Advanced turbine generator torsional vibration evaluation method using Kalman filtering

J. Liška, J. Jakl, S. Kunkel
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Abstract

Turbine generator torsional vibration is becoming a major concern in modern power grids with a high level of changeability due to the operation of renewable energy sources. The traditional absence of standard torsional vibration monitoring and a lack of experience with the operation of torsional vibration monitoring systems opens up a wide range of opportunities for the design of torsional vibration monitoring systems and the possibility of their installation in power plants. As the measured signals are adversely affected by noise, proper filtering is essential for capturing the torsional vibration information. The benefits of the designed Kalman filtering method are the computational efficiency and the possibility of tackling two different types of noise: the state noise and the measurement noise. The feasibility of the proposed method is demonstrated by case studies based on practical signals measured on steam turbine generators.
基于卡尔曼滤波的汽轮发电机扭振评价方法
由于可再生能源的运行,水轮发电机的扭转振动已成为现代电网中一个重要的问题。传统上缺乏标准的扭振监测和缺乏扭振监测系统的运行经验,为扭振监测系统的设计和在电厂安装提供了广泛的机会。由于测量信号受到噪声的不利影响,因此对扭振信息进行适当的滤波是捕获扭振信息的必要条件。所设计的卡尔曼滤波方法的优点是计算效率高,并且可以处理两种不同类型的噪声:状态噪声和测量噪声。以汽轮发电机组实测信号为例,验证了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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