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Permanent magnet generator turn fault detection using Kalman filter technique

机译:使用卡尔曼滤波技术的永磁发电机转向故障检测

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In this paper, a stator turn fault detection strategy is developed for a permanent magnet (PM) generator system. Unlike conventional power generation systems, the output of the PM generator is directly rectified by an uncontrolled diode bridge. The only accessible signal is the DC link current/voltage. As a result, most existing detection techniques based on the phase current/voltage signals are not applicable. Instead, the 2nd and 6th harmonics of the DC link current are exploited for turn fault detection and they are extracted by a Kalman filter. It is shown that the phase unbalance caused by a turn fault gives rise to significant increase in the 2nd harmonic DC link current. Consequently, the dominant harmonic under healthy and fault conditions are of the 6th and 2nd orders, respectively. Hence, the turn fault can be detected by comparing the magnitudes of the two harmonics. The detection method is assessed by extensive simulation under various fault scenarios. It is shown that the developed Kalman filter method exhibits significant advantages in response time and computation effort than online fast Fourier transform (FFT) based techniques.
机译:在本文中,为永磁(PM)发电机系统开发了定子匝间故障检测策略。与常规发电系统不同,PM发电机的输出由不受控制的二极管电桥直接整流。唯一可访问的信号是直流母线电流/电压。结果,基于相电流/电压信号的大多数现有检测技术不适用。取而代之的是,将直流母线电流的二次谐波和二次谐波用于转向故障检测,并由卡尔曼滤波器提取。结果表明,由匝道故障引起的相位不平衡会导致二次谐波直流母线电流显着增加。因此,在健康状态和故障状态下的主要谐波分别为6阶和2阶。因此,可以通过比较两个谐波的幅度来检测转向故障。通过在各种故障情况下的广泛仿真来评估该检测方法。结果表明,与基于在线快速傅立叶变换(FFT)的技术相比,改进的卡尔曼滤波方法在响应时间和计算工作量方面显示出显着优势。

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