应用“最坏情况”法估计由ADC缺陷引起的频谱和功率测量误差

A. Serov
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引用次数: 1

摘要

复频谱作为计算实际电网信号频谱和功率参数的基本参数。对于复频谱的测量,最常用的是离散傅里叶变换技术。模数转换器用于将电压和电流样本转换为数字形式。模数转换器的转换功能不理想。对光谱测量误差贡献最大的是量化误差和非线性的影响,因为这些分量几乎不可能通过偏移调整和校准来减小。“最坏情况”法可用于估计频谱、电功率等参数的测量误差。这种方法可以“从上面”估计考虑参数的测量误差,这使得它在误差估计必须超过其实际值的应用中很有需要。得到了由量化误差和非线性引起的频谱和功率参数误差估计计算的解析关系式。研究了输入信号参数和模数转换器参数对测量参数误差的影响。在Matlab环境下进行仿真建模,估计了非线性形式对所考虑参数测量误差的影响。结果表明,对于所有考虑的非线性形式,误差估计结果不超过“最坏情况”方法估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the “Worst Case” Method to Estimate the Spectrum and Power Measurement Error Caused by ADC Imperfection
The complex spectrum is used as a basic parameter for calculating spectrum and power parameters of the signals of real electrical power grids. For measuring the complex spectrum, the most popular is the discrete Fourier transform technique. Analog-to-digital converters are used to convert voltage and current samples to the digital form. The conversion function of analog-to-digital converters is not ideal. The largest contribution to the spectrum measurement error is due to the influence of quantization error and nonlinearity, since these components almost impossible to reduce by offset-adjustment and calibration. The “worst case” method can be applied to estimate the measurement error of the spectrum, electric power and other parameters. This method makes it possible to estimate “from above” the measurement error of considerate parameters, which makes it in demand in applications where the error estimate must necessarily exceed its real value. The analytical relationships are obtained for calculation of the error estimation of spectrum and power parameters caused by quantization error and nonlinearity. The influence of parameters of input signals and analog-to-digital converter on the error of the measured parameters is investigated. The influence of the nonlinearity form on the measurement error of considered parameters is estimated by simulation modeling in Matlab environment. It is shown that for all the considered nonlinearity forms, the error estimation result does not exceed the “worst case” method estimation.
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