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This article introduces a frequency-adaptive control strategy for a three-phase shunt active power filter, aimed at improving energy efficiency and ensuring high power quality in consumer-oriented power systems. The proposed control system utilizes real-time frequency estimation to dynamically adjust the gain of a proportional-integral–resonant (PIR) controller, facilitating precise harmonic compensation under challenging unbalanced grid conditions, such as unbalanced three-phase loads, grid impedance variations, and diverse nonlinear loads like three-phase rectifiers and induction motors. These scenarios often increase total harmonic distortion (THD) at the point of common coupling (PCC), degrading the performance of connected loads and reducing the efficiency of induction motors. The PIR controller integrates both proportional-integral (PI) and proportional-resonant (PR) control features, achieving improved stability and reduced overshoot. A novel voltage sensorless control method is proposed, requiring only current measurements to determine reference currents for the inverter, thereby simplifying the implementation. Validation of the frequency adaptive control scheme through MATLAB/Simulink simulations and real-time experiments on a dSPACE (DS1202) platform demonstrates significant improvements in harmonic compensation, energy efficiency, and system stability across varying grid frequencies. This approach offers a robust consumer-oriented solution for managing power quality, positioning the SAPF as a key technology for advancing sustainable energy management in smart applications. [ABSTRACT FROM AUTHOR]

Purpose: Coupling membrane is used widely in the field of power transmission for misalignment reduction between the driving and the driven shafts. Knowledge of coupling dynamics is useful for improving the coupling membrane design. Traditional intrusive frequency measurement may lead to a disturbance in the coupling operation, which could cause its mechanical failure. Methods: Here we attempt to use high-speed imaging methods in the frequency study. An industrial six-bolt coupling membrane stack has been studying on John Crane Test Rig. Of the total of 14 study cases, Cases 1 to 4 are steady torque conditions, and the rest cases are cyclic torque conditions. Imaging-based measurement proposed here has successfully detected dynamic attributes of the coupling membrane in terms of rotation frequency (fr), cyclic frequency (fc) and vibration frequency (fv). Results: At 3036 Nm the coupling membrane stack was designed to bow for preventing its mechanical failure or the shaft bending. This bowing phenomenon has been observed successfully, and it is notable that the bowing areas have strong correlations with the bowing position and the frequency (fv) is found not to vary with the steady torque accordingly, even the torque increased significantly. The results show that taking advantage of the optical intensity variation reflected by the membrane stack is found to be effective in conjunction with imaging-based measurement for frequency detection. Conclusions: Imaging-based frequency measurement has been performed on a six-bolt coupling membrane stack, experimenting on Jhon Crane Test Rig. This simulates variable torque and vibration exerting on the couplings to validate the effectiveness of the proposed frequency measurement. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a digital low computation detection method for signal nonlinear distortion. After presetting ADC sampling rate and completing data sampling, the low sampling rate data extracted from the sampling data complete the autocorrelation analysis to correct and calculate the accurate fundamental frequency. According to the relationship between the fundamental frequency and the sampling rate, the complete periodic segment data of the signal cutting out from the sampling data carry out the digital quadrature detection operation to obtain the value of each harmonic component and nonlinear distortion. Experiments show that the calculation of this method is less than that of FFT spectrum analysis method when measuring the THD lower than 15 order. When calculating the 15-order THD at 1024 points, the calculation time is reduced by 44.26%. Moreover, the digital quadrature detection method has high measurement accuracy with less than 0.6% error of detecting 5-order THD.

The low‐frequency image brightness of the VRR mode display will decrease due to an increase in leakage time, causing the display to flicker when switching between different frequencies, seriously affecting user usage. By utilizing VDF technology (VRR De‐Flicker), on the one hand, digital voltage compensation is applied to low‐frequency images to maintain consistent brightness at different frequencies, and on the other hand, the Vcom voltage is dynamically adjusted to suppress pixel leakage. Ultimately, the goal of improving flicker is achieved. [ABSTRACT FROM AUTHOR]

Under the impetus of wireless communications, metamaterials have attracted considerable attention due to their superior merits of free manipulation of electromagnetic waves and easy integration. However, most efforts to date are mainly focused on the modulation of wave information or recognition of wave intensity, while the frequency detection is rarely explored. Here, a spoof localized surface plasmon (SLSP) structure is proposed to realize reconfigurable frequency detections. By switching the bias voltage applied to the varactor, the resonance frequency of SLSP can be controlled dynamically from 1.95 to 2.35 GHz. The SLSP‐based waveguide has a relatively high quality factor due to the strongly localized field confinement. Reconfigurable frequency detection is demonstrated experimentally by monitoring the output voltage of the introduced detector. The measured and simulated results are in good agreement. This work will hold promising applications in wireless communication and sensing systems. [ABSTRACT FROM AUTHOR]

In the process of dynamic Measurement While Drilling (MWD), the strong vibration and rapid rotation of the Bottom Hole Assembly (BHA) lead to multi-frequency and high-amplitude noise interference in the attitude measurement signal. The weak original signal and extremely low signal-to-noise ratio (SNR) are always the technical difficulties of dynamic MWD. To solve this problem, this paper uses the chaotic effect of the Duffing system, which takes the expression (−x3 + x5) as a nonlinear restoring force to detect the weak characteristic signal of downhole dynamic MWD. First of all, in order to meet the limit condition of the chaotic phase transition of the system output, the frequency value of the characteristic signal is reconstructed and transformed based on the variable scale theory. Then, in order to solve the influence of the initial phase of the characteristic signal on the detection accuracy, a detection model based on the array Duffing system is presented, and a frequency-detection scheme with all-phase coverage is given. Finally, another array Duffing system is designed for the parameter estimation of the characteristic signal. The critical value of chaotic phase transition is determined by adjusting the amplitude of the driving signal of the array Duffing system, and then the amplitude and phase parameters of the characteristic signal are synchronously estimated. The experimental results show that the proposed method can effectively extract the weak characteristic signal within the strong noise, and the SNR of the characteristic signal can be as low as −21 dB. Through the attitude calculation for the extracted characteristic signal, it can be seen that the proposed method can improve the accuracy of the inclination of the drilling tool significantly, which proves the feasibility and effectiveness of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper presents a digital low computation detection method for signal nonlinear distortion. After presetting ADC sampling rate and completing data sampling, the low sampling rate data extracted from the sampling data complete the autocorrelation analysis to correct and calculate the accurate fundamental frequency. According to the relationship between the fundamental frequency and the sampling rate, the complete periodic segment data of the signal cutting out from the sampling data carry out the digital quadrature detection operation to obtain the value of each harmonic component and nonlinear distortion. Experiments show that the calculation of this method is less than that of FFT spectrum analysis method when measuring the THD lower than 15 order. When calculating the 15-order THD at 1024 points, the calculation time is reduced by 44.26%. Moreover, the digital quadrature detection method has high measurement accuracy with less than 0.6% error of detecting 5-order THD. [ABSTRACT FROM AUTHOR]

Time–frequency analysis plays a crucial role in various fields, including signal processing and feature extraction. In this article, we propose an alternative and innovative method for time–frequency analysis using a biologically inspired spiking neural network (SNN), encompassing both a specific spike-continuous-time-neuron-based neural architecture and an adaptive learning rule. We aim to efficiently detect frequencies embedded in a given signal for the purpose of feature extraction. To achieve this, we suggest using an SN-based network functioning as a resonator for the detection of specific frequencies. We developed a modified supervised spike timing-dependent plasticity learning rule to effectively adjust the network parameters. Unlike traditional methods for time–frequency analysis, our approach obviates the need to segment the signal into several frames, resulting in a streamlined and more effective frequency analysis process. Simulation results demonstrate the efficiency of the proposed method, showcasing its ability to detect frequencies and generate a Spikegram akin to the fast Fourier transform (FFT) based spectrogram. The proposed approach is applied to analyzing EEG signals, demonstrating an accurate correlation to the equivalent FFT transform. Results show a success rate of 94.3% in classifying EEG signals.

In the context of carbon peak and carbon neutrality targets, high-proportion new energy power systems exhibit low inertia and weak damping characteristics. The frequency stability of the new power system has become a major problem for the safe and stable operation of the power grid. The traditional primary frequency modulation technology based on thermal power units or hydropower units has the defects of slow response speed and long frequency detection delay time. Therefore, we propose a multi-functional multiplexing super capacitor fast power control system, which has the functions of frequency stability control and voltage sag management. In the meantime, we proposed a fast frequency detection algorithm for cascaded signal delay, and the frequency detection delay is less than 10 ms. The system uses a high-speed communication ring network, and the communication delay is less than two milliseconds. Finally, we built a super capacitor energy storage system with a capacity of 50kW to verify that the super-capacitor has the ability to quickly and actively support the power system under frequency disturbances.

Estimating the frequencies of multiple superimposed exponentials in noise is an important problem due to its various applications in engineering. In order to obtain good inhibition of spectral leakage and improve the estimation accuracy, an improved Chirp-Z transform (CZT) algorithm is proposed for high-precision frequency estimation. Firstly, the proposed algorithm analyzes the characteristics of the CZT spectrum and utilizes the CZT spectrum to construct a bias correction factor for frequency bias estimation. Then, an expression between the bias correction factor and the frequency estimation error is derived to obtain a more accurate estimate of the frequency bias. Finally, the frequency estimate of the CZT is corrected by the estimated frequency bias so as to obtain a higher frequency estimation accuracy. Compared with the conventional CZT algorithm, the proposed improved CZT algorithm achieves a higher frequency estimation accuracy by correcting the frequency estimate of the CZT method using the estimated frequency bias. The proposed improved CZT algorithm is verified using simulation studies and experimental results, and the results show that it has a higher accuracy and better robustness than the existing methods. [ABSTRACT FROM AUTHOR]

This article proposes a novel humidity sensor using a microwave resonant cavity as the sensing device. This sensor comprises a high-quality factor resonant cavity and frequency detection circuits. The working frequency of the resonator is 9.6 GHz, it has the characteristics that the resonance frequency can be adjusted, and it is designed with embedded air guide holes to allow moist air to enter the interior of the resonant cavity. According to the perturbation theory, when humid air is distributed in the resonator’s sensing area, the resonator’s resonant frequency changes according to different relative humidity (RH) levels. Then, the frequency detection circuit is used to detect the resonance frequency change, and the RH level related to the shift in the resonance frequency can be obtained. In order to get more accurate measurement results, a temperature and atmospheric pressure compensation algorithm is introduced to correct the measurement results. Experiments show that the proposed humidity sensor effectively detects humidity in an RH environment of 20%-95%. It has the characteristics of fast detection speed and high stability, which avoids the need to use the conventional detection method of the vector network analyzer. [ABSTRACT FROM AUTHOR]

Accurate estimation of the frequency component is an important issue to identify and track marine objects (e.g., surface ship, submarine, etc.). In general, a passive sonar system consists of a sensor array, and each sensor receives data that have common information of the target signal. In this paper, we consider multiple-measurement sparse Bayesian learning (MM-SBL), which reconstructs sparse solutions in a linear system using Bayesian frameworks, to detect the common frequency components received by each sensor. In addition, the direction of arrival estimation was performed on each detected common frequency component using the MM-SBL based on beamforming. The azimuth for each common frequency component was confirmed in the frequency-azimuth plot, through which we identified the target. In addition, we perform target tracking using the target detection results along time, which are derived from the sum of the signal spectrum at the azimuth angle. The performance of the MM-SBL and the conventional target detection method based on energy detection were compared using in-situ data measured near the Korean peninsula, where MM-SBL displays superior detection performance and high-resolution results. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Electrical discharge machining (EDM) mainly uses the spark discharge generated between the workpiece and the tool electrode for material erosion; however, abnormal discharge status such as arcing and short circuit often occurs in the process of EDM, and normal discharge will also change into abnormal under certain conditions, which increases the difficulty of discharge state detection. To improve the detection accuracy of discharge states, the amplitude frequency characteristics of discharge voltage signal were studied and a discharge state detection system based on frequency detection was developed. The results showed that the amplitude of voltage signal of spark in the high-frequency range (> 30 MHz) is greater than that of the arcing. Spark and arcing can be effectively distinguished by detecting the amplitude of high-frequency component of the voltage signal. Combined with high-frequency component amplitude detection, voltage detection, and current detection, a discharge state detection system is developed, which can accurately distinguish open circuit, spark, arcing, and short circuit. The discharge state coefficients are calculated and used as the feedback signals of the adaptive control system for micro-EDM drilling process. Compared with the general control based on the average voltage method, using adaptive control can increase the average machining efficiency by 22.4%, reduce the average burned area of the inner surface of micro-holes by 38.2%, and reduce the number and size of micro-cracks in the recast layer. [ABSTRACT FROM AUTHOR]

Despite the considerable improvement of the common-mode rejection ratio of digital filtering techniques, the electrocardiogram (ECG) traces recorded by commercialized devices are still contaminated by residual power line interference (PLI). In this study, we address this issue by proposing a novel real-time filter adapted to single-frequency noise cancellation and automatic power line frequency detection. The filtering process is principally based on a point-by-point fast Fourier transform and a judicious choice of the analysis window length. Intensive experiments conducted on real and synthetic signals have shown that our filtering method offers very clean ECGs, due to the suppression of spikes corresponding to the PLI and the preservation of spikes outside the filter band. In addition, this method is characterized by its low computational complexity which makes it suitable for real-time cleaning of ECG signals and thus can serve for more accurate diagnosis in computer-based automated cardiac system.

Asymmetrical working conditions of the utility grid introduce the large-amplitude negative-sequence component to the output current of the voltage source converter (VSC), causing power semiconductor devices to suffer from thermal fatigue and thermal damage. Though the conventional phase-locked loop (PLL) based voltage oriented control (VOC) solution can suppress the steady-state negative-sequence current effectively, it has a weak suppression ability of transient overload current, and even aggravates the transient current asymmetry and causes more severe transient impact to the VSC. This paper first analyzes the transient performance of the conventional VOC strategy, especially its dynamic response time and the main factors for performance limitation. On this basis, the PLL-free VOC strategy for VSCs tied to unbalanced grids is proposed, and its critical parts, namely, the reference current calculation and the fast detection of the grid voltage sequence components, are implemented. Besides, to improve the frequency adaptability, a high-performance grid frequency detection strategy is developed based on the difference-frequency phase caused by the frequency variation. Finally, experiments are performed to verify the effectiveness and advancement of the proposed method. Specifically, the results proved the rapidity, accuracy, and frequency adaptability of the proposed method in suppressing the VSC negative-sequence current, both in transient and steady-state conditions.

Estimating the frequencies of multiple superimposed exponentials in noise is an important problem due to its various applications in engineering. In order to obtain good inhibition of spectral leakage and improve the estimation accuracy, an improved Chirp-Z transform (CZT) algorithm is proposed for high-precision frequency estimation. Firstly, the proposed algorithm analyzes the characteristics of the CZT spectrum and utilizes the CZT spectrum to construct a bias correction factor for frequency bias estimation. Then, an expression between the bias correction factor and the frequency estimation error is derived to obtain a more accurate estimate of the frequency bias. Finally, the frequency estimate of the CZT is corrected by the estimated frequency bias so as to obtain a higher frequency estimation accuracy. Compared with the conventional CZT algorithm, the proposed improved CZT algorithm achieves a higher frequency estimation accuracy by correcting the frequency estimate of the CZT method using the estimated frequency bias. The proposed improved CZT algorithm is verified using simulation studies and experimental results, and the results show that it has a higher accuracy and better robustness than the existing methods.

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a potential technology in weak signal detection (WSD), the chaos theory benefits from its characteristics of the sensitivity to the initial condition and the immunity to the Additive White Gaussian Noise (AWGN). Traditional methods based on chaos theory perform well on single non-variable-frequency signal detection (SNVFSD), which is a common situation in texture flaw detection while it is a rare scenario in the communication field. In this paper, we give a comprehensive analysis of the chaos-based approach for weak signal frequency detection. To better understand the advantages and limitations of the chaos theory, we present the research results for several typical communication scenarios. Specifically, we proposed several chaos-based approaches to get a satisfying performance in the following situations: single variable-frequency signal detection (SVFSD), multiple non-variable-frequency signals detection (MNVFSD), multiple variable-frequency signals detection (MVFSD). To enhance the generalization performance to real application, the critical state's characteristics, Lyapunov Exponents (LE) and Melnikov method are analyzed to employed in these proposed chaos-based approaches. By theoretical analysis and numerical simulations, we study the performance of chaos-based detection systems in terms of SVFSD, MNVFSD, MVFSD. Our results show that these proposed schemes can obtain a satisfying performance in terms of accuracy and robustness, and the extensive simulations demonstrate their effectiveness. [ABSTRACT FROM AUTHOR]

At present, three-phase 115V/360-800Hz variable frequency AC power system is mostly used in the main power system of More-Electric Aircraft. With the increase of EMA (Electro-Mechanical Actuator), EHA (Electro-Hydrostatic Actuator), DC/DC power supply and power electronic devices in More-Electric Aircraft, harmonic and reactive power problems are brought, which seriously affect the power supply quality of variable frequency power supply for aircraft. According to the characteristics of high frequency and wide range of aviation variable frequency power supply, this paper studies a three-level active filter which can effectively improve the power quality of aviation variable frequency power supply system. This paper analyzes the working principle of the diode clamped three-level topology active filter, and deduces its mathematical model; proposes the frequency detection of the aviation variable frequency power supply based on the improved Rife method; the ip-iq method based on the instantaneous reactive power theory, accurately detects the harmonic current of the aviation variable frequency power supply system; uses the quasi PR controller to track the current, and improves the harmonic suppression effect. Finally, the experimental hardware platform is built to verify the feasibility of the proposed control strategy.

The frequency detection of current and voltage plays a very important role in the grid-connected control strategy. Large detection errors can cause failure of control algorithms such as phase lock, harmonic compensation and reactive power compensation. Based on this, taking the harmonic separation as an example, the variation of amplitude attenuation with frequency detection error is derived under the condition of multi-channel, second-order generalized integrator(SOGI), parallel operation. The effects of frequency detection error on the separation of harmonics are introduced in detail. To reduce the frequency error, a medium and low frequency high precision current signal frequency detecting device is designed, which is divided into two parts: hardware circuit and software design. The hardware includes controller peripheral circuit, sampling circuit, sensor circuit, voltage follower circuit, voltage bias circuit and so on. The software part mainly includes sampling program, frequency detection program and error correction program. Finally, the simulation results verified the correctness of the theoretical analysis of the frequency detection error. The experimental results of current frequency detection verified the feasibility of the design and the high precision of the device.

The propagation of nonlinear loads and distributed power generation systems can cause power quality problems such as harmonic distortion, system imbalance, and resonance problems. Shunt active power filters are used to eliminate these power quality problems. A recently proposed control scheme for a shunt active power filter utilized a time-domain transformation to extract positive and negative sequence components of the system voltages and currents. These components are used in a modified version of instantaneous reactive power theory to calculate the reference currents for a three-phase inverter. Changes in the system operating conditions can cause the system frequency to vary, which can impact the performance of the time-domain transformation. Proposed in this paper is a frequency adaptive control scheme to compensate for frequency variations. Several simulation and experimental tests have been performed to validate the operation of the proposed frequency adaptive control scheme. [ABSTRACT FROM AUTHOR]

Despite the considerable improvement of the common-mode rejection ratio of digital filtering techniques, the electrocardiogram (ECG) traces recorded by commercialized devices are still contaminated by residual power line interference (PLI). In this study, we address this issue by proposing a novel real-time filter adapted to single-frequency noise cancellation and automatic power line frequency detection. The filtering process is principally based on a point-by-point fast Fourier transform and a judicious choice of the analysis window length. Intensive experiments conducted on real and synthetic signals have shown that our filtering method offers very clean ECGs, due to the suppression of spikes corresponding to the PLI and the preservation of spikes outside the filter band. In addition, this method is characterized by its low computational complexity which makes it suitable for real-time cleaning of ECG signals and thus can serve for more accurate diagnosis in computer-based automated cardiac system. [ABSTRACT FROM AUTHOR]

When a voltage source converter (VSC) connects to a parallel compensated grid, high‐frequency resonance (HFR) is a subsistent issue that exists in the interconnected system. HFR will introduce a significantly high‐frequency voltage component at the point of common coupling, thereby the performance of the VSC system can be deteriorated seriously. For improving the operation of the VSC system under the parallel compensated grid, this study proposes an HFR damping strategy based on a voltage feedforward control to reshape the impedance of grid connected VSC. The VSC system with the proposed control strategy can damp HFR in a wide high‐frequency range without employing the frequency detection and introducing the differential elements so that the negative influence caused by the high‐frequency noise can be avoided. Theoretical analysis and experimental results are given to verify the effectiveness and availability of the proposed damping control strategy. [ABSTRACT FROM AUTHOR]

In this paper, a self-tunable energy harvester based on pendulum oscillations with a mechanical motion rectifier (MMR) system, which can convert vibration into electrical energy, is proposed. The harvester is composed of a pendulum excited by a slider-crank mechanism. The pendulum system is designed to automatically adjust its own natural frequency to match that of the imposed base excitation. Frequency adjustment in a proposed pendulum-type energy harvester is achieved by varying the length of the pendulum rod through changing the position of pendulum mass which mounted at its tip. The pendulum mass is driven by a ball screw through a stepper motor which controls the length of the pendulum automatically in accordance with the frequency of the external motion. The base motion frequency is detected by an infrared sensor. An ultrasonic distance sensor is used to detect the length of the pendulum rod and feeds this information to a microcontroller to obtain the corresponding natural frequency from a lookup table. The microcontroller calculates the frequency difference between natural frequency and excitation frequency and converts this value into a length difference through another lookup table. The microcontroller then gives instructions to drive a stepper motor through a sequence of steps to achieve the target length and keeps the device in resonance state to harvest maximum power during operation. Different time detection intervals were studied to investigate their effect on the tuning process. This study showed that the longer time intervals increase the detection accuracy for the calculation of low excitation frequency. The amount of energy consumed during the tuning process to adjust the pendulum length is presented. In this context, the consumed energy is only needed until the resonance of the device matches the excitation frequency. The harvester system was studied numerically and experimentally. Based on the findings of this work, the natural frequency of the harvester is successfully tuned below 0.7 Hz, when the length of pendulum rod is changed from 550 mm to 900 mm, generating power from 1.78 W to 4.1 W at an optimal load resistance value of 10 Ω and 3 Ω respectively at maximum excitation amplitude of 120 mm. Therefore, the proposed pendulum system can be used as an efficient harvester for producing power in low-frequency applications (< 1 Hz). [ABSTRACT FROM AUTHOR]

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To improve the accuracy of phase retardation measurement, a wave plate measurement method was proposed based on magneto-optical modulating and base frequency signal detecting. Firstly, a magneto-optical modulator was placed at a suitable location of the optical path to be adjusted and to make only even harmonic components be left in the measurement signal. And then, detecting the residue of the base frequency component instead of whole spectrum signal, the phase retardation measurement of wave plate was carried out accurately. Finally, the theoretical formulae and corresponding wave plate measuring system were established based on Jones matrix. The analysis results show that, when the ambient temperature changes 0.1°, the measurement uncertainty of the system can be less than 5'. Half-wave plates (HWP) and quarter-wave plates? (QWP) measurement results show that, the measurement standard deviation is about 2'. [ABSTRACT FROM AUTHOR]

The load sharing in the DC microgrids is affected by the practical factors such as the cable resistances and changes in the system topology. This paper presents a new control algorithm for the application in the DC microgrids to achieve accurate load distribution between droop controlled converters. An identical steady state voltage feedback is used for all droop controlled converters to ensure accurate current sharing. The information about the common voltage is obtained by means of the proposed communication-less control strategy. The proposed strategy does not require prior information about the grid topology and parameters. Therefore, it is applicable to both single- and multi-bus microgrids. The conducted stability analysis demonstrates that the proposed approach and the conventional droop control deomstrate similiar dynamic performance. Furthermore, the proposed algorithm has a potential to enhance the operation of the Interlinking Converters in the hybrid AC/DC microgrids. A comprehensive nonlinear simulation study is conducted in the Matlab/Simulink environment. The simulation results verify the effectiveness of the proposed communication-less control scheme to enable proper load distribution between droop controlled converters as well as enhance the load sharing between AC and DC microgrids. Finally, the proposed control approach is verified using an OPAL-RT setup. [ABSTRACT FROM AUTHOR]

Transmission surface acoustic wave (SAW) sensors are widely used in various fields of application. In order to improve the limit of detection (LOD) of such sensor systems, it is essential to understand and quantify the relevant noise sources. Only then, strategies for noise reduction can be developed. In this paper, low noise readout systems for the application with SAW sensors in open-loop and closed-loop configurations are presented and experimentally investigated with regard to their phase noise on the example of a SAW delay line magnetic field sensor. Besides a comprehensive analysis of the phase- and frequency modulated signals, respectively, previously derived equations in a theoretic study for describing the LOD of both readout structures are utilized in the experimental context. According to the theory, the same LOD is also obtained in the experiment for all frequencies for which the noise contributions of the readout electronics are negligible. To the best of our knowledge, this is the first experimental study that directly compares both operating modes for the same sensor and in terms of the overall achievable LOD. The results are applicable to all kinds of phase-sensitive delay-line sensors. [ABSTRACT FROM AUTHOR]

The localization of active brain sources from Electroencephalogram (EEG) is a useful method in clinical applications, such as the study of localized epilepsy, evoked-related-potentials, and attention deficit/hyperactivity disorder. The distributed-source model is a common method to estimate neural activity in the brain. The location and amplitude of each active source are estimated by solving the inverse problem by regularization or using Bayesian methods with spatio-temporal constraints. Frequency and spatio-temporal constraints improve the quality of the reconstructed neural activity. However, separation into frequency bands is beneficial when the relevant information is in specific sub-bands. We improved frequency-band identification and preserved good temporal resolution using EEG pre-processing techniques with good frequency band separation and temporal resolution properties. The identified frequency bands were included as constraints in the solution of the inverse problem by decomposing the EEG signals into frequency bands through various methods that offer good frequency and temporal resolution, such as empirical mode decomposition (EMD) and wavelet transform (WT). We present a comparative analysis of the accuracy of brain-source reconstruction using these techniques. The accuracy of the spatial reconstruction was assessed using the Wasserstein metric for real and simulated signals. We approached the mode-mixing problem, inherent to EMD, by exploring three variants of EMD: masking EMD, Ensemble-EMD (EEMD), and multivariate EMD (MEMD). The results of the spatio-temporal brain source reconstruction using these techniques show that masking EMD and MEMD can largely mitigate the mode-mixing problem and achieve a good spatio-temporal reconstruction of the active sources. Masking EMD and EEMD achieved better reconstruction than standard EMD, Multiple Sparse Priors, or wavelet packet decomposition when EMD was used as a pre-processing tool for the spatial reconstruction (averaged over time) of the brain sources. The spatial resolution obtained using all three EMD variants was substantially better than the use of EMD alone, as the mode-mixing problem was mitigated, particularly with masking EMD and EEMD. These findings encourage further exploration into the use of EMD-based pre-processing, the mode-mixing problem, and its impact on the accuracy of brain source activity reconstruction.

Generally, the more channels are used to acquire EEG signals, the better the performance of the brain-computer interface (BCI). However, from the user's point of view, a BCI system comprising a large number of channels is not desirable because of the lower comfort and extended application time. Therefore, the current trend in BCI design is to use the smallest number of channels possible. The problem is, however, that usually when we decrease the number of channels, the interface accuracy also drops significantly. In the paper, we examined whether it is possible to maintain the high accuracy of a BCI based on steady-state visual evoked potentials (SSVEP-BCI) in a low-channel setup using a preprocessing procedure successfully used in a multichannel setting: independent component analysis (ICA). The influence of ICA on the BCI performance was measured in an off-line (24 subjects) mode and online (eight subjects) mode. In the off-line mode, we compared the number of correctly recognized different stimulation frequencies, and in the online mode, we compared the classification accuracy. In both experiments, we noted the predominance of signals that underwent ICA preprocessing. In the off-line mode, we detected 50% more stimulation frequencies after ICA preprocessing than before (in the case of four EEG channels), and in the online mode, we noted a classification accuracy increase of 8%. The most important results, however, were the results obtained for a very low luminance (350 lx), where we noted 71% gain in the off-line mode and 11% gain in the online mode. [ABSTRACT FROM AUTHOR]

The localization of active brain sources from Electroencephalogram (EEG) is a useful method in clinical applications, such as the study of localized epilepsy, evoked-related-potentials, and attention deficit/hyperactivity disorder. The distributed-source model is a common method to estimate neural activity in the brain. The location and amplitude of each active source are estimated by solving the inverse problem by regularization or using Bayesian methods with spatio-temporal constraints. Frequency and spatio-temporal constraints improve the quality of the reconstructed neural activity. However, separation into frequency bands is beneficial when the relevant information is in specific sub-bands. We improved frequency-band identification and preserved good temporal resolution using EEG pre-processing techniques with good frequency band separation and temporal resolution properties. The identified frequency bands were included as constraints in the solution of the inverse problem by decomposing the EEG signals into frequency bands through various methods that offer good frequency and temporal resolution, such as empirical mode decomposition (EMD) and wavelet transform (WT). We present a comparative analysis of the accuracy of brain-source reconstruction using these techniques. The accuracy of the spatial reconstruction was assessed using the Wasserstein metric for real and simulated signals. We approached the mode-mixing problem, inherent to EMD, by exploring three variants of EMD: masking EMD, Ensemble-EMD (EEMD), and multivariate EMD (MEMD). The results of the spatio-temporal brain source reconstruction using these techniques show that masking EMD and MEMD can largely mitigate the mode-mixing problem and achieve a good spatio-temporal reconstruction of the active sources. Masking EMD and EEMD achieved better reconstruction than standard EMD, Multiple Sparse Priors, or wavelet packet decomposition when EMD was used as a pre-processing tool for the spatial reconstruction (averaged over time) of the brain sources. The spatial resolution obtained using all three EMD variants was substantially better than the use of EMD alone, as the mode-mixing problem was mitigated, particularly with masking EMD and EEMD. These findings encourage further exploration into the use of EMD-based pre-processing, the mode-mixing problem, and its impact on the accuracy of brain source activity reconstruction. [ABSTRACT FROM AUTHOR]

From the control point of view, synchronization techniques are divided into two major categories: open-loop and closed-loop methods. Roughly speaking, open-loop synchronization (OLS) approaches are not as popular as closed-loop ones, probably because they suffer from a poor performance in the presence of frequency drifts. This is particularly true in single-phase applications, where the lack of multiple independent input signals makes the implementation of the synchronization technique difficult. The aim of this letter is to develop an effective OLS technique for single-phase power and energy applications. The proposed OLS method benefits from a straightforward implementation, a fast dynamic response (a response time less than two cycles of the nominal frequency), and a complete immunity against the dc component in the grid voltage. In addition, the designed OLS method totally blocks (significantly attenuates) all harmonics up to the aliasing point under a nominal (off-nominal) frequency. The effectiveness of the designed OLS technique is verified using comparative experimental results. [ABSTRACT FROM PUBLISHER]

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• Propose an error-and-hold algorithm for the SOGI-FLL that can quickly detect faults and give a response that consists in holding the previous to the fault estimated frequency value during these perturbations. • Develop the algorithm using the absolute value of the SOGI's error, its average, and the average of the FLL's estimated frequency to operate, to reduce induced errors in the SOGI-FLL's quadrature outputs, improves the FLL's transient response, hold the estimated frequency, and restores the phase to its previous value before the fault. • Using the LTP model of the SOGI-FLL, to demonstrate how voltage sags and swells affect the amplitude voltage and frequency via an asymmetrical-gain mutual interaction between the SOGI-FLL estimates and a sinusoidal gain that relies on the grid voltage phase. • Demonstrate the practicality of the proposed algorithm, using MATLAB/Simulink software simulations and experimental results, illustrating how it can enhance the SOGI-FLL's response to these disturbances. The Second Order Generalized Integrator–Frequency Locked Loop (SOGI-FLL) is a widely used and popular adaptive filter for estimating grid voltage parameters with minimal computational burden. However, it is vulnerable to voltage sag and swell faults, especially voltage sags that can significantly distort the estimated frequency. In this paper, we propose an error-and-hold algorithm for the SOGI-FLL that can quickly detect faults and hold the estimated frequency during these perturbations. The algorithm uses the absolute value of the SOGI's error, its average, and the average of the FLL's estimated frequency to operate. It reduces induced errors in the SOGI-FLL's quadrature outputs, improves the FLL's transient response, holds the estimated frequency, and restores the phase to its previous value before the fault. The proposed algorithm is a straightforward and low computational burden algorithm that can be executed on a low-cost processor. We validate the effectiveness of the proposed error-and-hold algorithm through simulations and experimental results. [ABSTRACT FROM AUTHOR]

Lead-free materials with superior piezoelectric properties are gaining much interest due to their high performance and increased long-term sustainability. In this context, bismuth-based ternary oxides exhibit perovskite crystal structures with high piezoelectric coefficients and mechanical damping. Thus, in this work, we report a Bi 2 CuO 4 : Polydimethylsiloxane (BCO: PDMS) composite -based photoinduced-piezoelectric nanogenerator for harvesting weak mechanical vibrations which are abundant in the atmosphere. Notably, the BCO nanoparticles exhibit a highly crystalline tetragonal structure with 2D-nanoflake-like morphology providing a high surface area for the PENG applications. Further, the optical studies of BCO illustrate an enhanced absorption in the visible region with a bandgap of 2.5 eV. BCO: PDMS-based PENG displays a maximum open circuit voltage of 50 V and short circuit current of 300 nA upon application of 0.15 kgf vertical compressive force without any electrical poling. The PENG device exhibits an 18 % increment in output voltage upon illumination of visible light of 5 mW/cm2 intensity with superior photodetection properties. The obtained response can be attributed to the synergistic effect, i.e., the generation of exciton pairs upon illumination and separation of charge carriers due to the inbuilt piezoelectric field. Moreover, the PENG exhibits a distinct and accurate response for feeble and subtle frequencies in the range of 3–22 Hz such as atmospheric noise, and gravity hum noise. thus, proving the superior sensitivity. The fabricated PENG device displayed a stable response for 30 min of continuous vibration displaying superior cyclic stability. This work demonstrates a combination of perovskite crystalline material and PDMS leading to the development of high-performance piezoelectric nanogenerators with future scope in frequency detection systems for security and safety applications. [Display omitted] • Bi 2 CuO 4 : Polydimethylsiloxane (BCO: PDMS) composite-based PENG was fabricated via a simple spin coating technique. • The PENG was used for harvesting weak mechanical vibrations and photodetector applications. • The PENG device exhibits an 18 % increment in output voltage upon illumination of visible light of 5 mW/cm2. • PENG exhibits a distinct and accurate response for feeble and subtle frequencies in the range of 3–22 Hz such as atmospheric noise, and gravity hum noise. [ABSTRACT FROM AUTHOR]

This paper presents a method for online detection of symmetrical components of arbitrarily distorted and biased three-phase input signals. This method is based on Second-Order Generalized Integrators (SOGIs), for which a new tuning based on a gradient search is presented to achieve the fastest possible estimation. Frequency estimation is achieved by a Frequency Locked Loop (FLL) with Gain Normalization (GN) for which an Output Saturation (OS) is applied; this OS guarantees stability of the overall system. Offset detection is implemented by a combination of High-Pass Filter (HPF) and HPF-Amplitude Phase Correction (APC HPF ); the HPF filters out any offset, where the APC reconstructs the original offset-free signal. An identical method (APC LPF ) can be used for the implemented Low-Pass Filter (LPF) used for noise filtering. The resulting estimates are then used for Harmonic Sequence Detection (HSD) of each harmonic. For the overall system, stability is proven. The estimation performances of the proposed overall system are verified by simulation results. The improvements in tuning and offset detection are compared to standard approaches.