Abstract
The detection of partial discharge (PD) in the field is critically important for the maintenance of electrical power systems. Traditional methods often employ the affine projection algorithm (APA) for denoising PD signals, aiming to retain their fundamental characteristics. However, the conventional APA approach exhibits limitations in effectively eliminating pulse noise. To address this issue, this paper introduces a hyperbolic cosine function and proposes an innovative denoising technique, termed the affine projection exponential hyperbolic cosine algorithm (APEHCA). This enhanced APA-based method is specifically designed to mitigate noise in PD signals. Both simulation and empirical tests substantiate that the newly proposed algorithm excels in system identification and significantly improves the quality of PD signal denoising.
Similar content being viewed by others
Data Availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
Hussein, R., Bashir Shaban, K., El-Hag, A. H.: Denoising of acoustic partial discharge signals corrupted with random noise. IEEE Trans. Dialect. Electr. Insul., 23, pp. 1453–1459 (2016). https://doi.org/10.1109/TDEI.2015.005532.
Wang, P. Mo, F., Zhao, G. et al.: Research on denoising of cables partial discharge based on wavelet and high order PDE. Electrical Meas. Instrument.54(22), 6–10 (2017).
Lan, H., Gao, Y., Ye, H. et al.: Application of partial differential equation to suppress white—noise interference in GIS PD signals. High Voltage Apparat. 49(4), 43–48 (2013).
Ozeki, K., Umeda, T.: An adaptive filtering algorithm using an orthogonal projection to an affine subspace and its properties. Electron. Commun. Jpn. 67(5), 19–27 (1984)
Lu, L., Zhu, G., Yang, X., Zhou, K., Liu, Z., Wu, W.: Affine projection algorithm-based high-order error power for partial discharge denoising in power cables. IEEE Trans. Instrum. Meas. 69(4), 1821–1832 (2020). https://doi.org/10.1109/TIM.2019.2914710
Wang, S., Shi, C., Jiang, Y., et al.: q-affine projection algorithm and its steady-state mean square convergence analysis. J. Electron. Inf. Technol. 40(10), 2402–2407 (2018)
Huang, X., Li, Y., Han, X., Shi, W., Tu, H.: Affine-projection q-Rényi algorithm for channel estimation under different vehicle velocities and impulsive interference. IEEE Trans. Circuits Syst. II Express Briefs. 70(3), 1234–1238.
Zheng, Z., Zhao, H.Q.: Affine projection M-estimate subband adaptive filters for robust adaptive filtering in impulsive noise. Signal Process. 120, 64–70 (2016)
Liang, T., Li, Y., Xue, W., Li, Y., Jiang, T.: Performance and analysis of recursive constrained least Lncosh algorithm under impulsive noises. IEEE Trans. Circuits Syst. II Express Briefs. 68(6), 2217–2221.
Shao, T., Zheng, Y.R., Benesty, J.: An affine projection sign algorithm robust against impulsive interferences. IEEE Signal Process. Lett. 17(4), 327–330 (2010)
Hariri, A., Du, Z., Sui, D., Mashikian, M. S., Jordan, D.: Field location of partial discharge in power cables using an adaptive noise mitigating system. in Proc. IEEE Int. Symp. Elect. Insul. Conf. Rec., pp. 121–125 (1996).
Haykin, S.: Adaptive Filter Theory. Prentice-Hall, Upper Saddle River, NJ, USA (2002)
Kumar, K., Pandey, R., Bhattacharjee, S.S., George, N.V.: Exponential hyperbolic cosine robust adaptive filters for audio signal processing. IEEE Signal Process. Lett. 28, 1410–1414 (2021). https://doi.org/10.1109/LSP.2021.3093862
Chen, F., Li, X., Duan, S., Wang, L., Wu, J.: Diffusion generalized maximum correntropy criterion algorithm for distributed estimation over multitask network. Digit. Signal Process. 81, 16–25 (2018)
Liu, C., Jiang, M.: Robust adaptive filter with lncosh cost. Signal Process. 168, Art. no. 107348 (2020).
Funding
This research was supported by the Jiangsu Provincial Natural Science Foundation (BK20210450).
Author information
Authors and Affiliations
Contributions
XB and WW designed the framework of models. WY,WW and XB studied conception. WW and XB established the experimental platform. XB, SR and HZ collected experimental data. XB, WY, and WW summarized and discussed experimental results. XB and WW wrote the main manuscript text. XB and WW prepared Figs.1–11. All authors reviewed the manuscript.
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Human and Animal Rights
This article does not contain any studies with human or animal subjects performed by any of the authors.
Informed Consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Bao, X., Yan, W., Ren, S. et al. Affine projection algorithm-based exponential hyperbolic cosine for partial discharge denoising in substation. SIViP 18, 3829–3836 (2024). https://doi.org/10.1007/s11760-024-03045-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-024-03045-z