Study on Noise Reduction of Hydrostatic Leveling Signals for Wind Turbine Foundations Based on CEEMDAN-SG Algorithm

Spremljeno u:
Bibliografski detalji
Izdano u:Advances in Civil Engineering vol. 2025 (2025)
Glavni autor: Li, Renjie
Daljnji autori: Lu, Xiangxing, Song, Zhixin, Huanwei Wei, Tan, Fang, Liu, Zhonghua
Izdano:
John Wiley & Sons, Inc.
Teme:
Online pristup:Citation/Abstract
Full Text
Full Text - PDF
Oznake: Dodaj oznaku
Bez oznaka, Budi prvi tko označuje ovaj zapis!

MARC

LEADER 00000nab a2200000uu 4500
001 3186839012
003 UK-CbPIL
022 |a 1687-8086 
022 |a 1687-8094 
024 7 |a 10.1155/adce/3102629  |2 doi 
035 |a 3186839012 
045 2 |b d20250101  |b d20251231 
084 |a 130215  |2 nlm 
100 1 |a Li, Renjie  |u Shandong Electric Power Engineering Consulting Institute Corp., Ltd. Jinan 250013 China 
245 1 |a Study on Noise Reduction of Hydrostatic Leveling Signals for Wind Turbine Foundations Based on CEEMDAN-SG Algorithm 
260 |b John Wiley & Sons, Inc.  |c 2025 
513 |a Journal Article 
520 3 |a The hydrostatic leveling monitoring data related to the settlement of the wind turbine foundation display substantial fluctuations along with considerable noise. In this study, based on the characteristic of the hydrostatic level measurement data of wind turbine foundation, a joint denoising method that integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) algorithm with Savitzky–Golay (SG) filtering is proposed. Several commonly used denoising algorithms were presented to verify the effectiveness of the proposed joint algorithm. The denoising performance of each algorithm was evaluated through quantitative analysis, which included calculating the signal-to-noise ratio, mean square error, and coefficient of determination derived from the simulated signal data. The corresponding results affirm the effectiveness and superiority of the proposed algorithms. Furthermore, the proposed algorithm was employed to mitigate the inherent noise present in field measurement data. Subsequently, a qualitative analysis was undertaken to elucidate the correlation between the denoised results and the fundamental stress state of the actual wind turbine foundation. The results demonstrate that the joint noise reduction method exhibits significant advantages compared to the individual CEEMDAN and SG algorithms. Moreover, the refined hydrostatic leveling signal precisely captures the settlement trends within the wind turbine foundation, providing a clearer understanding of its structural stability and performance. 
653 |a Wind power 
653 |a Accuracy 
653 |a Leveling 
653 |a Wavelet transforms 
653 |a Data smoothing 
653 |a Signal processing 
653 |a Civil engineering 
653 |a Noise control 
653 |a Noise reduction 
653 |a Hydrostatic level 
653 |a Adaptive algorithms 
653 |a Turbines 
653 |a Qualitative analysis 
653 |a Construction 
653 |a Wind 
653 |a Noise measurement 
653 |a Effectiveness 
653 |a Algorithms 
653 |a Wind turbines 
653 |a Structural stability 
653 |a Signal to noise ratio 
653 |a Environmental 
700 1 |a Lu, Xiangxing  |u Shandong Electric Power Engineering Consulting Institute Corp., Ltd. Jinan 250013 China 
700 1 |a Song, Zhixin  |u School of Civil Engineering Shandong Jianzhu University Jinan 250101 China 
700 1 |a Huanwei Wei  |u Key Laboratory of Building Structural Retrofitting and Underground Space Engineering (Ministry of Education) Shandong Jianzhu University Jinan 250101 China 
700 1 |a Tan, Fang  |u Key Laboratory of Building Structural Retrofitting and Underground Space Engineering (Ministry of Education) Shandong Jianzhu University Jinan 250101 China 
700 1 |a Liu, Zhonghua  |u School of Civil Engineering Shandong Jianzhu University Jinan 250101 China 
773 0 |t Advances in Civil Engineering  |g vol. 2025 (2025) 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3186839012/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3186839012/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3186839012/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch