Frequency Tracking Method Research Articles

Computation and simulation of frequency variations in musical instrument sounds

Frequency variations of musical instrument sounds were measured using phase-derivative and frequency-tracking methods based on the short-time Fourier transform. Frequency variations are important features of instrument sounds and are very useful for musical expression. Three categories of variation are: vibrato, portamento, and microvariation. Microvariations exist even when a tone is played at a constant pitch, and they can be approximated as small frequency-deviation low-frequency noise signals. Portamento is a purposeful pitch glide embellishment that can occur during attacks, between notes, or, less often, at the ends of notes. Vibrato can be characterized as an approximately sinusoidal frequency variation, and usually its amplitude is sufficient to interact with instrument resonances and cause significant harmonic amplitude modulations. Deviation amplitudes and frequencies of acoustic instrument vibratos are not perfectly steady, but rather vary over the durations of instrument tones. Measurements of vibrato characteristics of the harmonic frequencies and amplitudes as well as the frequency and amplitude microvariations of various instruments and voice indicate that a variety of parameters are required for effective instrument synthesis. The challenge in synthesis is to avoid a “mechanical sound.”

Research on the Frequency Tracking in Rotary Ultrasonic Machining

According to the characteristics of rotary ultrasonic machining, the paper designs rotary ultrasonic power matching circuits. It presents compound frequency tracking method that utilizing Phase-Locked Loop (PLL) on accurate frequency tracking and maximum current method on rough frequency tracking. A control strategy of frequency tracking based on adjusting matching inductance and driving frequency was described. The experimental results verify the proposed compound frequency tracking method is feasible and effective which eliminates temperature, load changed on the effect of the transducer.

Fast frequency tracking

A method of periodical signal frequency tracking by the frequency-locked loops is proposed. Increasing of frequency adjustment accuracy is achieved by using of a new fast frequency discriminator, based on estimates of an instantaneous frequency. Reasonability of an input signal pre-filtering in case of nonlinear distortions, harmonics interferences and strong noise is proved.

A New Design of Ultrasonic Power Based on ARM

An ultrasonic power for rotary machining is introduced based on ARM. Its frequency tracking principle is analyzed. The improved accurate frequency tracking method using a phase lock loops (PLL) is presented. The control circuit based on ARM is designed and the presentation of system program flow chart is given. The experimental result proved that the ultrasonic power system can realize quick and accurate frequency tracking. Ihe power can work well with constant amplitude control.

ENF Extraction From Digital Recordings Using Adaptive Techniques and Frequency Tracking

A novel forensic tool used for assessing the authenticity of digital audio recordings is known as the electric network frequency (ENF) criterion. It involves extracting the embedded power line (utility) frequency from said recordings and matching it to a known database to verify the time the recording was made, and its authenticity. In this paper, a nonparametric, adaptive, and high resolution technique, known as the time-recursive iterative adaptive approach, is presented as a tool for the extraction of the ENF from digital audio recordings. A comparison is made between this data dependent (adaptive) filter and the conventional short-time Fourier transform (STFT). Results show that the adaptive algorithm improves the ENF estimation accuracy in the presence of interference from other signals. To further enhance the ENF estimation accuracy, a frequency tracking method based on dynamic programming will be proposed. The algorithm uses the knowledge that the ENF is varying slowly with time to estimate with high accuracy the frequency present in the recording.

Frequency Adaptive Least-Squares-Kalman Technique for Real-Time Voltage Envelope and Flicker Estimation

This paper presents real-time implementation of a new frequency adaptive least-squares-Kalman (LSK) technique to monitor voltage flicker and fluctuations in power system. The proposed method is based on a two-level mathematical model of a voltage waveform. A simple low computation frequency tracking method is also introduced. The least-squares (LS) optimization algorithm extracts the fundamental frequency component of the voltage and updates its internal model based on the estimated frequency of the voltage waveform. The Kalman filter, which works in combination with the LS algorithm, is developed to predict the instantaneous voltage flicker level. The proposed method is robust and adaptive and is evaluated experimentally through real-time implementation with a widely available digital control board.

Frequency Tracking and Locking Method Used in Resonator Micro-Optic Gyro

Frequency Tracking and Locking Method Used in Resonator Micro-Optic Gyro

A Frequency Tracking Method Based on Improved Adaptive Notch Filter for Coriolis Mass Flowmeter

Adaptive notch filters (ANF) are known have non-absolute convergence problems which will lead to precision reduction in long-playing frequency tracking. In this paper, we propose an improved ANF based on Steiglitz-McBride method (SMM) for Coriolis mass flowmeter (CMF) whose frequency, amplitude and phase are time-varying based on the random walk model. An monitor is designed to monitor whether the frequency is estimated rightly or the ANF just filters noise. If the frequency of CMF’s signal is missed, we will modify the parameters and restart the ANF to resume the search for the correct frequency again. The particular algorithm of the improved ANF is also put forward. Simulations have verified the effectiveness of the presented method in tracking CMF’s frequency, which shows superior performance comparing to the primary SMM based ANF.

Driver Design of the Piezoelectric Ultrasonic Transducer for Wire Bonding Based on Direct Digital Synthesis Technology

In order to design a driver of piezoelectric ultrasonic transducer which can provide high quality ultrasonic signal and be able to realize the frequency tracking rapidly, accurately and intelligently during the bonding process, the ATmega128 microcontroller and AD9851 synthesizer are selected as core components to build an ultrasonic generator and frequency tracking system. The basic circuit units including low pass filter, power amplifier, signal detection and conversion circuits are also established. The test results of the system shows that, based on DDS technology, high quality ultrasonic signal for transducer can be achieved. By combining the two kinds of frequency tracking methods, the system can realize the frequency tracking during the bonding process. It also indicates that the design significantly improve the precision and flexibility of the ultrasonic generator system.

A performance evaluation of vision and radio frequency tracking methods for interacting workforce

Analysis and understanding of worksite operations requires the collection of trajectory information regarding active onsite entities. The trajectories provide essential information for assessment of site operations and management strategies. Unfortunately, many such tracking and assessment methods are based on manually generated trajectories, thereby excluding long term and complex scenarios. Automated trajectory extraction is a potential solution, however the automated method must provide reliable trajectory information. This paper evaluates the capability of two sensor technologies to provide accurate trajectory data. The primary system investigated is a vision-based strategy while the secondary system investigated is an Ultra Wideband System (UWB). A robotic total station (RTS) provides the ground truth of a single worker for evaluation of both sensor technologies. For comparison, the visual tracking signal is mapped to three-dimensional world coordinates. The UWB and RTS signals are filtered to remove outliers, and are synchronized with the visual tracking signal. Given the single target tracked by the RTS, both UWB and vision are shown to be feasible when the expected accuracy is 1 m. A second investigation seeks to demonstrate the accuracy of the proposed visual tracking system for tracking multiple interacting workforce, which relies on machine learning to generate target descriptions. The UWB signals for the personnel provide ground truth to evaluate the reliability and accuracy of the vision-based tracking algorithm. The proposed visual tracking system is reliable and accurate enough to permit automated extraction of trajectory information for analysis purposes, such as would be required for work sampling and productivity assessments.

Investigation of Adaptive Matching Methods for Near-Field Wireless Power Transfer

Adaptive matching methods for a wireless power transfer system in the near-field region are investigated. The impedance and resonant frequency characteristic of a near-field power transfer system are analyzed according to coupling distance. In the near-field region, adaptive matching is necessary to achieve an effective power transfer. We compare the power transfer efficiencies of several schemes including simultaneous conjugate matching and frequency tracking. It is found that effective adaptive matching can be easily achieved by tracking the split resonant frequency. In addition, a modified frequency tracking method is proposed to extend the range over which the power is transmitted with high efficiency. The experimental results are in agreement with the theoretical results.

New frequency tracking method for coriolis mass flowmeter based on adaptive notch Filter

New frequency tracking method for coriolis mass flowmeter based on adaptive notch Filter

谐振式微光学陀螺频率跟踪与锁定技术研究

谐振式微光学陀螺频率跟踪与锁定技术研究

Active vibration control using optimized modified acceleration feedback with Adaptive Line Enhancer for frequency tracking

Modified acceleration feedback (MAF) control, an active vibration control method that uses collocated piezoelectric actuators and accelerometer is developed and its gains optimized using an optimal controller. The control system consists of two main parts: (1) frequency adaptation that uses Adaptive Line Enhancer (ALE) and (2) an optimized controller. Frequency adaptation method tracks the frequency of vibrations using ALE. The obtained frequency is then fed to MAF compensators. This provides a unique feature for MAF, by extending its domain of capabilities from controlling a certain mode of vibrations to any excited mode. The optimized MAF controller can provide optimal sets of gains for a wide range of frequencies, based on the characteristics of the system. The experimental results show that the frequency tracking method works quite well and fast enough to be used in a real-time controller. ALE parameters are numerically and experimentally investigated and tuned for optimized frequency tracking. The results also indicate that the MAF can provide significant vibration reduction using the optimized controller. The control power varies for vibration suppression at different resonance frequencies; however, it is always optimized.

Instantaneous frequency of an arbitrary signal

This paper defines the non-negative pointwise instantaneous frequency (pIF) and pointwise instantaneous amplitude (pIA) of an arbitrary time signal to be the circular frequency and radius of curvature of the signal’s instantaneous trajectory on the complex plane consisting of the signal and its conjugate part from the Hilbert transform. One analytical and three computational methods are derived to prove and validate this concept. The analytical method is derived based on the definition of pIF and circle fitting. A five-point frequency tracking method is developed to eliminate the incapability of the original four-point Teager–Kaiser algorithm (TKA) for obtaining pIF of signals with moving averages. A three-point conjugate-pair decomposition (CPD) method is derived based on circle fitting using a pair of conjugate harmonic functions for frequency tracking. Moreover, the Hilbert–Huang transform (HHT) uses the empirical mode decomposition (EMD) to sift a signal’s instantaneous dynamic component from its sectional moving average (sMA) as the first intrinsic mode function, and then Hilbert transform is used to compute the first IMF’s frequency and amplitude as the sectional instantaneous frequency (sIF) and sectional instantaneous amplitude (sIA). Because finite difference is used in the five-point TKA, its accuracy is easily destroyed by noise. On the other hand, because CPD uses a constant and a pair of windowed regular harmonics to fit data points and estimate pIF and pIA, noise filtering is an implicit capability of CPD and its accuracy increases with the number of processed data points. Numerical simulations confirm that pIF and pIA are non-negative and physically meaningful and can be used for frequency tracking and accurate characterization of complex signals. However, sIF and sIA from HHT are more useful for system identification because the IMFs sifted by EMD often correspond to actual vibration modes.

Method for maneuvering target video frequency tracking based on inductive factor of posture information

A method for maneuvering target tracking based on inductive factor of posture information is proposed. A distinguished characteristic of video frequency tracking is that it can capture the target posture changes from its picture easily, and the posture change means the motive model of the target will change. This information is very important to predict the trace of maneuvering target. Based on this idea, the quantified values of the target posture change are obtained using Hough algorithm, this key values are defined as inductive factor of posture information, and then, the multiple grey trace predict models are established and the degrees of fuzzy subordinate values for every model are calculated with the inductive factor, the maneuvering extent values are determined by a new analysis method of stochastic differential equations for each model used to modify the degree of fuzzy subordinate values, these constitute the weighted values for every grey predict collection. Finally, the synthesis predicting weighted result is obtained. The experimental results show that the new method is superior to the conventional algorithm.

CIRCULAR INSTANTANEOUS FREQUENCY

This work defines the unique instantaneous frequency (IF) of an arbitrary time signal to be the circular instantaneous frequency (cIF) of the curvature radius of the signal's trajectory on the phase plane, where the signal's conjugate part is obtained from Hilbert transform (HT). Because a general signal of a dynamical system of multiple degrees of freedom contains multiple modal vibrations, its cIF varies dramatically and is not useful for system identification and other applications. If the signal is decomposed into modal vibration components without moving average, each component has no local extrema within each fundamental period and no local loops on the phase plane, each component's referred instantaneous frequency (rIF) with respect to the origin on the phase plane may be non-circular but is always non-negative, and the time-varying rIF and referred instantaneous amplitude (rIA) are convenient for combining the use of perturbation analysis for system identification. The empirical mode decomposition (EMD) of Hilbert–Huang transform (HHT) is valuable for decomposing a general nonlinear nonstationary signal into zero-mean intrinsic mode functions (IMFs), and HT enables accurate calculation of rIF and rIA of each IMF. Although the concept of circular frequency cannot be used for signal decomposition, it enables the development of time-domain-only techniques for online frequency tracking. A 5-point frequency tracking method is developed to eliminate the incapability of the original 4-point Teager–Kaiser algorithm (TKA) for frequency tracking of signals with moving averages. Moreover, a 3-point conjugate-pair decomposition (CPD) method is derived based on circle-fitting using a pair of conjugate harmonic functions. It is shown that both CPD and TKA are based on the concept of circle fitting, but TKA uses finite difference and CPD uses curve fitting in numerical implementation. However, the accuracy of TKA is easily destroyed by noise because of the use of finite difference. On the other hand, because CPD is based on curve fitting, noise filtering is an implicit capability and its accuracy increases with the number of processed data points. The rIF from HHT and the cIF from CPD and TKA are different by definition. Moreover, because the instantaneous frequency and amplitude are assumed to be constant in CPD and TKA, the cIF from CPD and TKA also deviates from the exact cIF.

Three-point Frequency Tracking Method

This paper presents and evaluates in detail a harmonics tracking method (HTM) for tracking the instantaneous frequency and amplitude of a vibration signal by processing only three most recent data points. Teager—Kaiser algorithm (TKA) is a popular four-point method for online frequency tracking, but its accuracy is easily destroyed by measurement noise due to the use of finite difference. Moreover, because a signal is assumed to be a pure harmonic in TKA, any moving average in the signal can destroy the accuracy of TKA. On the other hand, HTM uses a constant and a pair of harmonics to fit three recent data points and estimate the instantaneous frequency and amplitude, and it dramatically reduces the influence of any moving average. Moreover, noise filtering is an implicit capability of HTM even if only three points are processed, and this capability increases with the number of processed points. However, HTM depends on TKA to provide the first frequency estimation in order to start online tracking. To compare HTM and TKA and evaluate the accuracy of HTM, Hilbert— Huang transform (HHT) is used to extract accurate time-varying frequency and amplitude by processing the whole data set without assuming the signal to be harmonic. Frequency and amplitude tracking of different amplitude- and/or frequency-modulated signals and nonlinear nonstationary dynamic signals is studied. Results show that HTM is more accurate, robust, and versatile than TKA for online frequency tracking. Moreover, the frequencies and amplitudes tracked by HTM have about the same accuracy as those extracted by HHT, but without the edge effect that HHT suffers from.

A novel frequency tracking method based on complex adaptive linear neural network state vector in power systems

This paper presents the application of a Complex Adaptive Linear Neural Network (CADALINE) in tracking the fundamental power system frequency. In this method, by using stationary-axes Park transformation in addition to producing a complex input measurement, the decaying DC offset is eliminated. As the proposed method uses first-order differentiator to estimate frequency changes, a Hamming filter is used to smoothen the response and cancel high-frequency noises. The most distinguishing features of the proposed method are the reduction in the size of observation state vector required by a simple Adaptive Linear Neural Network (ADALINE) and increase in the accuracy and convergence speed under transient conditions. This paper concludes with the presentation of the representative results obtained in numerical simulation and simulation in PSCAD/EMTDC software as well as in practical study.

Stimulus design for auditory neuroethology using state space modeling and the extended Kalman smoother

A new method for designing vocalization based stimuli for experiments in auditory neurophysiology is described. This analysis-synthesis technique leverages a state space statistical signal model and the extended Kalman smoother for tracking the frequency, amplitude, and phase information of harmonically related components in recorded vocalizations. Using the same state space model, these parameters can then be used to synthesize the vocalizations and random or deterministic variants of the vocalizations. This method is shown to outperform short-time Fourier transform based frequency tracking methods in both noisy and noise-free synthetic test signals. It is further shown to accurately track recorded hummingbird, human, and bat vocalizations while removing recording artifacts such as noise, echo, and digital aliasing in the synthesis phase.