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Power quality monitoring is a theme in vogue and accurate frequency measurement of the power line is a major issue. This problem is particularly relevant for power generating systems since the generated signal must comply with restrictive standards. The novelty of this work is the development of a smart sensor for real-time high-resolution frequency measurement in accordance with international standards for power quality monitoring. The proposed smart sensor utilizes commercially available current clamp, hall-effect sensor or resistor as primary sensor. The signal processing is carried out through the chirp

Power quality monitoring is a theme in vogue and accurate frequency measurement of the power line is a major issue. This problem is particularly relevant for power generating systems as shown in the work of Xue and Yang [

Accurate frequency detection of a periodic signal embedded in noise is a problem that has been largely studied for several applications. Many methodologies [

The novelty of this work is the development of a smart sensor for real-time high-resolution frequency measurement, in accordance with the international standard CEI/IEC 61000-4-30 [

The CZT _{s}_{0} = 2π f_{0}_{1} = 2π f_{1}

In

The transformation kernel
_{R}_{I}

The power spectrum of the CZT

From ^{2} at which the CZT converges, on the high-resolution power spectrum, corresponds to the main frequency component of the discrete signal

The operational architecture for the CZT computation unit of the proposed smart sensor is depicted in _{R}_{I}^{2} is obtained by adding the squared accumulation of _{R}_{I}

In order to find an optimal algorithm that meets the international standard for frequency measurement [_{FFT}_{ZFFT}_{CZT}

_{acq}_{s}_{s}

From

The performance of the proposed smart sensor for real-time high-resolution frequency measurement is tested in this section. The simulation accuracy tests consist in feeding an artificially generated waveform into the proposed smart sensor for confirming its performance and compliance of the international standard CEI/IEC 61000-4-30 [

The analyzed pure periodic signal is described in

The periodic signal contaminated with white noise is described in

The harmonic contamination of the periodic signal is described in ^{nd} harmonic, as depicted in ^{rd} harmonic, as shown in ^{rd} + 5^{th} harmonics, as presented in

The white noise ^{nd} harmonic, as depicted in ^{rd} harmonic, as shown in ^{rd} + 5^{th} harmonics, as presented in

This section presents the application of the proposed smart sensor for frequency estimation in two different study cases. The first study case considers the frequency measurement of the electrical power supply, and the second one considers the frequency measurement of the signal obtained from a Stanford Research DS345 synthesized function generator [

The proposed smart sensor for frequency measurement can be utilized with several primary sensors. For this study case, the standard off-the-shelf current clamp i200s from Fluke is utilized for current monitoring. A 12-bit 4-channel serial-output analog to digital converter ADS7841 [

In this case the frequency is estimated from voltage signals generated by a Stanford Research DS345 synthesized function generator. Similar to the previous case of study, a 12-bit 4-channel serial-output analog to digital converter ADS7841 is used for signal acquisition.

To test the performance of the proposed smart sensor, three experiments are set up considering a 60 Hz sinusoidal signal generated by the DS345 function generator with white noise contamination at 10%, 20%, and 30% of its amplitude for a

A test of linearity to the proposed smart sensor for high resolution frequency estimation is carried out in this section.

An important result of this work is the hardware implementation of a smart sensor for high-resolution frequency detection in real-time applications. The proposed smart sensor is implemented in a low-cost FPGA device reaching operation speeds of 33.74

The proposed smart sensor shows high performance operation, meeting the international standards for frequency measurement even with high-level noise contamination. This is shown in the simulation results where different study cases were treated, with the white-noise-contamination case at

This work presents the development of a smart sensor for frequency estimation in real-time applications. The proposed sensor complies with international standards for frequency measurement in power systems, providing fast and accurate estimations with high resolution and small deviations as demonstrated by the results obtained in linearity test section, different from other methodologies where low resolutions of just decades of Hz are achieved. The proposed smart sensor implementation uses a simple architecture describing recursive functions for the CZT computation utilizing addition, multiplication, and accumulation operations, different from other algorithms using complex mathematics (e.g., FFT) and weighting factors for increasing their resolution (e.g., Zoom-FFT) or implementing the CZT in multiple iterations. The proposed system is considered a smart sensor since it integrates a commercially available current clamp, hall-effect sensor, or resistor as primary sensor, analyzing the corresponding output with digital signal processing techniques in the time domain for estimating the input signal frequency online, with high resolution. Other techniques can use only one kind of primary sensor and require the transformation of the monitored signal into the frequency domain. From the stated above, it can be concluded that the proposed smart sensor for high resolution frequency estimation is a low-cost and efficient solution for real-time application in power systems such as control and protection, thanks to its straightforward FPGA-based implementation that provides an accurate frequency readout every 2 s. complying international standards for power frequency monitoring different from other that either have problems meeting the norm [

This project was partially supported by CONACYT scholarship 312846, and CONCYTEG 08-16-K662-124 ANEXO 02 project.

Block diagram of the frequency-monitoring smart sensor.

Operational structure for the CZT computation unit.

(a) Artificially generated pure periodic signal, (b) CZT power spectrum.

Artificially generated periodic signal with added white noise at

Artificially generated periodic signal contaminated with (a) 2^{nd}, (b) 3^{rd}, (c) (3^{rd} + 5^{th}) harmonics, at 10% of the main periodic signal amplitude for a

Artificially generated periodic signal contaminated with white noise, and (a) 2^{nd}, (b) 3^{rd}, (c) (3^{rd} + 5^{th}) harmonics for a

Instantaneous 1% frequency jump on the power line (a) comparison of the input-signal frequency against the smart-sensor readout, (b) zoomed input signal.

Experiment setup for high-resolution power line frequency estimation utilizing an FPGA-implementation of the proposed smart sensor.

Power supply current.

Experiment setup for high-resolution frequency estimation monitoring voltage signals and utilizing the FPGA-implementation of the proposed smart sensor.

Pure sinusoidal signal with frequency of 59.973 Hz generated by the Stanford Research DS345 synthesized function generator.

60 Hz Sinusoidal signals with white noise contamination at

Linearity test of the proposed smart sensor for high-resolution frequency estimation.

Estimated number of operations and acquisition time comparison.

| |||
---|---|---|---|

65,536 | 65,536 | 512 | |

-- | 512 | 512 | |

1,048,576 | 655,360 | 262,144 | |

_{acq} |
100 | 100 | 1 |

Proposed smart-sensor frequency estimation of a periodic signal with added white noise at

| ||||
---|---|---|---|---|

| ||||

17.0 | 59.9997 | 0.0040 | 0.0003 | 0.0040 |

11.0 | 59.9992 | 0.0066 | 0.0008 | 0.0066 |

7.4 | 60.0007 | 0.0106 | 0.0007 | 0.0106 |

Proposed smart-sensor frequency estimation of a periodic signal contaminated with its 2^{nd}, 3^{rd}, and (3^{rd} + 5^{th}) harmonics, at 10% of the main periodic signal amplitude for a

| ||||
---|---|---|---|---|

| ||||

2^{nd} |
60.0000 | 0.0000 | 0.0000 | 0.0000 |

3^{rd} |
60.0000 | 0.0000 | 0.0000 | 0.0000 |

3^{rd} + 5^{th} |
60.0000 | 0.0000 | 0.0000 | 0.0000 |

Proposed smart-sensor frequency estimation of a periodic signal contaminated with white noise and its 2^{nd}, 3^{rd}, and (3^{rd} + 5^{th}) harmonics for a

| ||||
---|---|---|---|---|

| ||||

2^{nd} |
60.0002 | 0.0042 | 0.0002 | 0.0042 |

3^{rd} |
59.9996 | 0.0032 | 0.0004 | 0.0032 |

3^{rd} + 5^{th} |
59.9999 | 0.0038 | 0.0001 | 0.0038 |

Frequency estimation of a 60 Hz sinusoidal signal contaminated with white noise at

| ||||
---|---|---|---|---|

| ||||

17.0 | 60.0007 | 0.0034 | 0.0007 | 0.0034 |

11.0 | 60.0001 | 0.0064 | 0.0001 | 0.0064 |

7.4 | 60.0020 | 0.0091 | 0.0020 | 0.0091 |