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Novel Data Compression Algorithm for Transmission Line Condition Monitoring

Author

Listed:
  • Gang Liu

    (Electric Power Research Institute, CSG, Guangzhou 510663, China
    National Engineering Laboratory for UHV Technology, Kunming 651705, China)

  • Lei Jia

    (Electric Power Research Institute, CSG, Guangzhou 510663, China)

  • Taishan Hu

    (Electric Power Research Institute, CSG, Guangzhou 510663, China)

  • Fangming Deng

    (School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China)

  • Zheng Chen

    (Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd., Zhaoqing 526060, China)

  • Tong Sun

    (Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd., Zhaoqing 526060, China)

  • Yanchong Feng

    (Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd., Zhaoqing 526060, China)

Abstract

For the problem of data accumulation caused by massive sensor data in transmission line condition monitoring system, this paper analyzes the type and amount of data in the transmission line sensor network, compares the compression algorithms of wireless sensor network data at home and abroad, and proposes an efficient lossless compression algorithm suitable for sensor data in transmission line linear heterogeneous networks. The algorithm combines the wavelet compression algorithm and the neighborhood index sequence algorithm. It displays a fast operation speed and requires a small amount of calculation. It is suitable for battery powered wireless sensor network nodes. By combining wavelet correlation analysis and neighborhood index sequence coding, the compression algorithm proposed in this paper can achieve a high compression rate, has strong robustness to packet loss, has high compression performance, and can help to reduce network load and the packet loss rate. Simulation results show that the proposed method achieves a high compression rate in the compression of the transmission line parameter dataset, is superior to the existing data compression algorithms, and is suitable for the compression and transmission of transmission line condition monitoring data.

Suggested Citation

  • Gang Liu & Lei Jia & Taishan Hu & Fangming Deng & Zheng Chen & Tong Sun & Yanchong Feng, 2021. "Novel Data Compression Algorithm for Transmission Line Condition Monitoring," Energies, MDPI, vol. 14(24), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:24:p:8275-:d:698045
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    Cited by:

    1. Radim Hercik & Radek Svoboda, 2023. "Collecting and Pre-Processing Data for Industry 4.0 Implementation Using Hydraulic Press," Data, MDPI, vol. 8(4), pages 1-14, April.

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