A Review of Streamline Calibration Approaches for Digital Storage Oscilloscopes with Time-Interleaved Channels

Bonavolontà, Francesco; D’Arco, Mauro; Benedetto, Egidio De; Dallet, Dominique; Tedesco, Annarita

doi:10.1109/mim.2021.9448259

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…For the accuracy level used for measurement, the standard frequency range should be 99%~101% of the rated frequency, that is, the standard frequency is within the range of 49.5Hz~50.5Hz. Therefore, when the frequency fluctuates, the actual sampling cannot meet the synchronous sampling conditions, which will inevitably affect the results of electric energy measurement [14][15].…”

Section: The Influence Of Signal Frequency Offsetmentioning

confidence: 99%

Error Analysis of Digital Electric Energy Metering Based on FPGA

Zheng¹,

Yan²,

Luo³

2022

J. Phys.: Conf. Ser.

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With the emergence and development of smart grid, digital meters have been widely used in substations, so the research on digital energy metering error has become a research hotspot. The purpose of this paper is to analyze the error of digital power measurement based on FPGA, mainly take the analog input fusion module and digital power meter in the digital power measurement system as the research object, and analyze the source of measurement error. An FPGA-based energy metering error detection platform is built to analyze the energy metering error when there are harmonics in the full energy metering method currently used by most digital energy meter manufacturers. The comparative analysis of numerical integration algorithms shows that the asymmetric distortion rates of the simulated waveforms are approximate. The results of measurement error analysis under harmonic conditions show that when the number of sampling points per cycle is 60, the power measurement errors of the 2nd to 4th harmonics are equivalent. The magnitude of the measurement error is still consistent with other low-order harmonics, and the simulation results are consistent with the theoretical analysis results.

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Section: The Influence Of Signal Frequency Offsetmentioning

confidence: 99%

Error Analysis of Digital Electric Energy Metering Based on FPGA

Zheng¹,

Yan²,

Luo³

2022

J. Phys.: Conf. Ser.

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“…Channel mismatches are traditionally classified into static gain, time skew, and offset mismatches. A great deal of research has been devoted to the compensation of the three mismatches in the analog and digital domains [6][7][8][9][10][11][12][13]. The calibration methods utilize an "estimation-correction" strategy, where the mismatch coefficients are estimated first and subsequently a correction structure is designed based on the estimation results.…”

Section: Introductionmentioning

confidence: 99%

Hadamard transformation based frequency response mismatch calibration for a 4-channel TIADC

Qian,

Zheng,

Mei

et al. 2024

J. Inst.

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The time-interleaved analog-to-digital converter (TIADC) is one of the most effective solutions for improving the sampling rate of acquisition systems. However, the frequency response mismatch between channels can seriously degrade the performance of the system. In this paper, we propose a calibration method for frequency response mismatches in 4-channel TIADC systems. Following the construction of a four-channel TIADC model using a four-order Hadamard matrix, the error signals were extracted using three time-invariant filters and subsequently subtracted from the output to complete the calibration. It uses the Hadamard transform instead of the complex exponential modulator used in conventional time-varying filter methods, which can further simplify the signal processing without the necessity of complicated calculations. We have employed a stimulated four-channel TIADC system to validate the effectiveness of the proposed calibration technique. Moreover, in a commercial 12.5 GSPS four-channel TIADC system, it is also demonstrated that this approach is effective in improving the spurious-free dynamic range of the system.

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