Detection of power quality disturbances with overcomplete dictionary matrix and &amp;#x2113;&lt;inf&gt;1&lt;/inf&gt;-norm minimization

Kathirvel, P.; Manikandan, M. Sabarimalai; Maya, P.; Soman, K. P.

doi:10.1109/icpes.2011.6156684

Cited by 10 publications

(12 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Spikes are observed as impulses superimposed to the fundamental frequency. These are caused by load turning on and off, equipment faults, effect of discharging of stored energy when turned off, lightning, and more 1,15 . The frequency spectrum of the spike is flat.…”

Section: Spikesmentioning

confidence: 99%

“…Transients are the most damaging power disturbances, which is mainly caused by load turning on and off, equipment faults, lightning, and more. Impulsive transients or spikes are short duration burst of energy whose spectrum is flat 1,2,12 . Power signals are those signals having infinite signal energy or their signal power is finite 13 .…”

Section: Introductionmentioning

confidence: 99%

“…Now-a-days most of the equipments such as programmable logic controllers, computer terminals, home appliances, diagnostic systems etc are quite susceptible to power disturbance such as impulsive and oscillatory transients, harmonics, notching, voltage sags, voltage swells, and the power interruptions [1][2][3][4][5][6][7][8][9][10][11] . All these disturbances reduce the quality of service and raise the failure rates.…”

Section: Introductionmentioning

confidence: 99%

“…Various methods are available for the detection of transients. These methods are based on Fast Fourier transform (FFT), wavelet, wavelet packet transforms, short-time Fourier transform (STFT), S-transform, and Wigner-Vue distribution (WVD) [1][2][3][4][5][6][7][8][9][10][11] . Detection and localization of transients is not an easy task because they typically have different shapes, frequency contents, durations and amplitudes which are not known in many systems and applications.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Spike Detection of Disturbed Power Signal Using VMD

Viswanath

Jose

Krishnan

et al. 2015

Procedia Computer Science

View full text Add to dashboard Cite

Most of the electronic equipments are susceptible to power disturbances. Transients are one of the most damaging power disturbances among them. In this paper, a modern adaptive signal decomposition technique called Variational Mode Decomposition (VMD) is used for the detection of impulsive transients or spikes from power signals.VMD decomposes the signal effectively in to several Intrinsic Mode Functions (IMF). Each IMF assumes to have a central frequency. The VMD algorithm focuses on finding these central frequencies and intrinsic mode functions using an optimization methodology called Alternating Direction Method of Multipliers (ADMM). In case of spike on a single tone signal like power signal, it is observed that the information about the original signal is dissolved in any of the modes and also observed that the energy of this mode will be higher when compared to other modes. Using the spectral information of this mode the signature of original signal is preserved. The proposed methodology is found to give good result in case of single tone signals.

show abstract

Section: Spikesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spike Detection of Disturbed Power Signal Using VMD

Viswanath

Jose

Krishnan

et al. 2015

Procedia Computer Science

View full text Add to dashboard Cite

show abstract

“…A set of basic functions take the vector weighted function along with vector coordinate units, namely take [11],…”

Section: The Second Boundary Conditionmentioning

confidence: 99%

Simulation Analysis of Static Characteristics of CJX2-40 Type AC Contactor Electromagnetic Mechanism

Li¹

2014

TOEEJ

View full text Add to dashboard Cite

At present, the finite element method has been widely used in electrical engineering; value has an absolute advantage in the field of solving the problem of position in the electromagnetic boundary. From the perspective of historical development, for solving the electromagnetic boundary value problems, four kinds of methods are used namely; graphical method, simulation method, analytical method and numerical calculation . This study introduced finite element method which has developed rapidly. Before finite element method, numerical calculation method was used, although this method was effective to a certain extent but the results showed that it had a limited range of the electromagnetic boundary value problems to be solved.

show abstract

Simultaneous denoising and compression of power system disturbances using sparse representation on overcomplete hybrid dictionaries

Manikandan

Samantaray

Kamwa

2015

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

This study introduces a novel unified framework for simultaneous denoising and compression of electric power system disturbance signals using sparse signal decomposition and reconstruction on overcomplete hybrid dictionary (OHD) matrix. In the proposed method, the power quality signal is first decomposed into deterministic sinusoidal components and non-deterministic components using the OHD matrix, including discrete impulse dictionary (I), cosine dictionary (C), sine dictionary (S) and the ℓ 1 -norm optimisation algorithm. Then, the hard-thresholding, uniform threshold dead-zone quantisation, modified index coding and Huffman coding techniques are used for compression of significant detail signal samples and approximation coefficients. To justify the selection of OHD matrix, four compression methods are implemented using the decomposition techniques based on the dictionaries Ψ = [I C S] and Ψ = [I C], the wavelet transform (WT) and the discrete cosine transform (DCT). The performance of each method is tested and validated using a wide variety of typical power quality disturbance (PQD) signals taken from the IEEE-1159-PQE and GIM-PQE databases and generated using the Microgrid model. The results show that the method with dictionary Ψ = [I C S] is capable of effectively compressing the PQD signals as well as suppressing the noise components in the signals.

show abstract

Detection of power quality disturbances with overcomplete dictionary matrix and ℓ<inf>1</inf>-norm minimization

Cited by 10 publications

References 13 publications

Spike Detection of Disturbed Power Signal Using VMD

Spike Detection of Disturbed Power Signal Using VMD

Simulation Analysis of Static Characteristics of CJX2-40 Type AC Contactor Electromagnetic Mechanism

Simultaneous denoising and compression of power system disturbances using sparse representation on overcomplete hybrid dictionaries

Contact Info

Product

Resources

About