Hossam Eddine Guia; Ammar Soukkou; Redha Meneceur; Abdelkrim Mohrem

Design and Implementation of Real Time RMS Measurement System based on Wavelet Transform Using adsPIC-type Microcontroller

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Author(s)

Hossam Eddine Guia ^1,* Ammar Soukkou ² Redha Meneceur ¹ Abdelkrim Mohrem ³

1. Department of Mechanical Engineering, Faculty of Technology, El-Oued University, 39000 El-Oued, Algeria

2. Faculty of Sciences and Technology, Electronics Department, Jijel University, P.O. Box .98, Ouled-Aissa, Jijel, 18000, Algeria

3. M’Hamed Bougara University of Boumerdés, Boumerdés, Algeria

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2020.06.05

Received: 22 Mar. 2020 / Revised: 26 May 2020 / Accepted: 20 Aug. 2020 / Published: 8 Dec. 2020

Index Terms

Wavelet transform, Root mean square, Electrical energy meter, Real-time measurement system, Digital Signal Processing, microcontroller

Abstract

This paper presents a design and implementation of Root Mean Square (RMS) measurement system based on fast discrete Wavelet using a dsPIC-type microcontroller. For data acquisition, two sensors have been used such as the voltage divider for sensing voltage and the Hall Effect sensor for sensing the current. The proposed method has the real-time calculation advantages and can be used in sinusoidal and non–sinusoidal electrical power systems. The results of calculations have been verified using MATLAB and Proteus ISIS simulations. It has been proved that the Wavelet transform measuring technique is more accurate as it takes in consideration all the harmonics in the analyzed signal and provides temporal information, which is absent in other transforms or not directly available in the Fourier transform.

Cite This Paper

Hossam Eddine Guia, Ammar Soukkou, Redha Meneceur, Abdelkrim Mohrem, " Design and Implementation of Real Time RMS Measurement System based on Wavelet Transform Using adsPIC-type Microcontroller", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.12, No.6, pp. 43-56, 2020. DOI: 10.5815/ijigsp.2020.06.05

Reference

[1] S. Jaiswal, M.S. Ballal, ‘‘FDST-based PQ event detection and energy metering implementation on FPGA-in-the-loop and NI-LabVIEW,’’The Institution of Engineering and Technology Science, Measurement & Technology, vol. 11, no. 4, pp. 453-463, 2017.

[2] L. Angrisani, P. Daponte, M. D’apuzzo, A. Testa, ‘‘A Measurement Method based on the Wavelet Transform for power quality analysis,’’ IEEE Trans. On Power Delivery, vol. 13, pp. 990-998, 1996.

[3] W.-K Yoon, M. J. Devaney, ‘‘Power Measurement using the Wavelet Transform,’’IEEE Trans. On Instrumentation and Measurement, vol. 47, no.5, pp. 1205- 1210, October 1998.

[4] W.-K Yoon, M. J. Devaney, ‘‘Reactive Power Measurement using the Wavelet Transform,’’ IEEE Trans. On Instrumentation and Measurement, vol. 49, no.2, pp. 1205-1210, April 2000.

[5] D. Borras, M. Castilla, N. Moreno, J.C. Montano, ‘‘Wavelet and Neural Structure: A New Tool for Diagnostics of Power System Disturbances,’’ IEEE Trans. On Industry Applications, vol. 37, no. 1, pp. 184-190, Jan./Febr. 2001.

[6] E.Y. Hamid, R. Mardiana, Z.I. Kawasaki, ‘‘Method for RMS and power measurements based on the wavelet packet transform,’’ IEE Proceedings - Science, Measurement and Technology, vol. 149, no. 2, pp. 60-66, 2002.

[7] F.Vatansever, A.Ozdemir, ‘‘A new approach for measuring RMS value and phase angle of fundamental harmonic based on Wavelet Packet Transform,’’ Electric Power Systems Research, vol. 78, no. 1, pp. 74-79, 2009.

[8] J. M.Flores-Arias et al. ‘‘A memory-efficient true-RMS estimator in a limited-resources hardware,’’ Energies, vol. 12, pp. 2-18, 2019.

[9] S.P. Kambleet al.‘‘A Comparative Analysis for Selection of Appropriate Mother Wavelet for Detection of Stationary Disturbances,” Journal of The Institution of Engineers (India): Series B, vol. 98, pp. 533-540, 2017.

[10] J. Modarresi, R.A. Hooshmand, S.M Nosratabadi, ‘‘Enhancement of power measurement using a modified method based on wavelet with preprocessing: electric arc furnace case study,’’ Transactions of the Institute of Measurement and Control, vol 37, no. 9, pp. 1095-1108, 2015.

[11] M.O. Oliveira, J.H. Reversat and L.A Reynoso, ‘‘Wavelet Transform Analysis to Applications in Electric Power Systems,’’ in ‘‘Wavelet Transform and Complexity’’, IntechOpen Publisher, 2019. DOI: 10.5772/intechopen.85274

[12] C. S. Burrus, R. A. Gopinath, and H. Guo, ‘‘Introduction to Wavelets and Wavelet Transform: A Primer,” Englewood Cliffs, NJ: Prentice-Hall, 1998.

[13] A.N. Akansu, R. A. Haddad,‘‘Multi-resolution Signal Decomposition Transforms, Sub-bands, and Wavelets,” Second Edition, New Jersey Institute of Technology Newark, NJ, ACADEMIC PRESS, 2001.

[14] I. Daubechies, Ten Lectures on Wavelets, Philadelphia, PA, USA:Society for Industrial and Applied Mathematics, 1992.

[15] D. T. L. Lee, A. Yamamoto, ‘‘Wavelet analysis: theory and applications,” Hewlett-Packard Journal, pp. 44-54, December 1994.

[16] S. Mallat, “A theory for multi-resolution signal decomposition: the Wavelet representation,” IEEE Trans. on Pattern Analysis And Machine Intelligence, vol. 11, no. 7, pp. 674–693, 1989.

[17] International Electrotechnical Commission. IEC 61000-4-30: 2015. Electromagnetic compatibility (EMC)—Part 4-30: Testing and Measurement Techniques—Power Quality Measurement Methods; International Electrotechnical Commission: Geneva, Switzerland, 2015.

[18] Shannon, E. Claude, ‘‘Communication in the presence of noise,”Proceedings of the Institute of Radio Engineers. (January 1949). Reprint as classic paper in: Proc. IEEE, Vol. 86, No. 2, Feb 1998.

[19] H. Luke, ‘‘The origins of the sampling theorem,” IEEE Comm. Mag., vol. 37, no. 4, pp. 106-108, Apr 1999.

[20] M. Mishali, Y.C. Eldar, ‘‘Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals,” Signal Processing IEEE Transactions on, vol. 57, no. 3, pp. 993-1009, March 2009.

[21] K. M. Siddiqui, K. Sahay, V. K. Giri, ‘‘Early; diagnosis of stator inter-turn fault in inverter driven induction motor by Wavelet transform,” 2016 IEEE 1st International Conference on Power Electronics Intelligent Control and Energy Systems (ICPEICES), pp. 1-6, July 2016.

[22] C.S. Wang, ‘‘Power Disturbance Analysis via Discrete Wavelet Transform,” Wseas Transactions on Power Systems, vol. 9, pp. 208-218, 2014.

[23] L. Labib et al. ‘‘Design and implementation of low-cost universal smart energy meter with demand side load management,” The Institution of Engineering and Technology Generation, Transmission & Distribution, vol. 11 no. 16, pp. 3938-3945, 2017.

[24] Microchip, “High-Performance, 16-bit Digital Signal Controllers”, DS70290F datasheet, 2003.

International Journal of Image, Graphics and Signal Processing (IJIGSP)