Academic literature on the topic 'Time-frequency distribution (TFD)'
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Journal articles on the topic "Time-frequency distribution (TFD)"
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Mika, Dariusz, Grzegorz Budzik, and Jerzy Józwik. "Single Channel Source Separation with ICA-Based Time-Frequency Decomposition." Sensors 20, no. 7 (April 3, 2020): 2019. http://dx.doi.org/10.3390/s20072019.
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This paper relates to the separation of single channel source signals from a single mixed signal by means of independent component analysis (ICA). The proposed idea lies in a time-frequency representation of the mixed signal and the use of ICA on spectral rows corresponding to different time intervals. In our approach, in order to reconstruct true sources, we proposed a novelty idea of grouping statistically independent time-frequency domain (TFD) components of the mixed signal obtained by ICA. The TFD components are grouped by hierarchical clustering and k-mean partitional clustering. The distance between TFD components is measured with the classical Euclidean distance and the β distance of Gaussian distribution introduced by as. In addition, the TFD components are grouped by minimizing the negentropy of reconstructed constituent signals. The proposed method was used to separate source signals from single audio mixes of two- and three-component signals. The separation was performed using algorithms written by the authors in Matlab. The quality of obtained separation results was evaluated by perceptual tests. The tests showed that the automated separation requires qualitative information about time-frequency characteristics of constituent signals. The best separation results were obtained with the use of the β distance of Gaussian distribution, a distance measure based on the knowledge of the statistical nature of spectra of original constituent signals of the mixed signal.
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Wang, Yuqi, Jun Wang, Xingxing Jiang, Weiguo Huang, Juanjuan Shi, and Zhongkui Zhu. "Varying-parameter time-frequency manifold for gearbox fault diagnosis." Journal of Physics: Conference Series 2184, no. 1 (March 1, 2022): 012008. http://dx.doi.org/10.1088/1742-6596/2184/1/012008.
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Abstract The vibration signals of a faulty gearbox are non-stationary and contaminated by heavy background noise. Time-frequency transform is able to present the non-stationary fault impulsive features in the time-frequency distribution (TFD). However, the time-frequency fault information is still contaminated by the noise. This paper proposes a varying-parameter time-frequency manifold (VPTFM) method with the aim to remove the noise in the TFD for accurate identification of gearbox fault. First, a high-dimensional TFD is constructed by performing short- time Fourier transform (STFT) using some variable window lengths. Then, local tangent space alignment (LTSA) algorithm is carried out on the high-dimensional TFD to extract the manifold of the fault impulsive features with two dimensions, in which Rényi entropy is employed to select the proper neighborhood size for the LTSA by evaluating the first dimensional manifold. Afterwards, a threshold is designed by exploring the characteristics of the amplitudes of the manifold at two dimensions to adaptively remove the noise survived in the first dimensional manifold. Finally, the amplitudes at the frequency possessing the largest energy in the denoised manifold are taken out for spectrum analysis to identify the fault characteristic frequency. The enhanced performance of the proposed method in extraction of fault impulses and removal of background noise is validated by a gearbox experimental vibration signal measuring when the gear has a wearing fault.
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Wang, S. C., J. Han, Jian Feng Li, and Zhi Nong Li. "Adaptive Signal Analysis Based on Radial Parabola Kernel." Applied Mechanics and Materials 10-12 (December 2007): 737–41. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.737.
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Because of the deficiency of fixed kernel in bilinear time-frequency distribution (TFD), i.e. for each mapping, the resulting time-frequency representation is satisfactory only for a limited class of signals, a new adaptive kernel function named the radial parabola kernel (RPK), is proposed. The RPK can adopt the optimizing method to filter cross-terms adaptively according to the signal distribution, obtain good time-frequency resolution, and offer improved TFD for a large class of signals. Compared with traditional fixed -kernel functions, such as Wigner-Ville distribution, Choi-Willams distribution and Cone-kernel distribution, the superiority of the RPK function is obvious. At last, the RPK function is applied to the analysis of vibration signals of bearing, and the result proves the RPK function an effective method in analyzing signals.
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Habban, M. F., M. Manap, A. R. Abdullah, M. H. Jopri, and T. Sutikno. "An Evaluation of Linear Time Frequency Distribution Analysis for VSI Switch Faults Identification." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 1 (March 1, 2017): 1. http://dx.doi.org/10.11591/ijpeds.v8.i1.pp1-9.
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This paper present an evaluation of linear time frequency distribution analysis for voltage source inverter system (VSI). Power electronic now are highly demand in industrial such as manufacturing, industrial process and semiconductor because of the reliability and sustainability. However, the phenomenon that happened in switch fault has become a critical issue in the development of advanced. This causes problems that occur study on fault switch at voltage source inverter (VSI) must be identified more closely so that problems like this can be prevented. The TFD which is STFT and S-transform method are analyzed the switch fault of VSI. To identify the VSI switches fault, the parameter of fault signal such as instantaneous of average current, RMS current, RMS fundamental current, total waveform distortion, total harmonic distortion and total non-harmonic distortion can be estimated from TFD. The analysis information are useful especially for industrial application in the process for identify the switch fault detection. Then the accuracy of both method, which mean STFT and S-transform are identified by the lowest value of mean absolute percentage error (MAPE). In addition, the S-transform gives a better accuracy compare with STFT and it can be implement for fault detection system.
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Manap, Mustafa, Abdul Rahim Abdullah, Srete Nikolovski, Tole Sutikno, and Mohd Hatta Jopri. "An improved smooth-windowed Wigner-Ville distribution analysis for voltage variation signal." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (October 1, 2020): 4982. http://dx.doi.org/10.11591/ijece.v10i5.pp4982-4991.
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This paper outlines research conducted using bilinear time-frequency distribution (TFD), a smooth-windowed wigner-ville distribution (SWWVD) used to represent time-varying signals in time-frequency representation (TFR). Good time and frequency resolutions offer superiority in SWWVD to analyze voltage variation signals that consist of variations in magnitude. The separable kernel parameters are estimated from the signal in order to get an accurate TFR. The TFR for various kernel parameters is compared by a set of performance measures. The evaluation shows that different kernel settings are required for different signal parameters. Verification of the TFD that operated at optimal kernel parameters is then conducted. SWWVD exhibits a good performance of TFR which gives high peak-to-side lobe ratio (PSLR) and signal-to-cross-terms ratio (SCR) accompanied by low main-lobe width (MLW) and absolute percentage error (APE). This proved that the technique is appropriate for voltage variation signal analysis and it essential for development in an advanced embedded system.
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Ma, Ding, Li Hua Shi, Shang Chen Fu, and Hong Fu Cao. "Localization of Lamb Wave Scattering Source Based on Time-Frequency Analysis." Applied Mechanics and Materials 281 (January 2013): 276–81. http://dx.doi.org/10.4028/www.scientific.net/amm.281.276.
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Considering the influence of Lamb wave dispersion on the precision of damage detection, a new detection method of scattering source based on time-frequency curves and ellipse localization method is proposed. Empirical mode decomposition(EMD) is used to decompose the scattering signal into finite narrowband signals, and a modified continuous wavelet transform(CWT) is further used to get the time-frequency distribution(TFD) of the detected signal, and the arriving time of different frequency component is estimated based on TFD. A series of location results can be obtained from different frequency components using ellipse localization method. The damage position can finally be estimated by synthesizing localization results at different frequencies. Experiments on aluminum plate are conducted to demonstrate the efficiency of the proposed method. EMD-CWT analysis can get precise time-frequency curves in highly dispersive low frequency band of A0 mode. The damage location results is more accurate and the influence from occasional factors can be suppressed by using the synthesized method.
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Ponce de León, Jesús, José Ramón Beltrán, and Fernando Beltrán. "Instantaneous frequency estimation and representation of the audio signal through Complex Wavelet Additive Synthesis." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 03 (May 2014): 1450030. http://dx.doi.org/10.1142/s0219691314500301.
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In this work, an improvement of the Complex Wavelet Additive Synthesis (CWAS) algorithm is presented. This algorithm is based on a discrete version of the Complex Continuous Wavelet Transform (CCWT) which analyzes the input signal in a frame-to-frame approach and under variable frequency resolution per octave. After summarizing several Time-Frequency Distributions (TFD), concretely the standard Short Time Fourier Transform (STFT), the Pseudo Wigner–Ville Distribution (PWVD), reassignment and complex wavelets, a comparative study of the accuracy in the instantaneous frequency (IF) estimation is shown. The comparative study includes three different signal processing tools (based on the summarized TFD): the Time-Frequency Toolbox (TFTB) of François Auger, the High Resolution Spectrographic Routines (HRSR) of Sean Fulop and the proposed CWAS algorithm. A set of eight synthetic signals have been analyzed using six different methods: the regular STFT spectrogram, the PWVD, their corresponding reassigned versions, the Nelson crossed spectrum method and finally the Complex Continuous Wavelet Transform (CCWT). Finally, two- and three-dimensional Time-Frequency representations of the IF provided by the CWAS algorithm are presented.
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Park, Gi Young, C. K. Lee, Jung Taek Kim, K. C. Kwon, and Sang J. Lee. "Design of a Time-Frequency Distribution for Vibration Monitoring under Corrosions in the Pipe." Key Engineering Materials 321-323 (October 2006): 1257–61. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.1257.
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To monitor the wear and degradation on a pipe by corrosion during a plant operation, the vibration signals were measured by an accelerometer and analyzed by several analysis techniques. From the conventional methods, it was difficult to identify the wear and degradation on the pipe. And hence, the time-frequency distribution (TFD) and the adaptive cone-kernel distribution (ACKD) devised for reducing the interfering cross-terms are applied to the acquired data. They can provide the distinguishing peak patterns between the normal and corrosion signals.
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Jopri, M. H., A. R. Abdullah, T. Sutikno, M. Manap, M. R. Ab Ghani, and M. R. Yusoff. "A Critical Review of Time-frequency Distribution Analysis for Detection and Classification of Harmonic Signal in Power Distribution System." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4603. http://dx.doi.org/10.11591/ijece.v8i6.pp4603-4618.
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<p>This paper presents a critical review of time-frequency distributions (TFDs) analysis for detection and classification of harmonic signal. 100 unique harmonic signals comprise of numerous characteristic are detected and classified by using spectrogram, Gabor transform and S-transform. The rulebased classifier and the threshold settings of the analysis are according to the IEEE Standard 1159 2009. The best TFD for harmonic signals detection and classification is selected through performance analysis with regards to the accuracy, computational complexity and memory size that been used during the analysis.</p>
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Mousa, Allam, and Rashid Saleem. "Using Reduced Interference Distribution to Analyze Abnormal Cardiac Signal." Journal of Electrical Engineering 62, no. 3 (May 1, 2011): 168–72. http://dx.doi.org/10.2478/v10187-011-0028-9.
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Using Reduced Interference Distribution to Analyze Abnormal Cardiac SignalDue to the non-stationary, multicomponent nature of biomedical signals, the use of time-frequency analysis can be inevitable for these signals. The choice and selection of the proper Time-Frequency Distribution (TFD) that can reveal the exact multicomponent structure of biological signals is vital in many applications, including the diagnosis of medical abnormalities. In this paper, the instantaneous frequency techniques using two distribution functions are applied for analysis of biological signals. These distributions are the Wigner-Ville Distribution and the Bessel Distribution. The simulation performed on normaland abnormal cardiac signals show that the Bessel Distribution can clearly detect the QRS complexes. However, Wigner-Ville Distribution was able to detect the QRS complexes in the normal signa, but fails to detect these complexes in the abnormal cardiac signal.
Dissertations / Theses on the topic "Time-frequency distribution (TFD)"
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Sucic, Victor. "Parameters selection for optimising time-frequency distributions and measurements of time-frequency characteristics of nonstationary signals." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15834/1/Victor_Sucic_Thesis.pdf.
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The quadratic class of time-frequency distributions (TFDs) forms a set of tools which allow to effectively extract important information from a nonstationary signal. To determine which TFD best represents the given signal, it is a common practice to visually compare different TFDs' time-frequency plots, and select as best the TFD with the most appealing plot. This visual comparison is not only subjective, but also difficult and unreliable especially when signal components are closely-spaced in the time-frequency plane. To objectively compare TFDs, a quantitative performance measure should be used. Several measures of concentration/complexity have been proposed in the literature. However, those measures by being derived with certain theoretical assumptions about TFDs are generally not suitable for the TFD selection problem encountered in practical applications. The non-existence of practically-valuable measures for TFDs' resolution comparison, and hence the non-existence of methodologies for the signal optimal TFD selection, has significantly limited the use of time-frequency tools in practice. In this thesis, by extending and complementing the concept of spectral resolution to the case of nonstationary signals, and by redefining the set of TFDs' properties desirable for practical applications, we define an objective measure to quantify the quality of TFDs. This local measure of TFDs' resolution performance combines all important signal time-varying parameters, along with TFDs' characteristics that influence their resolution. Methodologies for automatically selecting a TFD which best suits a given signal, including real-life signals, are also developed. The optimisation of the resolution performances of TFDs, by modifying their kernel filter parameters to enhance the TFDs' resolution capabilities, is an important prerequisite in satisfying any additional application-specific requirements by the TFDs. The resolution performance measure and the accompanying TFDs' comparison criteria allow to improve procedures for designing high-resolution quadratic TFDs for practical time-frequency analysis. The separable kernel TFDs, designed in this way, are shown to best resolve closely-spaced components for various classes of synthetic and real-life signals that we have analysed.
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Sucic, Victor. "Parameters Selection for Optimising Time-Frequency Distributions and Measurements of Time-Frequency Characteristics of Nonstationary Signals." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15834/.
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The quadratic class of time-frequency distributions (TFDs) forms a set of tools which allow to effectively extract important information from a nonstationary signal. To determine which TFD best represents the given signal, it is a common practice to visually compare different TFDs' time-frequency plots, and select as best the TFD with the most appealing plot. This visual comparison is not only subjective, but also difficult and unreliable especially when signal components are closely-spaced in the time-frequency plane. To objectively compare TFDs, a quantitative performance measure should be used. Several measures of concentration/complexity have been proposed in the literature. However, those measures by being derived with certain theoretical assumptions about TFDs are generally not suitable for the TFD selection problem encountered in practical applications. The non-existence of practically-valuable measures for TFDs' resolution comparison, and hence the non-existence of methodologies for the signal optimal TFD selection, has significantly limited the use of time-frequency tools in practice. In this thesis, by extending and complementing the concept of spectral resolution to the case of nonstationary signals, and by redefining the set of TFDs' properties desirable for practical applications, we define an objective measure to quantify the quality of TFDs. This local measure of TFDs' resolution performance combines all important signal time-varying parameters, along with TFDs' characteristics that influence their resolution. Methodologies for automatically selecting a TFD which best suits a given signal, including real-life signals, are also developed. The optimisation of the resolution performances of TFDs, by modifying their kernel filter parameters to enhance the TFDs' resolution capabilities, is an important prerequisite in satisfying any additional application-specific requirements by the TFDs. The resolution performance measure and the accompanying TFDs' comparison criteria allow to improve procedures for designing high-resolution quadratic TFDs for practical time-frequency analysis. The separable kernel TFDs, designed in this way, are shown to best resolve closely-spaced components for various classes of synthetic and real-life signals that we have analysed.
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Hussain, Zahir M. "Adaptive instantaneous frequency estimation: Techniques and algorithms." Thesis, Queensland University of Technology, 2002. https://eprints.qut.edu.au/36137/7/36137_Digitised%20Thesis.pdf.
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This thesis deals with the problem of the instantaneous frequency (IF) estimation of sinusoidal signals. This topic plays significant role in signal processing and communications.
Depending on the type of the signal, two major approaches are considered. For IF estimation of single-tone or digitally-modulated sinusoidal signals (like frequency shift keying signals) the approach of digital phase-locked loops (DPLLs) is considered, and this is Part-I of this thesis. For FM signals the approach of time-frequency analysis is considered, and this is Part-II of the thesis.
In part-I we have utilized sinusoidal DPLLs with non-uniform sampling scheme as this type is widely used in communication systems. The digital tanlock loop (DTL) has introduced significant advantages over other existing DPLLs. In the last 10 years many efforts have been made to improve DTL performance. However, this loop and all of its modifications utilizes Hilbert transformer (HT) to produce a signal-independent 90-degree phase-shifted version of the input signal. Hilbert transformer can be realized approximately using a finite impulse response (FIR) digital filter. This realization introduces further complexity in the loop in addition to approximations and frequency limitations on the input signal. We have tried to avoid practical difficulties associated with the conventional tanlock scheme while keeping its advantages. A time-delay is utilized in the tanlock scheme of DTL to produce a signal-dependent phase shift. This gave rise to the time-delay digital tanlock loop (TDTL). Fixed point theorems are used to analyze the behavior of the new loop. As such TDTL combines the two major approaches in DPLLs: the non-linear approach of sinusoidal DPLL based on fixed point analysis, and the linear tanlock approach based on the arctan phase detection. TDTL preserves the main advantages of the DTL despite its reduced structure. An application of TDTL in FSK demodulation is also considered. This idea of replacing HT by a time-delay may be of interest in other signal processing systems. Hence we have analyzed and compared the behaviors of the HT and the time-delay in the presence of additive Gaussian noise.
Based on the above analysis, the behavior of the first and second-order TDTLs has been analyzed in additive Gaussian noise.
Since DPLLs need time for locking, they are normally not efficient in tracking the continuously changing frequencies of non-stationary signals, i.e. signals with time-varying spectra. Nonstationary signals are of importance in synthetic and real life applications. An example is the frequency-modulated (FM) signals widely used in communication systems. Part-II of this thesis is dedicated for the IF estimation of non-stationary signals. For such signals the classical spectral techniques break down, due to the time-varying nature of their spectra, and more advanced techniques should be utilized.
For the purpose of instantaneous frequency estimation of non-stationary signals there are two major approaches: parametric and non-parametric. We chose the non-parametric approach which is based on time-frequency analysis. This approach is computationally less expensive and more effective in dealing with multicomponent signals, which are the main aim of this part of the thesis.
A time-frequency distribution (TFD) of a signal is a two-dimensional transformation of the signal to the time-frequency domain. Multicomponent signals can be identified by multiple energy peaks in the time-frequency domain. Many real life and synthetic signals are of multicomponent nature and there is little in the literature concerning IF estimation of such signals. This is why we have concentrated on multicomponent signals in Part-H.
An adaptive algorithm for IF estimation using the quadratic time-frequency distributions has been analyzed. A class of time-frequency distributions that are more suitable for this purpose has been proposed. The kernels of this class are time-only or one-dimensional, rather than the time-lag (two-dimensional) kernels. Hence this class has been named as the T -class. If the parameters of these TFDs are properly chosen, they are more efficient than the existing fixed-kernel TFDs in terms of resolution (energy concentration around the IF) and artifacts reduction. The T-distributions has been used in the IF adaptive algorithm and proved to be efficient in tracking rapidly changing frequencies. They also enables direct amplitude estimation for the components of a multicomponent
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Shang, Lei, and lei shang@ieee org. "Modelling of Mobile Fading Channels with Fading Mitigation Techniques." RMIT University. Electrical and Computer Engineering, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20061222.113303.
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This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems.
Book chapters on the topic "Time-frequency distribution (TFD)"
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Liu, Ruolun, Xueqin Zhang, and Rui Huang. "A System-of-Systems Perspective on Frequency Estimation: Time-Frequency Distribution of Multiple LFM Signals." In Systems of Systems - Engineering, Modeling, Simulation and Analysis [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.95894.
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This chapter provides a System-of-Systems (SoS) perspective on a study of frequency estimation of signals with a focus on Linear Frequency Modulation (LFM) signals. This chapter describes an SoS approach for frequency estimation using Chirplet Transform (CT), Hough Transform (HT), and the Short Time Fourier Transform (STFT) with filtering viewpoint. The filtering viewpoint employs the filter impulse response length to obtain the best time-frequency concentration for accurate estimation of a signal frequency. The optimum impulse response length can be found by varying the length of the filter impulse response and observe the changing in the time-frequency distribution (TFD). The chapter shows that when the length of the impulse response becomes longer, the time-frequency concentration in TFD increases first and then decreases.
Conference papers on the topic "Time-frequency distribution (TFD)"
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Liu, Libin, and Ming J. Zuo. "Copula-Based Time-Frequency Distribution Analysis for Planetary Gearbox Fault Detection." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-68060.
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Linear and bilinear time-frequency distributions (TFDs) have been employed in planetary gearbox fault diagnosis. For linear TFDs, there is a trade-off between the time localization and frequency resolution and the spectrogram may not have correct energy marginals. For bilinear TFDs, they cannot be interpreted as an energy distribution because of the existence of possible negative values even though they are designed for energy density representation. To overcome these shortcomings, TFDs based on copula theory have been reported in the literature. In this paper, we analyze two simulated data sets using linear TFD and copula-based TFD. The results show that the constructed copula-based TFD has desirable properties of being positive, free from cross-term interference, having high time-frequency resolution and matching well with true marginals. The copula-based TFD is also able to locate fault-induced impulses by vertical lines over a certain frequency range in the time-frequency domain. Consequently, this study confirms the advantages of the copula-based TFD as an energy distribution and its capability in fault detection for planetary gearboxes.
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Tu, Xiaotong, Yue Hu, and Fucai Li. "Current-Aided Time-Frequency Analysis of Vibration Signals for Gearbox Fault Diagnosis." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85550.
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Vibration monitoring is an effective method for mechanical fault diagnosis. Wind turbines usually operated under varying-speed condition. Time-frequency analysis (TFA) is a reliable technique to handle such kind of nonstationary signal. In this paper, a new scheme, called current-aided TFA, is proposed to diagnose the planetary gearbox. This new technique acquires necessary information required by TFA from a current signal. The current signal is firstly used to estimate the rotating speed of the shaft. These parameters are applied to the demodulation transform to obtain a rough time-frequency distribution (TFD). Finally, the synchrosqueezing method further enhances the concentration of the obtained TFD. The validation and application of the proposed method are presented by a simulated signal and a vibration signal captured from a test rig.
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Pan, Min-chun. "Mechanical Noise Identification Using Time-Frequency Representations." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21005.
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Abstract Three computation schemes of time-frequency representations (TFRs) have been developed and implemented to identify different components of mechanical noise originated from the transmission system of electrical vehicles. This study explores the close relationships between three TFRs, i.e. the spectrogram based on windowed Fourier transform (WFT), the Wigner-Ville distribution (WVD), and the smoothed WVD (SWVD). One main purpose is to pursue the efficiency of computing the SWVD of a dynamic signature. The revised scheme can tremendously reduce the computation time to a scale of around 1/90, compared with the original scheme. To assess the validation of these TFR schemes, firstly, four synthetic signals are designed and processed. Secondly, the developed TFRs are applied to distinguish different spectral components of transmission noise, and identify their sources. This study takes an electrical scooter with a continuous velocity transmission (CVT) system as a test bench. The CVT-belt noise, helical-gear whine noise, and fan noise can be clearly identified via the processing of the TFRs. These obtained conclusions can be used as references for machine element modification to improve annoying noise.
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Hettel, Matthias, Peter Habisreuther, Horst Bu¨chner, Henning Bockhorn, and Nikolaos Zarzalis. "URANS-Modelling of Flame Transfer Functions of Turbulent Premixed Jet Flames." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53808.
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The understanding of the formation of self excited pressure oscillations in technical combustion systems depends on the knowledge of the dynamical behaviour of the flame used. As an important mechanism driving these combustion instabilities the formation and reaction of coherent large-scale ring-vortices has been indentified. The phenomenon is investigated with numerical simulations using “Unsteady Reynolds-Averaged Navier-Stokes” (URANS)-methods, applying the k-ε turbulence model and a “Turbulent-Flamespeed-Closure” (TFC) combustion model. Firstly, a premixed turbulent axial methane jet flame with a thermal load of 40 kW was calculated using steady-state flow conditions. The axial distibutions of the measured radiation of OH-radicals and the calculated reaction rate show good agreement, if the turbulent burning velocity is reduced versus the original formulation. The axial positions of the maxima of the curves coincide and are applied to define a characteristic overall time delay. Secondly, a pulsed flame with a forcing frequency of 100 Hz was calculated. An additional transport equation for the residence time of fuel was solved. The analysis of the distribution of the residence time showed, that the characteristic overall time delay of the steady-state flame is a good approximation for the overall time delay of the pulsed flame. Thirdly, the flame frequency response of the pulsed flame was calculated up to frequencies of 200 Hz. For the calculation with reduced burning velocity the phase angle function of the flame coincides with the measurement and shows the typical behaviour of an ideal idle-time model.
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Klein, Marvin, Niels Portzgen, Munendra S. Tomar, Martin Fingerhut, and Homayoon Ansari. "Sizing Stress Corrosion Cracking Using Laser Ultrasonics." In 2008 7th International Pipeline Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ipc2008-64468.
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Managing Stress Corrosion Cracking (SCC) damaged pipe has been a formidable challenge to the pipeline industry. Development of a practical solution for measurement and evaluation of SCC has been marred by the complexity of crack shapes, their distribution within a crack colony, and the lack of non-destructive technology capable of reliably measuring the crack depths. Laser Ultrasonics is an inspection technology wherein lasers are used for generation and detection of ultrasonic waves in the pipeline steel to be inspected. Unlike conventional ultrasonic testing, Laser Ultrasonics has a large frequency bandwidth and a tiny (∼0.5mm) footprint. These characteristics make it ideally suited for application as a depth sizing tool for closely-spaced cracks in a colony. It has been conclusively proved that laser ultrasonic inspection using the time of flight diffraction (TOFD) technique can reliably and accurately measure the depth of naturally occurring SCC and potentially other cracks and seam weld anomalies. This presentation describes the results of this co-sponsored project, including recent full scale demonstrations where a laser ultrasonic measurement subsystem has been built onto a prototype scanner.
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Singh, Maniesh, Parmanand Dhermeshwar Thakur, Mariam N. M. Al Baloushi, Haitham Ali Al Saadi, Maisoon M. Al Mansoori, Ahmed S. Al Mesafri, Saif Al Arfi, et al. "Real-Time 3D Ultra Deep Directional Electromagnetic LWD Inversions: An Innovative Approach for Geosteering and Geomapping Water Slumping Movement Around Sub-Seismic Fault, Onshore Abu Dhabi." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207478-ms.
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Abstract An Ultra-Deep Directional Electromagnetic LWD Resistivity (UDDE) tool was deployed in a mature Lower Cretaceous carbonate reservoir to map injection water movement. These thick carbonate reservoirs experience injection water preferentially travelling laterally at the top of the reservoir. The water held above oil by negative capillary forces slumps quickly, leading to increasing water cut, eventually killing the natural lift horizontal producing well. Real time 3D and 1D inversions provided important accurate mapping of the non-uniform water fronts and reservoir boundaries, providing insights into reservoir architecture and water movement. The candidate well is located in an area of significant uncertainty regarding fluid distribution and structural elements like sub-seismic faults etc. Pre-well 1D inversion results indicated that the water slumping front away from wellbore can be mapped within a vertical radius of 60-100 ft TVD. However, 1D inversion is not accurate where steeply dipping or discontinuous formations exist due to the presence of faults and is expected to impact well placement, mapping water fronts / formation boundaries and long-term oil recovery. Therefore in the real time, full 3D and 1D inversions of the Ultra-Deep EM data were run to provide high quality reservoir imaging in this complex geometrical setting and deliver improved reservoir fluid distribution and structure mapping. The pre-well inversion modeling optimized the frequency and transmitter-receiver spacing of the UDDE tool. The bottom hole assembly (BHA) configuration also included conventional LWD tools such as Neutron-Density, propagation Resistivity and Gamma Ray. Multiple 3D inversion datasets were processed in real-time using different depths of inversion ranging from 50 ft up to 120 ft depth. The 3D inversion results during the real-time drilling operation detected the non-uniform waterfront boundaries and water slumping up to 80 ft TVD above the wellbore using a slimhole (4¾″) tool. An interpreted sub-seismic down-thrown fault was mapped which controlled the non-uniform slumping fluid distribution, causing the water front to approach closest to the wellbore in this location. This suggests that the fault zone is open and provides a degree of increased permeability around the plane of the fault. The real-time 3D inversion, 1D shallow and 1D deep inversion results showed comparable structural imaging despite being inverted independently of each other. These results permitted updates to the static / dynamic reservoir models and an optimization of the completion design, to delay the water influx and thereby sustain oil production for a longer period of time. Field wide implementation of the UDDE tool and its advanced technology with improved 1D and 3D inversion results will enhance the quality of realtime geosteering, mapping and updating of reservoir models which have challenging water slumping fronts and structural variations. This will enable improvment in well locations, their spacing and finally allowing the proactive design of smart completions for enhanced oil production and improved recovery factors.
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Fares, Wael, Islam Moustafa, Ali Al Felasi, Hocine Khemissa, Omar Al Mutwali, Freddy Gutierrez, Nigel Clegg, Alban Duriez, and Ahmet Aki. "An Advanced Ultra-Deep Resistivity Mapping Sensor Reduced Reservoir Uncertainty and Eliminated the Need for a Pilot Hole for the First Time; A Case Study from Offshore Abu Dhabi." In SPE Middle East Oil & Gas Show and Conference. SPE, 2021. http://dx.doi.org/10.2118/204813-ms.
Full textAbstract:
Abstract The high reservoir uncertainty, due to the lateral distribution of fluids, results in variable water saturation, which is very challenging in drilling horizontal wells. In order to reduce uncertainty, the plan was to drill a pilot hole to evaluate the target zones and plan horizontal sections based on the information gained. To investigate the possibility of avoiding pilot holes in the future, an advanced ultra-deep resistivity mapping sensor was deployed to map the mature reservoirs, to identify formation and fluid boundaries early before penetrating them, avoiding the need for pilot holes. Prewell inversion modeling was conducted to optimize the spacing and firing frequency selection and to facilitate an early real-time geostopping decision. The plan was to run the ultra-deep resistivity mapping sensor in conjunction with shallow propagation resistivity, density, and neutron porosity tools while drilling the 8 ½-in. landing section. The real-time ultra-deep resistivity mapping inversion was run using a depth of inversion up to 120 ft., to be able to detect the reservoir early and evaluate the predicted reservoir resistivity. This would allow optimization of any geostopping decision. The ultra-deep resistivity mapping sensor delivered accurate mapping of low resistivity zones up to 85 ft. TVD away from the wellbore in a challenging low resistivity environment. The real-time ultra-deep resistivity mapping inversion enabled the prediction of resistivity values in target zones prior to entering the reservoir; values which were later crosschecked against open-hole logs for validation. The results enabled identification of the optimal geostopping point in the 8 ½-in. section, enabling up to seven rig days to be saved in the future by eliminating a pilot hole. In addition this would eliminate the risk of setting a whipstock at high inclination with the subsequent impact on milling operations. In specific cases, this minimizes drilling risks in unknown/high reservoir pressure zones by improving early detection of formation tops. Plans were modified for a nearby future well and the pilot-hole phase was eliminated because of the confidence provided by these results. Deployment of the ultra-deep resistivity mapping sensor in these mature carbonate reservoirs may reduce the uncertainty associated with fluid migration. In addition, use of the tool can facilitate precise geosteering to maintain distance from fluid boundaries in thick reservoirs. Furthermore, due to the depths of investigation possible with these tools, it will help enable the mapping of nearby reservoirs for future development. Further multi-disciplinary studies remain desirable using existing standard log data to validate the effectiveness of this concept for different fields and reservoirs.