Frequency Estimation Method Research Articles

Estimation Method for High-Speed Vehicle Identification With UHF RFID Systems

An estimation method for Ultra High Frequency (UHF) Radio Frequency Identification (RFID)-based vehicle identification systems is presented. It allows the estimation of the number of reads within certain bounds at arbitrary vehicle velocities without requiring the knowledge of all system parameters. Based on this, a formula to calculate the maximum identifiable velocity is derived. It is also shown how the uncertainties of the formulas can be minimized. For the verification of the estimation method, two high-speed scenarios are described; the vehicle identification on roads and railways. Simulations with electromagnetic (EM) models of transponders mounted on different vehicles are described for both scenarios. It turns out that the simulated number of reads lies within the estimated range. Furthermore, a comparison with measurement data from a test track is presented. Here a good agreement between measured and estimated numbers of reads can be observed. The measured data is also used for the calculation of the maximum vehicle identification which lies in the range from 475.00 km/h 591.67 km/h. This means that for vehicle identification scenarios similar to the test track no speed limit is needed.

Revised Dicken’s method for flood frequency estimation of Upper Ganga basin

Flood discharge and its frequency is an important input to many infrastructure development, management and decision making models. However, for a number of potential sites, the data used for statistical analysis of flood discharge and its frequency, are either insufficient or unavailable. In such a situation, empirical formulae are the only alternative method to provide an estimate of design flood. Dicken’s formula is one of such empirical formulae used by practicing field engineers for flood estimation. In spite of its simplicity and applicability, Dicken’s formula is not capable of yielding flood volume at different desired frequency. In the present study an attempt has been made to modify the Dicken’s coefficient so as to accommodate the frequency component in flood estimation. For this purpose, observed flood discharge data sixteen gauging points of Ganga basin have been used to develop regional flood frequency curve, using probability weighted method, Index flood method, General extreme value and Wakeby distribution. Modified Dicken’s coefficient CT shows a sharp gradient for sub-catchments draining up to 5000 Km2. Further, CT value, ranges from 0.834 to 6.924. The CT –values are lower when calculated by Index Flood method while these are higher by Wakeby method. In all of these methods, CT –values do not approach the values of 11 or 14 as suggested for northern Indian catchments. An analysis of flood volume corresponding to CT –values of 11 or 14, reveals that these values yield high flood volume that correspond to return period of more than 1000 years and 3000 years respectively. These values are certainly very high for any rational design. Best fit distribution is decided, based on annual maximum discharge peak (ADF), Efficiency (EFF) and Standard Error (SE) parameters. Prediction accuracy of flood frequency analysis using revised Dicken’s formula is found to be above 85% for the best-fit distribution. General Extreme Value is found to be the best fit distribution for the Upper Ganga basin.

Analyses Through the Metastatistical Extreme Value Distribution Identify Contributions of Tropical Cyclones to Rainfall Extremes in the Eastern United States

AbstractTropical cyclones (TCs) generate extreme precipitation with severe impacts across large coastal and inland areas, calling for accurate frequency estimation methods. Statistical approaches that take into account the physical mechanisms responsible for these extremes can help reduce the estimation uncertainty. Here we formulate a mixed‐population Metastatistical Extreme Value Distribution explicitly incorporating non‐TC and TC‐induced rainfall and evaluate its implications on long series of daily rainfall for six major U.S. urban areas impacted by these storms. We find statistically significant differences between the distributions of TC‐ and non‐TC‐related precipitation; moreover, including mixtures of distributions improves the estimation of the probability of extreme precipitation where TCs occur more frequently. These improvements are greater when rainfall aggregated over durations longer than one day are considered.

The Impact of Data Collection Frequency and Trend Estimation Method on the Consistency of Growth Estimates From Two Computer-Adaptive Tests

ABSTRACTWithin multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the magnitude of average rates of growth as well as the stability of individual estimates of growth from a computer-adaptive test. Students in Grades 2 through 5 (n > 2,000) were progress monitored once a month across the 2015–2016 school year with Star Reading or Star Math assessments. Results suggest that using ordinary least squares regression to estimate growth from triannual screening periods is generally sufficient to make program evaluation decisions about response to instruction across a school year. To make decisions about individual student progress, data should be collected at a minimum bimonthly but preferably once a month.

A Portable System With 0.1-ppm RMSE Resolution for 1–10 MHz Resonant MEMS Frequency Measurement

This article presents a portable and programmable frequency measurement system (PrO-FMS) with 0.1-ppm RMSE resolution over a measurement time interval of 33.2 s for bulk-acoustic resonator applications. PrO-FMS has a feature of choosing a frequency estimation method and accordingly the sampling frequency, which is programmable. Five frequency estimation methods, Candan, Djukanovic, Prony, M-Pisarenko, and zero crossing interpolation methods, are reviewed for high-resolution frequency measurement. PrO-FMS can also be reconfigured to select a particular resonance mode over a range of 1–10 MHz. Measurement results are provided for two different commercial quartz crystals and a microfabricated in-plane bulk acoustic resonator in two different modes of resonance. The results of these estimation methods are compared with a standard commercial tabletop frequency counter. Measurement results show that PrO-FMS can achieve a resolution of 0.1 ppm RMSE. For the same gate time, PrO-FMS provides better resolution than standard tabletop frequency counter. This article also provides a study on the behavior of the five different frequency estimation methods for short- and long-term measurements for quartz crystals and bulk acoustic resonator in two different modes.

Method to estimate sag frequency in doubly fed induction generator integrated power system based on adaptive kernel density estimation

Voltage sag frequency estimation is necessary for understanding the voltage sag severity in power system and offering full information for the interested parties to mitigate voltage sag. The high penetration of wind power in the power system and the uncertainty of the fault distribution raise new challenges to accurate voltage sag frequency estimation. This study presents a systematic voltage sag frequency estimation method, considering the fault distribution density, fault ride-through (FRT) process of wind turbines during voltage sag and the interval characteristic of voltage sag frequency. First, this study proposes a fault distribution estimation model based on adaptive kernel density. Second, this study proposes a method for calculating the residual voltage and duration of voltage sag during FRT and combines the common distance protection action to analyse the effect on voltage sag by FRT process of wind turbines. Lastly, this study proposes an interval-valued voltage sag estimation method considering the interval characteristics of fault rate in the power system. IEEE 30-bus test system is used to verify the proposed method, the estimation results show better performance of the proposed method compared with the typical estimation methods.

A frequency estimation method for two adjacent frequencies

The frequency-domain estimation methods are estimate frequency from main-lobe. One shortcoming of these methods lies in the fact that they are not suited to two adjacent frequency components. When the distance between two frequency components is less than 3 DFT bins, former methods are subject to severe spectral interference, which results in considerable errors of estimate. In this paper, a discovery is made that side-lobes have relatively smaller spectral interference as compared to main-lobe, for which a novel estimation method based on the first side-lobes is proposed. As demonstrated by simulation, the proposed method performs better in two adjacent frequency components estimation. When the distance between two frequency components reaches 1.5 bins, the maximum estimation error is approximately 0.07 bins for the two frequencies.

Joint 2D DOA and Doppler frequency estimation for L-shaped array using compressive sensing

A joint two-dimensional (2D) direction-of-arrival (DOA) and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing (CS) framework. Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix, three smaller scale matrices with independent azimuth, elevation and Doppler frequency are introduced adopting a separable observation model. Afterwards, the estimation is achieved by L 1 -norm minimization and the Bayesian CS algorithm. In addition, under the L-shaped array topology, the azimuth and elevation are separated yet coupled to the same radial Doppler frequency. Hence, the pair matching problem is solved with the aid of the radial Doppler frequency. Finally, numerical simulations corroborate the feasibility and validity of the proposed algorithm.

Closed-Form Estimator for Frequency Estimation of Complex Sinusoidal Signals in Multiplicative and Additive Noise

In this paper, a new method is proposed for estimating the frequency of a complex sinusoidal signal in multiplicative and additive noise. The proposed method is based on the linear prediction property of the signals’ autocorrelation function. This frequency estimation method is a closed-form algorithm which can directly estimate the frequency without peak searching. The performance of the proposed frequency estimator is investigated by computer simulations. Simulation results demonstrate that the performance of the proposed technique is reasonable and is close to Cramer–Rao bound.

A Comparative Study between Pitch Detection Techniques on Reverberant Speech Signals

Reverberation is one of the effects that occur regularly in closed room due to multiple reflections. This paper investigates the result of reverberation on both male and female speech signals. This effect is reflected in pitch frequency of speech signals. This parameter is important as it is usually used for speaker identification. Hence, several methods for pitch frequency estimation are investigated and compared on clear and reverberant male and female speech signals to select the one that is not affected so much by the reverberation effect.

Research on a Signal Separation Method Based on Vold-Kalman Filter of Improved Adaptive Instantaneous Frequency Estimation

The fault vibration signal of rotating machinery system under strong background noise has the characteristics of non-stationary, non-Gaussian and complex components. In view of these characteristics, an improved method of signal separation based on Vold-Kalman filter (VKF) of adaptive instantaneous frequency estimation is proposed. First, a method for adaptive multiridge extraction of peaks detection based on synchro-squeezing wavelet transform (SWT) is proposed as the high-precision adaptive instantaneous frequency (IF) estimation method. The high precision IF estimation is used as the instantaneous frequency parameter of VKF, so that the complex multi-component non-stationary signal can be separated directly in the time domain and transformed into a signal combination composed of multiple stationary single-component signals and signal residues. Secondly, an improved method is proposed combining the adaptive IF estimation method with order tracking analysis and diagonal slice of bispectrum. In the improved method, the corresponding IF estimation of each component signal is taken as the reference frequency of its order tracking and the order spectrum analysis of each component signal is carried out respectively. Meanwhile, the signal residual is analyzed by diagonal slice of bispectrum, so as to suppress Gaussian noise and effectively separate and extract fault features in the vibration signal. Finally, the method is verified on simulation data and experimental data under different conditions. The results show that the improved method has higher extraction accuracy than other traditional methods. It has the superiority and the great potential for practical applications.

Rolling bearing fault diagnosis via STFT and improved instantaneous frequency estimation method

Bearing vibration signals exhibit instantaneous modulation features under variable rotating frequency, making it difficult to identify the characteristic frequency components. As such, a novel rolling bearing fault diagnosis method via short time Fourier transform (STFT) and improved instantaneous frequency estimation algorithm is proposed. The novelty is that it can convert all the trajectories of instantaneous components, e.g., fault characteristic frequency (FCF) and modulation rotating frequency, to linear path in the time-frequency domain. First, a band pass filter is applied to separate the optimal frequency band which is determined by fast kurtogram. Second, the envelope time-frequency representation (TFR) is obtained by jointly adopting Hilbert transform and STFT to the filtered signal. Next, the instantaneous fault characteristic frequency (IFCF) is extracted from the filtered TFR based on improved instantaneous frequency estimation algorithm. Then, the frequency representation is calculated by dealing with the TFR of the envelope. Finally, the proportion of FCF to rotational frequency on the frequency representation is computed and then compared with the theoretical characteristic coefficient. The method is evaluated via the experimental data. The result demonstrates that bearing fault pattern can be identified via the proposed method.

Accurate natural frequency estimation method for myotonometer using a system identification method

Accurate natural frequency estimation method for myotonometer using a system identification method

Experimental verification of resonance frequency estimation method in two-inertia system based on steady-state oscillation control

Experimental verification of resonance frequency estimation method in two-inertia system based on steady-state oscillation control

Estimation of Grid Frequency in Disturbed Converter-Based Power Systems by PLL State Variable Feedback

Fast real-time estimation of the grid frequency is essential for stable operation of renewable converter-based sources in future power systems. Therefore this paper presents a new phase-locked loop for the estimation of time-dependent frequencies in unbalanced power systems with harmonics. The proposed frequency estimation method consists of two signal processing steps: In the first step, a least mean square estimator reconstructs the fundamental sinusoidal signal from the measured three-phase grid voltage and splits it into positive, negative and zero sequence components. In the second step, the resulting first harmonic three-phase positive sequence is converted into the synchronous reference frame in the form of a phase-locked loop using a state feedback controller scheme to reconstruct the current grid frequency. Here the controller output is equivalent to the signal to be reconstructed. The feedback controller design is based on linear matrix inequalities where the requirements are explicitly considered. The capability of proposed state feedback phase-locked loop is demonstrated by full scaled electro magnetic transient simulations.

Recent Development of Frequency Estimation Methods for Future Smart Grid

The frequency estimated by the Phasor Measurement Unit (PMU) is a critical index of power system status and supports many smart grid applications. The future smart grid features high penetration of renewables and more fast-moving power electronics inverters but raises challenges to the reliable frequency estimation. This article presents three methods to address these challenges. First, an enhanced zero-crossing algorithm was developed to track the fast-changing frequency in system dynamics. Second, we propose a technology that can tolerate the system transient and suppress the outliers. Third, an algorithm was developed to export high time-resolution frequency estimations with minimum computational effort. All of the proposed methods are realized in hardware and compared with classical frequency estimation methods. The testing results indicate that the proposed methods have excellent performance. They can be used in future PMUs and provide reliable and high time resolution data for smart grid applications.

Multiple Interacting Narrowband Interferences Suppression Algorithm for OFDM Systems

The OFDM technology is widely used in wireless communication systems, but it is highly sensitive to narrowband interference (NBI). The existing NBI suppression algorithms are mainly for single NBI or multiple NBIs with an assumption that the frequency distance of the multiple NBIs is large enough. However, in reality, there are more and more multiple interacting NBIs with small frequency distance, such as NB-IoT. Unfortunately, due to the interaction of multiple NBIs, the performance of existing NBI suppression algorithms is degraded. Aiming at this problem, we propose a multiple interacting NBIs suppression algorithm jointed time-frequency domain for OFDM systems. First, in order to achieve a high-precision and low-complexity frequency estimate for a single NBI, an interference frequency estimation method based on chirp-z transform (CZT-IFE) is studied. Then, for multiple interacting NBIs, based on the analysis of NBI frequency distance and spectral aliasing, a highly robust interference frequency estimation method combining IIR notch filter and CZT-IFE (NF-CZT-IFE) is given. It eliminates the interaction of multiple NBIs and obtains the accurate frequency estimates of the NBIs. Finally, based on NF-CZT-IFE, the multiple interacting NBIs are suppressed by using IIR notch filters. Simulation results demonstrate that the proposed multiple interacting NBIs suppression algorithm has better interference suppression performance on the NBIs with different frequency distances and different interference numbers. The proposed algorithm improves the robustness of OFDM systems in complex NBI environments.

ENF Signal Enhancement in Audio Recordings

In electric network frequency (ENF) based audio forensics, the ENF signal captured in a questioned audio recording is estimated and analyzed for authentication purposes. However, the captured ENF signal is usually contaminated by very strong noise and interference. In this paper, we propose a robust filtering algorithm (RFA) for ENF signal enhancement in audio recordings, which could effectively suppress the additive noise and facilitate subsequent ENF estimation, especially in practical low signal-to-noise ratio (SNR) situations. The proposed algorithm encodes the time domain expression of the preprocessed audio signal (ENF signal plus noise) as the instantaneous frequencies (IFs) of an analytical sinusoidal frequency modulated (SFM) signal. Then, a kernel function is utilized to generate a sinusoidal time-frequency distribution (STFD) whose peaks correspond to the IFs of the analytical signal, i.e., the denoised ENF signal. It is then proven that finding the STFD peaks is equivalent to finding the averaged phases of the kernel function if the additive noise is a zero mean wide sense stationary (WSS) process. The RFA serves as a noise reduction mechanism yielding improved SNR at the filter output. Combined with generic frequency estimation methods, ENF extraction accuracy could be substantially improved with the use of the proposed RFA than without using it. Both synthetic and experimental results are provided to illustrate the effectiveness of our proposal. Reliable ENF extraction could be achieved under noise level down to −20 dB SNR, and the RFA is suitable for a wide range of ENF-based forensic applications.

Characterization of Historical Methane Occurrence Frequencies from U.S. Underground Natural Gas Storage Facilities with Implications for Risk Management, Operations, and Regulatory Policy.

Defining a baseline for the frequency of occurrences at underground natural gas storage facilities is critical to maintaining safe operation and to the development of appropriate risk management plans and regulatory approaches. Currently used frequency-estimation methods are reviewed and broadened in this article to include critical factors of cause, severity, and uncertainty that contribute to risk. A Bayesian probabilistic analysis characterizes the aleatoric historical occurrence frequencies given imperfect sampling. Frequencies for the three main storage facility types in the United States (depleted oil-and-gas field storage, aquifer storage, solution-mined salt cavern storage) are generally on the order of 3 to 9 × 10-2 occurrences, of all causes (surface, well integrity, subsurface integrity) and severities (nuisance, serious, catastrophic), per facility-year. Loss of well integrity is associated with many, but not all, occurrences either within the subsurface or from there up to the surface. The probability of one serious or catastrophic leakage occurrence to the ground surface within the next 10 years, assuming constant number of facilities, is approximately 0.1-0.3% for any facility type. Storage operators and industry regulators can use occurrence frequencies, their associated probabilities and uncertainties, and forecasts of severity magnitudes to better prioritize resources, establish a baseline against which progress toward achieving a reduction target could be measured, and develop more effective mitigation/monitoring/reduction programs in a risk management plan.

타이어 저압감지를 위한 타이어 공진 주파수 추정

Indirect tire pressure monitoring system(i-TPMS) monitors the inflation pressures in pneumatic tires by using wheel speed signals acquired from the anti-lock braking system(ABS). Frequency analysis and wheel radius analysis are performed at the same time in order to monitor the tire pressures indirectly. The resonance frequency of the tire torsional vibration decreases as the tire pressure decreases. It is necessary to estimate the resonance frequency in order to detect a reduction in tire pressure. This paper discusses the method of estimating the resonance frequency with the rotational wheel speed signal. First, the toothed wheel error of the wheel speed sensor and the wheel speed corrected with the toothed wheel error are calculated from the wheel speed signals. The engine noise caused by the explosion in the four-stroke of engine is eliminated by the notch filter, which is designed by using the engine rotational speed. Finally, the resonance frequency is evaluated via model parameter estimation based on the autoregressive(AR) model. Vehicle tests have been conducted in order to evaluate the proposed estimation method of resonance frequency. The findings of the vehicle test have shown that the proposed method provides satisfactory performance for the warning indication of tire pressure loss.