Instantaneous phase inversion based on an unwrapping algorithm

The full-waveform inversion method is a high-precision inversion method based on the minimization of the misfit between the synthetic seismograms and the observed data.However,this method suffers from cycle skipping in the time domain or phase wrapping in the frequency because of the inaccurate initial velocity or the lack of low-frequency information.furthermore,the object scale of inversion is affected by the observation system and wavelet bandwidth,the inversion for large-scale structures is a strongly nonlinear problem that is considerably difficult to solve.In this study,we modify the unwrapping algorithm to obtain accurate unwrapped instantaneous phase,then using this phase conducts the inversion for reducing the strong nonlinearity.The normal instantaneous phases are measured as modulo 2π,leading the loss of true phase information.The path integral algorithm can be used to unwrap the instantaneous phase of the seismograms having time series and onedimensional(1 D)signal characteristics.However,the unwrapped phase is easily affected by the numerical simulation and phase calculations,resulting in the low resolution of inversion parameters.To increase the noise resistance and ensure the inversion accuracy,we present an improved unwrapping method by adding an envelope into the path integral unwrapping algorithm for restricting the phase mutation points,getting accurate instantaneous phase.The objective function constructed by unwrapping instantaneous phase is less affected by the local minimum,thereby making it suitable for full-waveform inversion.Further,the corresponding instantaneous phase inversion formulas are provided.Using the improved algorithm,we can invert the low-wavenumber components of the underneath structure and ensure the accuracy of the inverted velocity.Finally,the numerical tests of the 2 D Marmousi model and 3 D SEG/EAGE salt model prove the accuracy of the proposed algorithm and the ability to restore largescale low-wavenumber structures,respectively.

Extrapolate well logs based on the constrained interpolation algorithm

Based on a detailed analysis of differences between seismic data and well logs, we discuss the problem of matching seismic traces and well logs and present a new matching method based on event search in instantaneous phase which greatly improves seismic resolution. The method is based on flattening events in instantaneous phase to compare the seismic traces to the well log traces with the same phase. We calculate the coefficients using the singular value decomposition method to extrapolate the well logs. As a result, the events in the seismic profile are continuous and match well with well logs. We apply this method to the Mao-2 well in Daqing Oilfield with good results.

Properties of an improved Gabor wavelet transform and its applications to seismic signal processing and interpretation

This paper presents an analytical study of the complete transform of improved Gabor wavelets （IGWs）, and discusses its application to the processing and interpretation of seismic signals. The complete Gabor wavelet transform has the following properties. First, unlike the conventional transform, the improved Gabor wavelet transform （IGWT） maps time domain signals to the time-frequency domain instead of the time-scale domain. Second, the IGW＇s dominant frequency is fixed, so the transform can perform signal frequency division, where the dominant frequency components of the extracted sub-band signal carry essentially the same information as the corresponding components of the original signal, and the sub- band signal bandwidth can be regulated effectively by the transform＇s resolution factor. Third, a time-frequency filter consisting of an IGWT and its inverse transform can accurately locate target areas in the time-frequency field and perform filtering in a given time-frequency range. The complete IGW transform＇s properties are investigated using simulation experiments and test cases, showing positive results for seismic signal processing and interpretation, such as enhancing seismic signal resolution, permitting signal frequency division, and allowing small faults to be identified.

Single-ended Time Domain Fault Location Based on Transient Signal Measurements of Transmission Lines

Precise fault location plays an important role in the reliability of modern power systems.With the in-creasing penetration of renewable energy sources,the power system experiences a decrease in system inertia and alterations in steady-state characteristics following a fault occurrence.Most existing single-ended phasor domain methods assume a certain impedance of the remote-end system or consistent current phases at both ends.These problems present challenges to the applicability of con-ventional phasor-domain location methods.This paper presents a novel single-ended time domain fault location method for single-phase-to-ground faults,one which fully considers the distributed parameters of the line model.The fitting of transient signals in the time domain is real-ized to extract the instantaneous amplitude and phase.Then,to eliminate the error caused by assumptions of lumped series resistance in the Bergeron model,an im-proved numerical derivation is presented for the distrib-uted parameter line model.The instantaneous symmet-rical components are extracted for decoupling and inverse transformation of three-phase recording data.Based on the above,the equation of instantaneous phase constraint is established to effectively identify the fault location.The proposed location method reduces the negative effects of fault resistance and the uncertainty of remote end pa-rameters when relying on one-terminal data for localiza-tion.Additionally,the proposed fault analysis methods have the ability to adapt to transient processes in power systems.Through comparisons with existing methods in three different systems,the fault position is correctly identified within an error of 1%.Also,the results are not affected by sampling rates,data windows,fault inception angles,and load conditions. Index Terms—Fault location,distributed parameter line model,transient signal,renewable energy,instantaneous phase.

Vibration-based synchronous sampling and its application in wind-turbine drive-train-condition monitoring

Utilizing shaft-speed information to analyse vibration signals is an important method for fault diagnosis and condition monitoring of rotating machineries,especially for those running at variable speeds.However,in many cases,shaft-speed information is not always available,for a variety of reasons.Fortunately,in most of the measurements,the shaft-speed information is embedded in the vibration response in many different forms,such as in the format of the fundamental shaft-rotation-frequency response and its harmonics,and the gear-meshing-frequency response and its harmonics,etc.Proper signal processing can be used to extract the shaft instantaneous speed from the measured vibration responses.In existing instantaneous shaft-speed-identification methods,a narrow-bandpass filtering technique is used explicitly or implicitly.In a complex gearbox system,such as that used in a wind turbine,the gear-meshing-response component could be modulated by many other shaft speeds,due to the configuration of the gearbox or due to the existence of component damage.As a result,it is very difficult to isolate a single vibration-response component for instantaneous shaft-speed detection.In this paper,an innovative approach is presented.The instantaneous shaft speed is extracted based on maxima tracking from the vibration-response spectrogram.A numerical integration scheme is employed to obtain the shaft instantaneous phase.Digital-domain synchronous resampling is then applied to the vibration data by using the instantaneous phase information.Due to the nature of noise suppression in the numerical integration,the accuracy of synchronous sampling is greatly improved.This proposed approach demonstrates the feasibility and engineering applicability through a controlled laboratory test case and two field wind-turbine cases.More detailed results and conclusions of this research are presented at the end of this paper.

Unintentional modulation evaluation in time domain and frequency domain

With the development of wireless communication technology, the electromagnetic environment has become more and more complex. Conventional signal identification methods are difficult to accurately identify illegal devices. However, electromagnetic signals have an unavoidable device-specific characteristic unintentionally generated by a transmitter, appearing in the form of an Un Intentional Modulation(UIM), namely Radio Frequency Fingerprint(RFF). RFFs can be used to uniquely identify an emitter to match a received signal with its source. In this paper, the authors propose a novel RFF scheme to separate UIM part from the original signals from the time and frequency domain, and then utilize non-Gaussian measuring tools to extract a set of dimensionreduced secondary features. Additionally, Singular Value Reconstruction(SVR) is developed to extract UIM in the frequency spectrum. In time domain, a curve-fitting residual method is proposed to extract the UIM on the estimated instantaneous phase based on Maximum Likelihood Estimator(MLE). Various aspects of the proposed method are evaluated, including identification accuracy under various Signal-to-Noise Ratio(SNR) conditions, energy relationships between the UIM and the whole signal, and sensitivity to training set size. Compared with other methods, experimental results based on real-world signals prove that the proposed method has remarkable performance and high practicability.

Modeling and simulation methods of sea clutter based on measured data

The modeling and simulation of sea clutter are important in detecting radar targets in sea backgrounds.Because the nonstationary property of sea clutter is ignored in traditional statistical models,a new method based on measured sea clutter is proposed in this paper.First,we convert the measured sea clutter data under different sea conditions[xI,xQ]into real amplitude SM.Instantaneous phaseθis then extracted from the coherent radar’s baseband data.Second,we select a candidate statistic model and estimate its parameters based on SM by utilizing maximum likelihood estimation.Finally,we generate random series A using corresponding random data generator and then add instantaneous phaseθinto A,i.e.,y=Ae^(jθ),to obtain simulated sea clutter series.Through a comparison of simulated sea clutter and measured sea clutter data via histogram,the validity of the proposed method is proved.

Ideal proportional navigation for exoatmospheric interception

Ideal proportional navigation （IPN） is a natural choice for exoatmospheric interception for its mighty capture capability and ease of implementation. The closed-form solution of two- dimensional ideal proportional navigation was conducted in previous public literature, whereas the practical interception happens in the three-dimensional space. A novel set of relative dynamic equations is adopted in this paper, which is with the advantage of decoupling relative motion in the instantaneous rotation plane of the line of sight from the rotation of this plane. The dimension-reduced IPN is constructed in this instantaneous plane, which functions as a three-dimensional guidance law. The trajectory features of dimension-reduced IPN are explored, and the capture regions of dimension-reduced IPN with limited acceleration against nonmaneuvering and maneuvering targets are analyzed by using phase plane method. It is proved that the capture capability of IPN is much stronger than true proportional navigation （TPN）, no matter the target maneuvers or not. Finally, simulation results indicate that IPN is more effective than TPN in exoatmospheric interception scenarios.