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access icon openaccess Pre-processing approach for de-noising on-line oil chromatography data based on self-adapting wavelet analysis

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 21/08/2018, Accepted 17/09/2018, Published 01/10/2018

Due to the influence of the external environment and the performance of measuring equipment, the on-line oil chromatography data contains obvious noise which makes the signal to oscillate. The monitoring data is difficult to be directly applied to the equipment state analysis. A novel wavelet-based de-noising method is proposed for pre-processing the on-line oil chromatography data. By analysing the characteristics of on-line oil chromatography data, the method of determining the decomposition layer number based on the probability distribution of wavelet coefficients and the method of determining the threshold value based on outliers conservation are proposed. The improved wavelet de-noising method is applied to analysing the on-line oil chromatography data of a defective ultra-high voltage (UHV) reactor. The results show that the proposed method is feasible and effective.

Inspec keywords: reactors (electric); insulating oils; chromatography; power engineering computing; signal denoising; wavelet transforms

Other keywords: monitoring data; self-adapting wavelet analysis; online oil chromatography data pre-processing approach; threshold value; probability distribution; defective UHV reactor; decomposition layer number; outlier conservation; equipment state analysis; novel wavelet-based denoising method

Subjects: Power engineering computing; Digital signal processing; Transformers and reactors; Integral transforms; Organic insulation; Integral transforms; Signal processing and detection

References

    1. 1)
      • 2. Liu, L., He, W., Liu, Y., et al: ‘Analysis software design of on-line monitoring and fault dianose system for power transmission equipmnent’, Cmput. Syst. Appl., 2011, 8, (8), pp. 27–32.
    2. 2)
      • 3. Liazg, Y., Cao, Y.: ‘Application of transformer oil chromatographic analysis technology to equipmentcondition maintenance’, Transformer, 2011, 12, (12), pp. 67–71.
    3. 3)
      • 1. Sun, C.: ‘Present situation and development of condition on-line monitoring and diagnosetechnology for power transmission and transformation equipment’, Electr. Power, 2005, 38, (2), pp. 1–7.
    4. 4)
      • 6. Guo, B., Yang, X.: ‘Analysis on development and application of monitoring technique for electric power devices in chin’, Power Syst. Techonol., 2004, 23, (8), pp. 65–68.
    5. 5)
      • 4. Guan, G., He, J.: ‘On-line insulation monitoring techniques and condition maintenance of electric equipment’, Transformer, 2004, 39, (z1), pp. 46–50.
    6. 6)
      • 5. Zhang, H., Zhu, S., Zhang, Y., et al: ‘Research and implementation of condition-based maintencance technology system for power transmission and distribution equipment’, Power Syst. Techonol., 2009, 33, (1), pp. 70–73.
http://iet.metastore.ingenta.com/content/journals/10.1049/joe.2018.8362
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