Key Technology in Wind Turbine Transmission System Condition Monitoring: A Review

Abstract:

Key technology for the transmission system of wind turbine condition monitoring is researched in this paper. It gives a summary overview, including monitoring methods, signal processing methods and state recognition technology, data acquisition and transmission technology, programming languages. Understanding of the progress of the field is to provide technical reference and research inspiration for insiders.

• Periodical: Applied Mechanics and Materials (Volume 442)
• Pages: 304-310
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.442.304
• Online since: October 2013
• Authors: Hai Jiang Dong, Chun Hua Zhao*, Shi Qing Wan, Xian You Zhong, Wei Wang
• Keywords: Condition Monitoring, Key Technology, Transmission System, Wind Turbine (WT)

References

[1] Tang Xin'an. Fault Diagnosis of 600KW Wind Turbine (in Chinese). Hohhot: Xinjiang University (2006).

[2] Yang Wenxian, Court Richard, Tavner Peter J, et al. Bivariate empirical mode decomposition and its contribution to wind turbine condition monitoring. Journal of Sound and Vibration 2011; 330(15): 3766-3782.

DOI: 10.1016/j.jsv.2011.02.027

[3] Luisa F Villa, Aníbal Reñones, Jose R Perán, et al. Statistical fault diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load. Mechanical Systems and Signal Processing 2012; (29): 436–446.

DOI: 10.1016/j.ymssp.2011.12.013

[4] Guo Peng, Li Linlin, Ma Dengchang. Wind Turbine Gearbox Condition Monitoring With IPSO-BP (in Chinese). Acta Energiae Solaris Sinica 2012; 33(3): 439-445.

[5] Guo Peng, David Infield, Yang Xiyun. Wind Turbine Gearbox Condition Monitoring Using Temperature Trend Analysis (in Chinese). Proceedings of the CSEE 2011; 31(32): 129-136.

[6] K Nienhaus, M Hilbert, R Baltes. Statistical and time domain signal analysis of the thermal behaviour of wind turbine drive train components under dynamic operation conditions. Journal of Physics 2012; (364): 1-11.

DOI: 10.1088/1742-6596/364/1/012132

[7] Fausto Pedro García Márquez, Andrew Mark Tobias, Jesús María Pinar Pérez, et al. Condition monitoring of wind turbines: Techniques and methods. Renewable Energy 2012; (46): 169-178.

DOI: 10.1016/j.renene.2012.03.003

[8] Lu Wenxiu, Chu Fulei. Condition Monitoring and Fault Diagnostics of Wind Turbines. Prognostics and Health Management Conference 2010; 1-11. Online, http: /ieeexplore. ieee. org/ stamp/stamp. jsp?tp=&arnumber=5413527. [Accessed on April 10, 2013].

DOI: 10.1109/phm.2010.5413527

[9] Slim Soua, Paul Van Lieshout, Asanka Perera, et al. Determination of the combined vibrational and acoustic emission signature of a wind turbine gearbox and generator shaft in service as a pre-requisite for effective condition monitoring. Renewable Energy 2013; (51): 175-181.

DOI: 10.1016/j.renene.2012.07.004

[10] Kusiak Andrew, Li Wenyan. The prediction and diagnosis of wind turbine faults. Renewable Energy 2011; 36(1): 16-23.

DOI: 10.1016/j.renene.2010.05.014

[11] Meik Schlechtingen, Ilmar Ferreira Santos, Sofiane Achiche. Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 1: System description. Applied Soft Computing 2013; (13): 259–270.

DOI: 10.1016/j.asoc.2012.08.033

[12] Jacek Urbanek, Tomasz Barszcz, Radosław Zimroz, et al. Application of averaged instantaneous power spectrum for diagnostics of machinery operating under non-stationary operational conditions. Measurement 2012; (45): 1782–1791.

DOI: 10.1016/j.measurement.2012.04.006

[13] Wenxian Yang, Richard Court, Jiesheng Jiang. Wind turbine condition monitoring by the approach of SCADA data analysis. Renewable Energy 2013; (53): 365-376.

DOI: 10.1016/j.renene.2012.11.030

[14] Zhang Zhaohuang, Ding Xian, Liu Man, et al. Based on wavelet transform of fault diagnosis and analysis of wind turbine transmission system (in Chinese). Journal of Basic Science and Engineering 2011; 19(s): 210-218.

[15] Yang Wenxian, Tavner P J, Crabtree C J, et al. Cost-effective condition monitoring for wind turbines. IEEE Transactions Industrial Electronics 2010; 57(1): 263-271.

DOI: 10.1109/tie.2009.2032202

[16] Jiang Yonghua, Tang Baoping, Qin Yi, et al. Feature extraction method of wind turbine based on adaptive Morlet wavelet and SVD. Renewable Energy 2011; (36): 2146-2153.

DOI: 10.1016/j.renene.2011.01.009

[17] An Xueli, Jiang Dongxiang, Li Shaohua, et al. Application of the ensemble empirical mode decomposition and Hilbert transform to pedestal looseness study of direct-drive wind turbine. Energy 2011; 36(09): 5508-5520.

DOI: 10.1016/j.energy.2011.07.025

[18] Zhipeng Feng, Ming Liang, Yi Zhang, et al. Fault diagnosis for wind turbine planetary gearboxes via demodulation analysis based on ensemble empirical mode decomposition and energy separation. Renewable Energy 2012; (47): 112-126.

DOI: 10.1016/j.renene.2012.04.019

[19] Wang Min, Liu Jia, Gu Yu-jiong, et al. The composite fault identification for wind turbine gearbox based on the IMF envelopment analysis (in Chinese). Renewable Energy Resources 2012; 30(11): 45-49.

[20] W.Y. Liu, W.H. Zhang, J.G. Han, et al. A new wind turbine fault diagnosis method based on the local mean decomposition. Renewable Energy 2012; (48): 411-415.

DOI: 10.1016/j.renene.2012.05.018

[21] An Xueli, Jiang Dongxiang, Liu Chao, et al. Bearing Fault Feature Extraction of Wind Turbine Based on Intrinsic Time-scale Decomposition (in Chinese). Automation of Electric Power Systems 2012; 36(5): 41-44.

[22] An Xueli, Jiang Dongxiang, Chen Jie, et al. Bearing fault diagnosis based on ITD and LS-SVM for wind turbine (in Chinese). Electric Power Automation Equipment 2011; 31(9): 10-13.

[23] Luisa F Villa, Aníbal Reñones, Jose R Perán, et al. Angular resampling for vibration analysis in wind turbines under non-linear speed fluctuation. Mechanical Systems and Signal Processing 2011; 25: 2157-2168.

DOI: 10.1016/j.ymssp.2011.01.022

[24] Liu Wenyi, Wang Zhenfeng, Han Jiguang, et al. Wind turbine fault diagnosis method based on diagonal spectrum and clustering binary tree SVM. Renewable Energy 2013; (50): 1-6.

DOI: 10.1016/j.renene.2012.06.013

[25] Long Quan, Liu Yongqian, Yang Yongping. Fault Diagnosi Method of Wind Turbine Gearbox Based on BP Neural Network Trained by Partical Swarm Optinization Algorithm (in Chinese). Acta Energiae Solaris Sinica 2012; 33(1): 120-125.

[26] Lu Y, Tang J, Luo H. Wind Turbine Gearbox Fault Detection Using Multiple Sensors With Features Level Data Fusion. Journal of Engineering for Gas Turbines and Power 2012; 134.

DOI: 10.1115/1.4004438

[27] Yang Zhiling, Wang Bin , Dong Xinghui. Expert System of Fault Diagnosis for Gear Box in Wind Turbine. Systems Engineering Procedia 2012; (4): 189–195.

DOI: 10.1016/j.sepro.2011.11.065

[28] Yang Yanli, Miao Changyun. Remote Monitoring for Wind Turbines Based on Multirate Signal Processing (in Chinese). Journal of Vibration, Measurement & Diagnosis 2012; 32(3): 498-501.

[29] Wei Qing, Ye Anli, Ma Hongyan. System for Wind Turbine Gearbox Fault Diagnosis Based on ZigBee (in Chinese). Journal of Beijing University of Civil Engineering and Architecture 2012; 28(3): 44-47.

[30] Qin Kang. The Research and Design of A Wind Turbine Vibration Monitoring System Based on GPRS (in Chinese). Changsha: Hunan University (2011).

[31] X Ma, G Wang, P Cross. A remote condition monitoring system for wind-turbine based DG systems. Journal of Physics 2012; (364): 1-6.

DOI: 10.1088/1742-6596/364/1/012129

[32] Edzel Lapira, Dustin Brisset, Hossein Davari Ardakan. Wind turbine performance assessment using multi-regime modeling approach. Renewable Energy 2012; (45): 86-95.

DOI: 10.1016/j.renene.2012.02.018

[33] Li Xiaolong. Research on the Mechanical Fault Diagnosis Information System of Large-Scale Wind Turbine (in Chinese). Qinghuangdao: Yanshan University (2011).

[34] Bo Lin, Liu Xiaofeng, He Xingxi. Measurement system for wind turbines noises assessment based on LabVIEW. Measurement: Journal of the International Measurement Confederation. 2011; 44(2): 445-453.

DOI: 10.1016/j.measurement.2010.11.007

[35] Lin Jinshan, Dou Chunhong. Design of gearbox fault diagnosis system based on LabVIEW. Proceedings-2010 3rd International Congress on Image and Signal Processing, CISP 2010. 2010; 4206-4208.

DOI: 10.1109/cisp.2010.5646823

[36] Xu Haosong, Zheng Xiaoxia. Fault Diagnosis System of Wind Turbine Rolling Bearing Based on LabVIEW and Simulation (in Chinese). Journal of Shanghai University of Electric Power 2011; 27(6): 563-567.

[37] Guo Xin, Cao Guohua. Design of Wind Turbines Vibration Monitoring System Based on STM32 (in Chinese). 2011(9): 61-70.

[38] M. Elforjani, D. Mba, A. Muhammad, A. Sire. Condition monitoring of worm gears. Applied Acoustics. 2012; 73(8): 859-863.

DOI: 10.1016/j.apacoust.2012.03.008

[39] B. S. Prasad, M. M. Sarcar, B. Satish Ben. Surface textural analys is using acousto opticemission-and vision-based 3D surface topography —a base for online tool condition monitoring in face turning. Int J Adv Manuf Technol. 2011; 55: 1025–1035.

DOI: 10.1007/s00170-010-3127-z

[40] T.H. Loutas, D. Roulias, E. Pauly, et al. The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery. Mechanical Systems and Signal Processing. 2011; 25(4): 1339-1352.

DOI: 10.1016/j.ymssp.2010.11.007