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Compression method for partial discharge on-line monitoring data

A technology for monitoring data and compression methods, applied to electrical components, transmission systems, etc., can solve problems such as lossy compression, large information loss or distortion, and inability to obtain ideal use effects, etc., to achieve efficient transmission effects

Inactive Publication Date: 2011-08-17
ELECTRIC POWER RES INST OF GUANGDONG POWER GRID +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, threshold compression is a lossy compression technique
The higher the data compression rate, the greater the loss or distortion of information. Therefore, it is usually necessary to consider these two factors comprehensively when using it. It is often impossible to obtain an ideal use effect by finding a balance point through a compromise method.

Method used

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  • Compression method for partial discharge on-line monitoring data
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  • Compression method for partial discharge on-line monitoring data

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0022] Embodiment 1: the compression method of partial discharge on-line monitoring data of the present invention, at first collect monitoring data (step 1) from partial discharge monitoring device, then according to predetermined row width and row height, the monitoring data collected is stored (step 2 ); According to the row width and the row height of the stored monitoring data, judge the correlation of the row of the monitoring data and the correlation (step 3); according to the judgment result, use the XOR algorithm to correlate the monitoring data of the row Processing (step 4); storing the compressed data after correlation processing (step 5).

[0023] Since the row width or row height of the monitoring data is determined, the correlation between adjacent rows or columns can be determined. Because the size of the data source of the total monitoring data is known, determining the row height also determines the row width, and similarly, determining the row width also dete...

Embodiment 2

[0034] Embodiment 2: This embodiment has made further improvement on the basis of embodiment 1, further carries out further to the data after correlation processing by RL-B (Run Length To Binar, run length binary) algorithm after performing step 4 compression.

[0035] As a preferred embodiment of this embodiment, in order to make the characters with high occurrence probability in the original monitoring data collected in step 1 and the 0 appearing after XOR, one RL-B compression can be performed uniformly. Before step 3, the collected original monitoring data is counted, and when the character occurrence probability exceeds M (the value of M can be set according to the different needs of the user, for example, M=40% can be taken), and 0 is interacted with Change. For example, assuming that the character with high occurrence probability is 0xff, let 0xff and 0 be interchanged (expressed as 0xff0).

[0036] In order to show the compression effect of this embodiment, see the t...

Embodiment 3

[0045] Embodiment 3: As a further improvement to Embodiment 2, this embodiment further compresses the data through the LZW (Lempel-Ziv-Welch Encoding) algorithm after the RL-B compression processing.

[0046] Similarly, in order to show the compression effect of this embodiment, see the table below:

[0047] For example, if the PD spectrogram data (this data is 512*160 points) is transformed, the metadata is 10240 bytes, assuming that the character with high occurrence probability is 0xff, the results can be seen in Table 2.

[0048] Table 2 Processing results of single data source files according to different compression schemes

[0049]

[0050]RL-B+LZW: Indicates that the monitoring data after XOR processing is compressed using the RL-B algorithm, and then the monitoring data compressed by the RL-B algorithm is compressed using the LZW algorithm.

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Abstract

The invention provides a compression method for partial discharge on-line monitoring data, which comprises the following steps of: firstly collecting monitoring data from a partial discharge monitoring device; storing the collected monitoring data according to preset line width and line height; then judging the line relativity and row relativity of the monitoring data according to the line width and line height of the stored monitoring data; and using XOR algorithm to perform correlation processing on the monitoring data according to judging results; and finally storing compressed data after correlation processing. The method can reduce the degree of data distortion, and has relatively higher data compression efficiency.

Description

technical field [0001] The invention relates to data compression technology, in particular to a data compression method for low-speed field bus. Background technique [0002] On-line monitoring of partial discharge signals inside high-voltage electrical equipment can detect latent insulation defects in time and avoid major accidents. Due to the high frequency of the partial discharge pulse signal, an analog-to-digital converter with a high sampling frequency is usually required during monitoring, which will inevitably result in a large amount of collected data. Most of the early partial discharge on-line monitoring devices adopt a centralized monitoring structure, use high-performance computers for data processing, and use high-speed Ethernet for data transmission. The data processing and transmission capabilities are strong, so it is usually not necessary to consider compressing the monitoring data. question. [0003] In recent years, the on-line monitoring device adoptin...

Claims

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Application Information

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IPC IPC(8): H04L29/06
Inventor 梁文进姚森敬王红斌朱文俊孟源源卢启付李谦王圣李晏
Owner ELECTRIC POWER RES INST OF GUANGDONG POWER GRID