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.

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.

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.