Search

This paper presents a novel approach for detecting high-impedance faults (HIF) in distribution systems that uses the Hilbert transform. Our approach is based on determining the instantaneous frequency of signals and detecting deviations from a reference frequency. Our technique is very sensitive to fault fluctuations because it makes use of the Hilbert transform's ability to capture dynamic signal properties like phase and frequency alterations. This sensitivity enables the extraction of unique features that identify fault signals, providing critical insights into fault detection and location. Notably, our method is appropriate for the analysis of non-stationary signals, which are typical in power systems where signal attributes vary fast during fault conditions. Furthermore, our method resolves deviations by comparing them to a predefined range and displaying essential features such as basic frequency, RMS (Root Mean Square), Crest Factor, Minimum and Maximum Deviations, and Maximum Current Amplitude. These values offer unique insights into the present signal's qualities, which aids in defect detection and diagnostics, particularly in HIF settings. Our proposed technique detects high-impedance flaws by evaluating deviations from the nominal frequency, even in environments with weaker features and variable surface conditions. To improve our system's robustness and usefulness, we recommend performing additional study on adaptive thresholding algorithms and real-time implementation choices. Future research areas could involve investigating the integration of machine learning algorithms for automatic fault categorization and localization, which would enhance the capabilities of distribution system fault detection approaches. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for detecting high-impedance faults (HIF) in distribution systems that uses the Hilbert transform. Our approach is based on determining the instantaneous frequency of signals and detecting deviations from a reference frequency. Our technique is very sensitive to fault fluctuations because it makes use of the Hilbert transform’s ability to capture dynamic signal properties like phase and frequency alterations. This sensitivity enables the extraction of unique features that identify fault signals, providing critical insights into fault detection and location. Notably, our method is appropriate for the analysis of non-stationary signals, which are typical in power systems where signal attributes vary fast during fault conditions. Furthermore, our method resolves deviations by comparing them to a predefined range and displaying essential features such as basic frequency, RMS (Root Mean Square), Crest Factor, Minimum and Maximum Deviations, and Maximum Current Amplitude. These values offer unique insights into the present signal’s qualities, which aids in defect detection and diagnostics, particularly in HIF settings. Our proposed technique detects high-impedance flaws by evaluating deviations from the nominal frequency, even in environments with weaker features and variable surface conditions. To improve our system’s robustness and usefulness, we recommend performing additional study on adaptive thresholding algorithms and real-time implementation choices. Future research areas could involve investigating the integration of machine learning algorithms for automatic fault categorization and localization, which would enhance the capabilities of distribution system fault detection approaches.

BackgroundLong-term exposure to whole-body vibration (WBV) will affect the health of occupational drivers. However, research on the characteristics of WBV exposure by urban bus drivers and health risk evaluation is still insufficient. ObjectiveTo identify the characteristics of occupational WBV exposure of bus drivers serving 31 bus routes provided by three branches of Haikou Public Transport Group, and to evaluate their occupational health risks related to WBV. MethodsA total of 31 out of 142 bus routes run by three branches of Haikou Public Transport Group were selected to monitor WBV exposure of 31 bus drivers during driving. WBV parameters such as triaxial frequency weighted acceleration (awx, awy, awz) and triaxial crest factor (CFx, CFy, CFz) of the drivers were determined with a six-channel human vibration meter. Two methods, 8-hour daily value of the weighted root mean square average weighted vibration [A(8)] based on aw and 8-hour daily value of vibration dose [VDV(8)] based on vibration dose value (VDV), were used for health risk assessment and classified WBV health risk results into three levels (high, medium, and low) by the exposure action value (EAV) and exposure limit values (ELV) for A(8) and VDV(8) recommended by ISO 2631-1:1997. The two evaluation methods, A(8) and VDV(8), were compared by Fisher's exact test. ResultsRegarding the WBV parameters, the vector sum of acceleration (av) was 0.321-0.680 m·s−2, the VDV of monitoring interval was 3.824-10.174 m·s−1.75, and the VDV(8) was 6.039-13.505 m·s−1.75; their values in mean ± standard deviation were (0.480±0.100) m·s−2, (6.987±2.737) m·s−1.75, and (9.773±4.540) m·s−1.75, respectively. Positive correlations were found between awx and awz, av and awz, CFx and CFy, CFy and CFz. No bus route's WBV exposure level was graded as high health risk by either A(8) or VDV(8). The number of routes graded as low health risk by A(8) was 26, while the number by VDV(8) was 12. The consistency rates of health risk levels evaluated by the two methods were 66.7% (6/9), 54.6% (6/11), and 45.5% (5/11) for the three bus group branches, respectively. The difference in WBV health risk assessment results between the two evaluation methods was not statistically significant. ConclusionPositive correlations are found between triaxial acceleration and triaxial crest factor. There is no difference in the results of using A(8) and VDV(8) to evaluate health risks of WBV in urban bus routes.

Multisine signals are commonly used in the measurement of dynamic systems and wireless channels. For optimal measurements with a high dynamic range, a low Crest Factor (CF) excitation signal is required. In this paper, a modified approach to optimize the crest factor for complex-valued multisine signals is presented. The approach uses a nonlinear optimization method where the real and imaginary parts can also be optimized for low CF. Furthermore, extensions of the real-valued multisine CF optimization methods are presented for complex-valued cases. The proposed methods are validated and compared using simulations. Based on the results it is shown that the novel approach can lead to more optimal signal design and lower CF compared to other techniques for complex-valued multisine signals.

To gain a deeper understanding of the hotly contested topic of the non-thermal biological effects of microwaves, new metrics and methodologies need to be adopted. The direction proposed in the current work, which includes peak exposure analysis and not just time-averaged analysis, aligns well with this objective. The proposed methodology is not intended to facilitate a comparison of the general characteristics between 4G and 5G mobile communication signals. Instead, its purpose is to provide a means for analyzing specific real-life exposure conditions that may vary based on multiple parameters. A differentiation based on amplitude-time features of the 4G versus 5G signals is followed, with the aim of describing the peculiarities of a user's exposure when he runs four types of mobile applications on his mobile phone on either of the two mobile networks. To achieve the goals, we used signal and spectrum analyzers with adequate real-time analysis bandwidths and statistical descriptions provided by the amplitude probability density (APD) function, the complementary cumulative distribution function (CCDF), channel power measurements, and recorded spectrogram databases. We compared the exposimetric descriptors of emissions specific to file download, file upload, Internet video streaming, and video call usage in both 4G and 5G networks based on the specific modulation and coding schemes. The highest and lowest electric field strengths measured in the air at a 10 cm distance from the phone during emissions are indicated. The power distribution functions with the highest prevalence are highlighted and commented on. Afterwards, the capability of a convolutional neural network that belongs to the family of single-shot detectors is proven to recognize and classify the emissions with a very high degree of accuracy, enabling traceability of the dynamics of human exposure. [ABSTRACT FROM AUTHOR]

Vehicle comfort has become a buzzword in the automobile sector and continuous research is going on in this domain. Every automobile manufacturer would like to take the lead in vehicle comfort so as to attract more customers. Noise, vibration and harshness (NVH) testing is very important for improving the driving comfort of a vehicle. Driving comfort is directly related to the driving ability and health of the driver. Many international organisations have laid down guidelines for measuring driving comfort and categorise it in a range from comfortable to extremely uncomfortable. The present study adopts an experimental approach to determine the driving comfort in all-terrain vehicles (ATVs) by measuring frequency-weighted root-mean-square (RMS) accelerations at all the driver contact points in three mutually perpendicular directions as per the guidelines laid down in ISO 2631-1:1997 and ISO 5349-1:2001. The low-amplitude high-frequency engine vibrations are attenuated by performing transfer path analysis (TPA) of the vehicle roll cage before and after design modifications. The performance of the engine isolator mount is evaluated by carrying out transfer function analysis (TFA) of the active and passive engine mount vibrations. A novel hybrid approach comprising the TPA and TFA methods is used to attenuate the engine vibrations. The test result shows the effectiveness of the design modifications at the footrest, whereas there is moderate to low effectiveness at the steering and seat, respectively. [ABSTRACT FROM AUTHOR]

Vibration analysis has always been used for the diagnosis of gear faults. The vibration signals obtained are generally contaminated with noise and therefore not usable. The denoising of the vibration signals obtained helps in the diagnosis of faults, giving significant results. The wavelet transform increases the signal-to-noise ratio, reduces the mean absolute error, and is recommended for denoising gear vibration signals. The extracted signals must be denoised by choosing an appropriate denoising scheme to preserve the information contained in the signal. An approach has been developed in this work to show the effectiveness of this method. We chose a single-stage dynamic model with basically two shafts, one driving a load and the other a motor, to obtain this signal. Four bearings and two gears support both shafts. The meshing stiffness and the response have been calculated by an analytical method and a Newmark integration scheme, respectively. Then, we deliberately introduced a defect in the shape of a crack in a gear tooth. We selected Daubchies wavelets, which are well adapted to this type of problem. The objective is to control the different parameters related to our approach based on the wavelet transform, which is the levels of decomposition and the order of the wavelets. This approach consists of observing a series of indicators for a series of wavelet orders depending on the severity of the defect. The novelty of this research work is the improvement of scalar indicators while mastering the parameters linked to the wavelet transform. Our approach has been compared to other well-known methods in the literature. [ABSTRACT FROM AUTHOR]

Multisine signals are commonly used in the measurement of dynamic systems and wireless channels. For optimal measurements with a high dynamic range, a low Crest Factor (CF) excitation signal is required. In this paper, a modified approach to optimize the crest factor for complex-valued multisine signals is presented. The approach uses a nonlinear optimization method where the real and imaginary parts can also be optimized for low CF. Furthermore, extensions of the real-valued multisine CF optimization methods are presented for complex-valued cases. The proposed methods are validated and compared using simulations. Based on the results it is shown that the novel approach can lead to more optimal signal design and lower CF compared to other techniques for complex-valued multisine signals. [ABSTRACT FROM AUTHOR]

In this work we investigate the connection between two fundamental features of solutions of partial differential equations (PDEs), namely the crest factor and the length scale associated to each solution. We illustrate how the crest factor of solutions of some linear and non-linear PDEs, including the incompressible two-dimensional Navier-Stokes equations, has the capability for detecting turbulent and non-turbulent behaviour.

Magnetic particle inspection is a well-established industrial process of quality control. The ISO standard for magnetic particle inspection requires control of the crest factor and recommends avoiding current waveforms with a crest factor larger than three without documented evidence of detection effectiveness. Modern test bench units often use thyristor regulation of the magnetization current, which enables broad control ranges to generate an adequate magnetic field. A possible method of evaluation of magnetic field for magnetic particle inspection is to quantify the force effect on a detection particle. The cumulative force effect can be expressed as an impulse of force on a detection particle. The method of evaluation by an impulse of force implies that crest factor does not have a major effect if the impulse is controlled. This work contains a theoretical analysis of force in magnetic field generated by thyristor controlled currents. In the experimental part a comparison of indications generated by magnetic fields of different crest factorsis performed. The results of the experiment are in line with the theoretical analysis and show that it is the impulse that plays the major role in the formation of an indication and not crest factor. [ABSTRACT FROM AUTHOR]

The crest factor is an important indicator to measure the performance of the load. To reduce the crest factor of the system and improve the internal stability of the circuit, this article proposes a novel direct‐current piezoelectric energy harvester with sustainable output (S‐PEH). Voltage superposition with phase coupling could significantly improve the stability of the circuit system and reduce the interference and damage of transient pulses to the system. Here, the influence of angle size and phase number on the output performance of S‐PEH is studied. S‐PEH could produce a more stable voltage output with a low crest factor through phase coupling. At 3 P 120°, the optimum MAX voltage and root mean square (RMS) voltage are 29.06 and 16.55 V. The maximum RMS power is 1.38 mW. When the rotating speed is 550 r min−1, the lowest crest factor is 1.35. The charging rate is four times higher than a single‐group piezoelectric patch. Experiments show that S‐PEH can make light‐emitting diodes (LEDs) and calculators work stably. These results show that S‐PEH has great prospects in the power supply of wireless sensor networks and microelectronic devices. [ABSTRACT FROM AUTHOR]

To gain a deeper understanding of the hotly contested topic of the non-thermal biological effects of microwaves, new metrics and methodologies need to be adopted. The direction proposed in the current work, which includes peak exposure analysis and not just time-averaged analysis, aligns well with this objective. The proposed methodology is not intended to facilitate a comparison of the general characteristics between 4G and 5G mobile communication signals. Instead, its purpose is to provide a means for analyzing specific real-life exposure conditions that may vary based on multiple parameters. A differentiation based on amplitude-time features of the 4G versus 5G signals is followed, with the aim of describing the peculiarities of a user’s exposure when he runs four types of mobile applications on his mobile phone on either of the two mobile networks. To achieve the goals, we used signal and spectrum analyzers with adequate real-time analysis bandwidths and statistical descriptions provided by the amplitude probability density (APD) function, the complementary cumulative distribution function (CCDF), channel power measurements, and recorded spectrogram databases. We compared the exposimetric descriptors of emissions specific to file download, file upload, Internet video streaming, and video call usage in both 4G and 5G networks based on the specific modulation and coding schemes. The highest and lowest electric field strengths measured in the air at a 10 cm distance from the phone during emissions are indicated. The power distribution functions with the highest prevalence are highlighted and commented on. Afterwards, the capability of a convolutional neural network that belongs to the family of single-shot detectors is proven to recognize and classify the emissions with a very high degree of accuracy, enabling traceability of the dynamics of human exposure.

Noise-induced hearing loss (NIHL) is the largest cause of action for indemnity in North American industries despite the widespread implementation of hearing conservation programs. Possible causes behind the onset of NIHL are the intervals between hearing tests which are generally too long and the tests are insufficiently sensitive to detect temporary hearing changes to act and prevent permanent hearing damage. Moreover, current noise regulations might be too lenient as to the permissible maximum noise levels. Short-interval hearing assessment could help to observe temporary changes in hearing health and prevent permanent damage. This study investigates the short-term effects of noise exposure characteristics using repeated measurements of otoacoustic emission (OAE) growth functions and presents the most significant predictors of hearing health changes as observed in sixteen individuals equipped with OAE earpieces. The experimental results of this study show that the impulsiveness and frequency spectrum of the noise level could be a possible cause of the decline in OAE levels. As a consequence, hearing conservation programs should consider taking these noise metrics into account for proper NIHL risk assessment. Such noise exposure and hearing health monitoring could greatly improve hearing conservation practices in the workplace by acting faster and eventually mitigate occupational hearing loss. [ABSTRACT FROM AUTHOR]

Non-Gaussian random vibration tests have received increasing attention in the field of dynamic environmental testing. This paper presents a kurtosis and crest factor simultaneous control strategy for producing the preset stationary non-Gaussian random vibration environment. A novel generation method of non-Gaussian random vibration signal is proposed, which is composed of the shock and random signal components. The advantage of the method is that the kurtosis and crest factor of the signal can be controlled simultaneously and thus it can simulate more real non-Gaussian random vibrations. The first four statistical properties of the proposed non-Gaussian random signal are formulated. Subsequently, a closed-loop control procedure for the non-Gaussian random vibration test by kurtosis and crest factor control is elaborated. The monotonicity analyses of two crucial parameters on the kurtosis and crest factor control are discussed. Finally, a two-degree-of-freedom vibration simulation and a cantilever beam non-Gaussian vibration test are provided, and the results indicate the feasibility and validity of the presented control strategy. [ABSTRACT FROM AUTHOR]

This study aims to increase machine reliability thereby preventing product defects from adhesive dispense and slider attachment by a fault detection and diagnostic technique. The experiment was set up to investigate the vibration signal and motor current. Six fault conditions of a linear bearing were set up. The approaches, including spectrum analysis, crest factor, and analysis of variance, are used for data analysis. It was found that the spectrum analysis was suitable for classifying the frequency domains and the statistics tool was successful in measuring the current. Fault detection and diagnosis results can forecast the status of the linear bearings.

To reduce the crest factor in the DRM+ system due to the limitations imposed by the standard the peak limiting method (clipping) and the window weighting method, which are based on signal distortion, are widely used. As a result of the application of these methods out-of-band emissions in the signal spectrum significantly increase. After filtering out-of-band emissions the effect of a repeated increase in the crest factor appears. In this regard, there is an urgent scientific and technical problem of finding the optimal method for filtering out-of-band emissions of the DRM+ signal. The purpose of this article is to analyze the existing methods for filtering out-of-band emissions in the process of reducing the crest factor in a DRM system, as well as choosing the optimal filtering algorithm after reducing the crest factor for DRM+ transmitters. A method for suppressing out-of-band emissions using a digital filter based on FFT / IFFT is considered. The modeling of the proposed algorithm for filtering the signal by the mask of out-of-band emissions is carried out. Comparative studies of the method of the standard filtering algorithm and the proposed algorithm are carried out; the high efficiency of the latter is shown. The results obtained will improve the efficiency of reducing the crest factor in broadcasting transmitters of the DRM + standard, thereby increasing their power efficiency.

Triboelectric nanogenerator (TENG) has presented the huge potential application in distributed energy field which can realize the conversion from dispersed mechanical energy to electric energy. However, the natural characteristic of pulse output for conventional TENG, which means high crest factor, is defective for directly driving electronics. Here, a strategy to convert the pulse alternate current of TENG into a direct current with low crest factor is achieved through introducing a phase difference design into the structure of TENG. As a result, a direct current with a crest factor of 1.07 is obtained in a rotational free‐standing TENG (RF‐TENG) array at optimum phase difference, where 3D digital printing technology is used to accurately control the parameter of phase difference. Moreover, an adaptable contact mode structure between tribolayer and electrode improves the durability of the RF‐TENG array, which can present a stable performance after working 1.2 million cycles. This work provides a combined strategy to obtain a long‐lifetime and low crest‐factor TENG for its large‐scale application in energy harvesting. [ABSTRACT FROM AUTHOR]

This study aims to increase machine reliability thereby preventing product defects from adhesive dispense and slider attachment by a fault detection and diagnostic technique. The experiment was set up to investigate the vibration signal and motor current. Six fault conditions of a linear bearing were set up. The approaches, including spectrum analysis, crest factor, and analysis of variance, are used for data analysis. It was found that the spectrum analysis was suitable for classifying the frequency domains and the statistics tool was successful in measuring the current. Fault detection and diagnosis results can forecast the status of the linear bearings. [ABSTRACT FROM AUTHOR]

High-voltage insulators are one of the essential components of a power network, and regular monitoring of them ensures the reliable operation of the network. Therefore, several research groups have proposed different condition assessment indices by analyzing the measured leakage current of the polluted insulator at different environmental conditions. At laboratory conditions, those indices are developed under pure or nearly sinusoidal voltage waveforms. However, a considerable amount of harmonic distortion is prevalent in the supply voltage in real life owing to the ever-increasing trend in the use of power electronic devices in the power network; as a result, insulators in the power network are immediately subject to this distortion. Therefore, in the presence of distorted supply voltage, the efficacy of these current indicators developed for pollution severity assessment under purely sinusoidal voltage will become dubious. In this work, authors have investigated the impact of distorted supply voltage waveforms on the leakage current of an artificially polluted silicone rubber insulator. The result of this work indicates that in combination with contaminant severity and relative humidity, supply voltage distortion causes significant changes in the measured leakage current. Based on these findings, the authors further proposed a new crest factor-based index to predict the pollution level of a silicone rubber insulator. [ABSTRACT FROM AUTHOR]

With the expansion of the business over the internet, corporations nowadays are investing numerous amounts of money in the web applications. However, there are different threats could make the corporations vulnerable for potential attacks. One of these threats is harnessing the domain name protocol for passing harmful information, this kind of threats is known as DNS tunneling. As a result, confidential information would be exposed and violated. Several studies have investigated the machine learning in order to propose a detection approach. In their approaches, authors have used different and numerous types of features such as domain length, number of bytes, content, volume of DNS traffic, number of hostnames per domain, geographic location and domain history. Apparently, there is a vital demand to accommodate feature selection task in order to identify the best features. This paper proposes a hybrid method of genetic algorithm feature selection approach with the support vector machine classifier for the sake of identifying the best features that have the ability to optimize the detection of DNS tunneling. To evaluate the proposed method, a benchmark dataset of DNS tunneling has been used. Results showed that the proposed method has outperformed the conventional SVM by achieving 0.946 of f-measure [ABSTRACT FROM AUTHOR]

The results of statistical analysis of cross-correlation properties of complex signals’ ensembles, were obtained due to time interval permutations are presented in this paper. The essence of the method is to apply the division of short videopulse sequences at the level of intervals with low interaction in the time domain with different numbers of pulses. By applying the cross-correlation analysis, the maximum emission values of the side lobes of the cross-correlation functions are calculated and its total average value is determined. Based on the obtained values, a series is formed in which the first position is occupied by a time interval in which the value of the maximum emissions of the side lobes of the cross-correlation function has an average value. The determination of the following time intervals is based on the analysis of the rating series and the arrangement of values is carried out in accordance with the selected total average value. Thus, a new average range of the maximum emission values of the side lobes of the cross-correlation function is formed. The average range increases the number of ensembles with satisfactory cross-correlation properties for use in radio communication systems with code division multiplexing, and minimal interaction between signals in the time domain reduces multiple access interference.

The residual stress assessment in structures is essential for optimization of the structures' design. The attention of this paper is focused on how acoustic emission signals caused by tensile loading of the friction stir welded aluminum plates are expected to vary depending upon the residual stress. To this aim, the distribution of residual stresses in two friction stir welded aluminum specimens was firstly evaluated by ultrasonic stress measurement. AE signals were then produced during tensile tests and captured using AE sensors. The obtained AE signals were analyzed using statistical features including crest factor, cumulative crest factor and sentry function. It was found that the crest factor could be used to identify the presence of the residual stresses and that the trends of sentry function are in good agreement with the results of crest factor and cumulative crest factor.

Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal 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.)

Monitoring with fault diagnosis of machineries is critically important for production efficiency and plant safety in modern enterprises. The process of fault diagnosis along with extracting representative features from the vibrational signal with the existing Harmonised Swan Machine feature extraction technique resulted in high noise sensitivity, mixing mode problem and data loss. Moreover, measuring the correlation between the features with the existing fault diagnosis researches suffers from learning time limitations and memory constraints. Thus to commensurate a perfect diagnosis, in this research a "Robust Harmonised Swan Machine (RHSM) with Stalwart Trippy classifier" is formulated in which the iterative threshold VMD (Variational Mode Decomposition) estimation of each mode satisfying a self-consistency nature in decomposition method of RHSM is performed which in turn resolves the missing sample problem eminently independent of the signal type. Moreover, reinforcement learning uses a greedy layer wise approach empowering quick and dynamic sorts without repetition and accuracy thus measures the correlation between the features to classify the faulty features extremely thereby it takes only less memory constraint with less learning time. [ABSTRACT FROM AUTHOR]

We consider the Modified Kuramoto–Sivashinky Equation (MKSE) in one and two space dimensions and we obtain explicit and accurate estimates of various Sobolev norms of the solutions. In particular, by using the sharp constants which appear in the functional interpolation inequalities used in the analysis of partial differential equations, we evaluate explicitly the sup-norm of the solutions of the MKSE. Furthermore we introduce and then compute the so-called crest factor associated with the above solutions. The crest factor provides information on the distortion of the solution away from its space average and therefore, if it is large, gives evidence of strong turbulence. Here we find that the time average of the crest factor scales like λ (2 d - 1) / 8 for λ large, where λ is the bifurcation parameter of the source term and d = 1 , 2 is the space dimension. This shows that strong turbulence cannot be attained unless the bifurcation parameter is large enough. [ABSTRACT FROM AUTHOR]

Today, the increase in demand for electrical energy has revealed a more reliable and higher quality energy concept. This subject has taken its place in electrical engineering as "Power Quality" or "Electric Energy Quality" and has made a point for its importance with the studies on it. Especially in the process of working with devices containing electronic circuits with direct current and using the alternating current offered from the network by using rectifiers, the devices may fail or become disabled due to self-protection circuits in case of power quality problems arising from the mains or the rectifiers of the device. In this article, a detailed analysis is carried out considering the problem may be due to the power quality due to the fact that the MRI device in Kırıkkale University Faculty of Medicine is in continuous failure mode. In addition, the analyzes made in accordance with TS EN 50160 standard within the scope of the research were analyzed in computer environment and the results were shared in our article. In this article, the relationship between power quality problems and grounding is also examined. [ABSTRACT FROM AUTHOR]

Frequency scanning is a powerful and versatile approach for subsynchronous resonance (SSR) screening in power grids. Among different numerical and analytical frequency scanning techniques, the harmonic injection method is well suited for the scan of black-box models with active elements, such as in wind farms and solar plants. The results can be used for SSR risk assessment, in which accuracy performs a decisive role. The ideal situation for this method, which leads to the most accurate results, is to perform one simulation per single-frequency injection. However, for SSR studies with a wide range of frequencies and simulations with very small time steps (scale of μs), this comes at the expense of increased simulation time. This article proposes a technique to improve the accuracy of the harmonic injection method through the optimization of the crest factor while injecting all frequencies at one shot, therefore also reducing simulation time. The proposed technique was tested on a wind farm connected to a radial test case and on a portion of a Texas synthetic grid with multiple active elements, including two wind farms and a VSC-based STATCOM. The frequency scan results were benchmarked with both time-domain transient simulations and the ideal multiple single-frequency injection case and compared with other techniques. The results show that the proposed method is superior in accuracy when compared to the other techniques and is 11.71 times faster when compared to multiple single-frequency injections. [ABSTRACT FROM AUTHOR]

The high‐output triboelectric nanogenerator (TENG) is indispensable for its practical applications toward industrial products. However, the electricity loss in simple parallel connection among all units and the typically high crest factor output seriously hamper the practical applications of TENG. Here, a rectified TENG is reported in parallel structure to solve the problem of electricity loss in simple parallel connection. The rotational contact–separation structure with phase difference between rectified TENGs addresses high crest factor output and extends service life of rotational TENG simultaneously. The current crest factor is dramatically decreased to 1.31 in multiple rectifier multiple TENG in parallel (MRM‐TENG), while that of TENG in simple parallel is higher than 6. Meanwhile, the current output can retain up to ≈93% of its initial performance after 7 200 000 rotations under 2.00 r s−1 of 1000 h. Furthermore, the equivalent current can be in linear growth with low crest factor by making MRM‐TENG in parallel for distributed energy supply without electricity loss. This work may provide a new strategy for TENG in parallel to achieve a low crest factor output and long‐term cycling stability power generation in distributed energy harvesting for large‐scale power application. [ABSTRACT FROM AUTHOR]

The tone reservation method can be used to reduce the peak to average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) transmission systems. In this paper, the tone reservation method is analyzed for OFDM with a restricted carrier set, where only the positive carrier frequencies are used. Performing a fully analytical analysis, we give a complete characterization of the information sets for which the PAPR problem is solvable. To derive our main result, we connect the PAPR problem with a geometric functional analytic property of certain spaces. Furthermore, we present applications of our theory that give guidelines for choosing the information carriers in the finite setting and discuss a probabilistic approach for selecting the carriers. In addition, it is shown that if there exists an information sequence for which the PAPR problem is not solvable, then the set of information sequences for which the PAPR problem is not solvable is a residual set. [ABSTRACT FROM AUTHOR]

In the present work, defect detection in rolling bearing using empirical mode decomposition of vibration signal data has been done. Higher order statistical parameters viz root mean square, kurtosis, skewness, and crest factor are utilized to diagnose bearing fault. Simulated bearing defects as spall on outer race, on roller, and on inner race are used for the study. For experimental study, four different load and speed combination have been chosen to widen the acceptability of results. The effect of bearing speed on statistical parameters is also studied. Effectiveness of signal decomposition by the empirical mode decomposition method has been established by the results. Kurtosis and crest factor values of decomposed and unprocessed signals have been selected and empirical mode decomposition-based values are shown as effective parameters for defect identification. The crest factor and Kurtosis of outer race defect show greater sensitivity to the load and speed variations, while the skewness of same defect shows its insensitivity to load and speed variations. [ABSTRACT FROM AUTHOR]

The paper demonstrates the use of frequency reassignment for bearing estimation. For this task, signals derived from a linear equispaced passive array are used. The presented method makes use of Fourier transformation based spatial spectrum estimation. It is further developed through the application of two-dimensional reassignment, which leads to obtaining highly concentrated energy distributions in the joint frequency-angle domain and sharp graphical imaging. The introduced method can be used for analysing, a priori, unknown signals of broadband, nonstationary, and/or multicomponent type. For such signals, the direction of arrival is obtained based upon the marginal energy distribution in the angle domain, through searching for arguments of its maxima. In the paper, bearing estimation of three popular types of sonar pulses, including linear and hyperbolic frequency modulated pulses, as well as no frequency modulation at all, is considered. The results of numerical experiments performed in the presence of additive white Gaussian noise are presented and compared to conventional digital sum-delay beamforming performed in the time domain. The root-mean-square error and the peak-to-average power ratio, also known as the crest factor, are introduced in order to estimate, respectively, the accuracy of the methods and the sharpness of the obtained energy distributions in the angle domain.

Digital audio is one of the most important types of data at present. It is used in several applications, such as human knowledge and many security and banking applications. A digital voice signal is usually of a large size where the acoustic signal consists of a set of values distributed in one column (one channel) (mono signal) or distributed in two columns (two channels) (stereo signal), these values usually are the results of sampling and quantization of the original analogue voice signal. In this paper we will introduce a method which can be used to create a signature or key, which can be used later to identify or recognize the wave file. The proposed method will be implemented and tested to show the accuracy and flexibility of this method. [ABSTRACT FROM AUTHOR]

In this work we have analysed the nature of space fluctuations in dissipative Partial Differential Equations (PDEs). By taking a well known and much investigated dissipative PDE as our representative, namely the Swift–Hohenberg Equation, we estimated in an explicit manner the values of the crest factor of its solutions. We believe that the crest factor, namely the ratio between the sup-norm and the L 2 norm of solutions, is a suitable and proper measure of space fluctuations in solutions of dissipative PDEs. In particular it gives some information on the nature of "soft" and "hard" fluctuations regimes in the flows of dissipative PDEs. [ABSTRACT FROM AUTHOR]

In this work, we have introduced and then computed the so-called crest factor associated with solutions of dissipative partial differential equations (PDEs). By taking two paradigmatic dissipative PDEs, we estimated in an explicit and accurate manner the values of the crest factor of their solutions. We then analysed and compared the estimates as a function of the positive parameter which appears in the PDEs in space dimensions one and two. These estimates shed some light on the dynamics of the fluctuations of the solutions of the two model PDEs, and therefore provide a criterion for discerning between small and large potential excursions in space for the solution of any dissipative PDE. Being able to detect between small and large intermittent fluctuations is one of the hallmarks of turbulence. We believe that the crest factor is an appropriate tool for extracting space fluctuation features in solutions of dissipative PDEs. [ABSTRACT FROM AUTHOR]

This outcome of this research paper improves the quality and performance of the power system by using a four-quadrant chopper circuit in the DC -LINK of the variable speed drive systems (VSDS). In addition, the effects on reducing the ripple factor for both the current and voltage in DC-LINK are illustrated. In this study, a variable speed drive system is simulated and designed with the proposed chopper. Furthermore, the control system of pulses for the transistors is determined. Finally, a discussion of the results is introduced. The given results show the advantages of using the proposed chopper circuit with variable speed drive systems. Likewise, the superiority of the proposed method over other newly suggested techniques is verified by several simulation scenarios. [ABSTRACT FROM AUTHOR]