在风机故障监测中,同步采集和同步分析技术能够有效地减缓风机变速旋转导致的频谱能量弥散现象，使损伤特征频率能量集中，从而易于实现故障的精准检测。然而由于现有的风机故障检测系统通常并未配有速度传感器，因此从风机振动信号中提取瞬时轴相位是实现同步采集与分析技术的前提和关键。现有的相位解调轴速提取方法往往由于带宽的选择问题导致难以得到较为精确的相位信息，本文提出了一种优化轴速提取方法(OSSE)，该方法基于代价函数脊线追踪(OSCF)、最优带宽搜索及基于解析信号的相位解调方法对风机轴速进行提取。仿真结果表明，本方法能够获得精确的相位信息，使用该相位信息对原始振动信号同步重采集，可以得到清晰的阶次谱。最后利用某风场实际采集的风机振动数据进行验证，所得结论与仿真结果一致，证明了本方法的有效性和准确性。
Abstract
In wind turbine condition monitoring, application of synchronous resampling and synchronous analysis techniques can greatly alleviate the spectral energy dispersion phenomenon caused by the variable speed operations so that it is easier to realize damage feature extraction. However, the existing wind turbine condition monitoring system is usually not equipped with the speed sensor, therefore, extracting the shaft instantaneous phase from the measured vibration responses is the key to realize synchronous resampling and synchronous analysis techniques. The existing speed extraction methods with phase demodulation are often difficult to obtain accurate phase information due to the problem of bandwidth selection and other restrictions. In this paper, an optimal shaft speed extraction (OSSE) based on the combination of one-step cost function (OSCF), optimal bandwidth searching and Hilbert phase demodulation to extract the shaft instantaneous speed of wind turbine. The simulation results show that the proposed method can obtain accurate phase information. Using this phase signal to synchronously resampling the vibration signal and carry out the spectrum analysis, a clearer order spectrum can be obtained. Finally, the vibration data from a real wind turbine operation are used to verify the proposed method. The analysis results derive the similar conclusions as those from simulations. The effectiveness and accuracy of the proposed method are demonstrated.
关键词
瞬时转速 /
瞬时相位 /
同步采集 /
故障检测 /
风力发电机
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Key words
instantaneous speed /
instantaneous phase /
synchronous resampling /
fault detection /
wind turbine
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参考文献
[1] Kandukuri S T, Klausen A, Karimi H R, et al. A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management[J]. Renewable and Sustainable Energy Reviews, 2016, 53: 697-708.
[2] Teng W, Ding X, Tang S, et al. Vibration analysis for fault detection of wind turbine drivetrains—a comprehensive investigation[J]. Sensors, 2021, 21(5): 1686.
[3] Hameed Z, Hong YS, Choa YM, Ahn SH, Song CK. Condition monitoring and fault detection of wind turbines and related algorithms: a review. Renewable and Sustainable Energy Reviews 2009; 13: 1-39.
[4] Liu X, Du J, Ye Z S. A Condition Monitoring and Fault Isolation System for Wind Turbine based on SCADA Data[J]. IEEE Transactions on Industrial Informatics, 2021.
[5] Zhang Y, Lu W, Chu F. Planet gear fault localization for wind turbine gearbox using acoustic emission signals[J]. Renewable Energy, 2017, 109: 449-460.
[6] Márquez F P G, Tobias A M, Pérez J M P, et al. Condition monitoring of wind turbines: Techniques and methods[J]. Renewable energy, 2012, 46: 169-178.
[7] Teng W, Ding X, Tang S, et al. Vibration Analysis for Fault Detection of Wind Turbine Drivetrains—A Comprehensive Investigation[J]. Sensors, 2021, 21(5): 1686.
[8] Hu T, Wan H, Luo H. Vibration-based synchronous sampling and its application in wind-turbine drive-train-condition monitoring[J]. Clean Energy, 2021, 5(1): 79-92.
[9] Lu S, Yan R, Liu Y, et al. Tacholess speed estimation in order tracking: A review with application to rotating machine fault diagnosis[J]. IEEE Transactions on Instrumentation and Measurement, 2019, 68(7): 2315-2332.
[10] Peeters C, Leclere Q, Antoni J, et al. Review and comparison of tacholess instantaneous speed estimation methods on experimental vibration data[J]. Mechanical Systems and Signal Processing, 2019, 129: 407-436.
[11] Urbanek J, Barszcz T, Sawalhi N, et al. Comparison of amplitude-based and phase-based method for speed tracking in application to wind turbines [J]. Metrology and measurement systems, 2011, 18(2): 295-303.
[12] Wang J, He Q, Kong F. A new synthetic detection technique for trackside acoustic identification of railroad roller bearing defects [J]. Applied acoustics, 2014, 85: 69-81.
[13] Jiang X, Li S. A dual path optimization ridge estimation method for condition monitoring of planetary gearbox under varying-speed operation [J]. Measurement, 2016, 94: 630-644.
[14] Coats M D, Randall R B. Order-Tracking with and without a tacho signal for gear fault diagnostics[C]. Proceedings of Acoustics. 2012: 1-6.
[15] Coats M D, Randall R B. Single and multi-stage phase demodulation based order-tracking[J]. Mechanical Systems and Signal Processing, 2014, 44(1-2): 86-117.
[16] Randall R, Smith W. Use of the Teager Kaiser Energy Operator to estimate machine speed[C]. PHM Society European Conference. 2016: 3(1).
[17] Urbanek J, Barszcz T, Antoni J. A two-step procedure for estimation of instantaneous rotational speed with large fluctuations[J]. Mechanical Systems & Signal Processing, 2013, 38(1):96-102.
[18] McFadden P D. Interpolation techniques for time domain averaging of gear vibration[J]. Mechanical systems and signal processing, 1989, 3(1): 87-97.
[19] Večeř P, Kreidl M, Šmíd R. Condition indicators for gearbox condition monitoring systems[J]. Acta Polytechnica, 2005, 45(6):35-43.
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