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RMS value measurement based on classical and modified digital signal processing algorithms

机译:基于经典和改进的数字信号处理算法的RMS值测量

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摘要

If the RMS value is obtained by digital processing of a sequence of signal samples, both the uncertainty and the bias of the measured value depend on the algorithm used. Since in practice signal sampling is usually non-coherent, leakage occurs in the signal DFT spectrum and the definition of the RMS of periodic signals in the time domain is violated. This paper presents an overview of estimation of RMS values by comparing five different DSP algorithms of RMS measurements by non-coherent sampling from the point of view of measurement bias and uncertainty for various leakage levels and the data window used. The results of simulations and examples of measurements are evaluated for both monofrequency and multifrequency signals. For non-coherent signal sampling, we compare time domain signal processing based on signal windowing with classical RMS estimation. This is shown to be an effective approach to RMS value measurement. A new method for finding the exact signal frequency by non-coherent sampling is introduced, and a method for effective RMS value bias correction in the frequency domain is presented. Methods for estimating RMS values in the time and frequency domains are compared.
机译:如果RMS值是通过对一系列信号样本进行数字处理而获得的,则不确定性和测量值的偏差都取决于所使用的算法。由于实际上信号采样通常是非相干的,因此在信号DFT频谱中会发生泄漏,并且会违反时域中周期信号RMS的定义。本文通过比较五种不同的DSP算法(通过非相干采样进行的非相干采样)对RMS值进行评估,概述了RMS值的估计,从测量偏差和不确定性的角度考虑了各种泄漏水平以及所使用的数据窗口。对单频和多频信号都评估了仿真结果和测量示例。对于非相干信号采样,我们将基于信号窗口的时域信号处理与经典RMS估计进行了比较。这表明是有效的RMS值测量方法。介绍了一种通过非相干采样找到精确信号频率的新方法,并提出了一种有效的频域RMS值偏差校正方法。比较了在时域和频域中估计RMS值的方法。

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