most of the time period are not utilized

Moreover, the lossless compression method above compresses all the data. Due to the huge amount of information in the wave recording data, it may lead to low compression efficiency, long compression time, large space occupation of compressed data, and low efficiency of data compression, transmission and storage.

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