Interpolated-DFT-Based Fast and Accurate Amplitude and Phase Estimation for the Control of Power

The quality of energy produced in renewable energy systems has to be at the high level specified by respective standards and directives. The estimation accuracy of grid signal parameters is one of the most important factors affecting this quality. This paper presents a method for a very fast and accurate amplitude and phase grid signal estimation using the Fast Fourier Transform procedure and maximum decay sidelobes windows. The most important features of the method are the elimination of the impact associated with the conjugate's component on the results and the straightforward implementation. Moreover, the measurement time is very short - even far less than one period of the grid signal. The influence of harmonics on the results is reduced by using a bandpass prefilter. Even using a 40 dB FIR prefilter for the grid signal with THD = 38%, SNR = 53 dB and a 20-30% slow decay exponential drift the maximum error of the amplitude estimation is approximately 1% and approximately 0.085 rad of the phase estimation in a real-time DSP system for 512 samples. The errors are smaller by several orders of magnitude for more accurate prefilters.Comment: in Metrology and Measurement Systems, 201

The Influence of Power Network Disturbances on Short Delayed Estimation of Fundamental Frequency Based on IpDFT Method with GMSD Windows

This paper presents an application of the IpDFT spectrum interpolation method to estimate the fundamental frequency of a power waveform. Zero-crossing method (ZC) with signal prefiltering was used as a reference method. Test models of disturbances were applied, based on real disturbances recorded in power networks, including voltage harmonics and interharmonics, transient overvoltages, frequency spikes, dips and noise. It was determined that the IpDFT method is characterized by much better dynamic parameters with better estimation precision. In an example, in the presence of interharmonics, the frequency estimation error was three times larger for the reference method than that for the IpDFT method. Furthermore, during the occurrence of fast transient overvoltages, the IpDFT method reached its original accuracy about three times faster than the ZC method. Finally, using IpDFT, it was possible to identify the type of disturbances: impulsive, step changes of frequency or voltage dips

Coal disintegration using high pressure water jet

U radu se opisuje drobljenje ugljena primjenom vodenog mlaza pod visokim pritiskom. Daje se prototip aparata s vodenim mlazom za usitnjavanje ugljena primjenom te metode. Ispitivane su tri različite vrste ugljena: antracit, lignit i drveni. Dobiveni rezultati ukazuju na veliku učinkovitost primjene visokotlačnog vodenog mlaza u tu svrhu. Lignit je pogodniji za obradu tom metodom nego antracit dok je najintenzivnije usitnjavanje karakteristično za drveni ugljen. Takav efekt mikronizacije daje čak više od 100 000 puta povećanje njegove specifične površine u usporedbi s normalnim finim ugljenom nakon tradicionalnog usitnjavanja. Uz to, pogodnost drvenog ugljena za intenzivno hidro-drobljenje razlog je mogućnosti postizanja najsitnije strukture, a to je dobra prognoza za njegovu modifikaciju u bio-gorivo.The paper presents coal comminution utilizing high-pressure water jet. Prototype of hydrojetting apparatus for coal disintegration with this method is presented. Three different types of coal were examined: hard-, brown-, and charcoal. Obtained results point out that high-pressure water jet usage for such purpose is very effective. Brown coal is more susceptible to this method treatment than the hard one whereas the most intensive disintegration is characteristic for charcoal. Such micronization effect gives even over 100 000 time\u27s increase of its specific surface compared to normal fine coal after traditional comminution. Moreover, charcoal susceptibility for intensive hydro-comminution is the reason why one can get the most comminuted structure, this being a good prognosis for its modification into bio-fuels

Single-ended quality measurement of a music content via convolutional recurrent neural networks

The paper examines the usage of Convolutional Bidirectional Recurrent Neural Network (CBRNN) for a problem of quality measurement in a music content. The key contribution in this approach, compared to the existing research, is that the examined model is evaluated in terms of detecting acoustic anomalies without the requirement to provide a reference (clean) signal. Since real music content may include some modes of instrumental sounds, speech and singing voice or different audio effects, it is more complex to analyze than clean speech or artificial signals, especially without a comparison to the known reference content. The presented results might be treated as a proof of concept, since some specific types of artefacts are covered in this paper (examples of quantization defect, missing sound, distortion of gain characteristics, extra noise sound). However, the described model can be easily expanded to detect other impairments or used as a pre-trained model for other transfer learning processes. To examine the model efficiency several experiments have been performed and reported in the paper. The raw audio samples were transformed into Mel-scaled spectrograms and transferred as input to the model, first independently, then along with additional features (Zero Crossing Rate, Spectral Contrast). According to the obtained results, there is a significant increase in overall accuracy (by 10.1%), if Spectral Contrast information is provided together with Mel-scaled spectrograms. The paper examines also the influence of recursive layers on effectiveness of the artefact classification task

Influence of the DC offset on the DFT-based frequency estimation for noised multifrequency signals in PV systems with a DSP processor

Digital signal processing is present in many areas of industry and science. One of them is analyzing multifrequency signals, e.g. in photovoltaic systems. This paper focuses on the frequency estimation of pure signals and signals distorted by AWGN noise in the presence of a DC voltage offset. The used IpDFT estimation method is based on the FFT procedure, I class Rife-Vincent time windows and three points of the spectrum taken to calculations. Measurement time was limited only up to two cycles of a tested signal and the method is very accurate even below one cycle. Obtained results show that additional DC component negatively affect the accuracy. The paper can be very useful because it shows properties of the method in real measurement conditions for various values of parameters

Interpolated-DFT-Based Fast and Accurate Amplitude and Phase Estimation for the Control of Power

Quality of energy produced in renewable energy systems has to be at the high level specified by respective standards and directives. One of the most important factors affecting quality is the estimation accuracy of grid signal parameters. This paper presents a method of a very fast and accurate amplitude and phase grid signal estimation using the Fast Fourier Transform procedure and maximum decay side-lobes windows. The most important features of the method are elimination of the impact associated with the conjugate’s component on the results and its straightforward implementation. Moreover, the measurement time is very short ‒ even far less than one period of the grid signal. The influence of harmonics on the results is reduced by using a bandpass pre-filter. Even using a 40 dB FIR pre-filter for the grid signal with THD ≈ 38%, SNR ≈ 53 dB and a 20‒30% slow decay exponential drift the maximum estimation errors in a real-time DSP system for 512 samples are approximately 1% for the amplitude and approximately 8.5・10‒2 rad for the phase, respectively. The errors are smaller by several orders of magnitude with using more accurate pre-filters

Influence of the DC offset on the DFT-based frequency estimation for noised multifrequency signals in PV systems with a DSP processor

Digital signal processing is present in many areas of industry and science. One of them is analyzing multifrequency signals, e.g. in photovoltaic systems. This paper focuses on the frequency estimation of pure signals and signals distorted by AWGN noise in the presence of a DC voltage offset. The used IpDFT estimation method is based on the FFT procedure, I class Rife-Vincent time windows and three points of the spectrum taken to calculations. Measurement time was limited only up to two cycles of a tested signal and the method is very accurate even below one cycle. Obtained results show that additional DC component negatively affect the accuracy. The paper can be very useful because it shows properties of the method in real measurement conditions for various values of parameters

Influence of A/D Quantization in an Interpolated DFT Based System of Power Control with A Small Delay

Fast and accurate grid signal frequency estimation is a very important issue in the control of renewable energy systems. Important factors that influence the estimation accuracy include the A/D converter parameters in the inverter control system. This paper presents the influence of the number of A/D converter bits b, the phase shift of the grid signal relative to the time window, the width of the time window relative to the grid signal period (expressed as a cycle in range (CiR) parameter) and the number of N samples obtained in this window with the A/D converter on the developed estimation method results. An increase in the number b by 8 decreases the estimation error by approximately 256 times. The largest estimation error occurs when the signal module maximum is in the time window center (for small values of CiR) or when the signal value is zero in the time window center (for large values of CiR). In practical applications, the dominant component of the frequency estimation error is the error caused by the quantization noise, and its range is from approximately 8×10-10 to 6×10-4