Fault Period Research Articles

Fault Current Limiting Operations of Three-Phase Transformer Type SFCL Using Two Common Connection Points Between Secondary Windings

Three-phase transformer type superconducting fault current limiter (SFCL) using two common connection points between secondary windings, which consisted of three-phase transformer windings wound on three legs of E-I iron core and two/three superconducting modules (SCMs), were suggested and its fault current limiting operations according to ground-fault types were analyzed. To verify the effective operation of the three-phase transformer type SFCL using two common connection points between secondary windings, the unsymmetrical ground and the symmetrical ground faults were applied into three-phase power simulated system with the suggested SFCL. For the comparison, the ground faults were generated into three-phase transformer type SFCL with two/three SCMs. Through analysis on the test results, the SFCL with two SCMs was confirmed to have no different fault current limiting operation from the SFCL with three SCMs. The structure of E-I iron core with three magnetically coupled legs and the constitution of three secondary windings with two common connection points were analyzed to be contributed to the same fault current limiting operation. Furthermore, the power consumption and the joule energy of the SCMs comprising both the SFCL with two SCMs and the SFCL with three SCMs during the fault period had shown to be almost the same except for the transient period due to the quench time difference in case of the single-line ground fault.

Comparison between saturated-iron core and shielded-iron core superconducting fault current limiters on recloser-fuse coordination of radial distribution systems connected with distributed generation

Abstract Recently, distributed generators (DGs) are being largely amalgamated with radial distribution systems because of their positive impacts on these systems such as voltage profile improvement and power loss minimization. However, if this integration is not well-planned, it can lead to serious problems in the protection devices. One of these problems is the recloser-fuse miscoordination. This paper presents an effective solution to the recloser-fuse miscoordination due to DGs integration with RDS. The proposed approach is based on suppressing the DG current during fault period so that the contribution of DG to the fault current becomes minimal. Two types of superconducting fault current limiters (SFCLs) namely, saturated iron-core and shielded iron-core SFCLs are studied and a comparison between their performance is presented. The proposed solution was implemented on IEEE 33-bus RDS. All simulation studies are performed on MATLAB script. The simulation results illustrated that saturated iron-core SFCL could not recover recloser-fuse coordination in some of the studied cases. However, shielded iron-core SFCL could successfully restore the recloser-fuse coordination in all the studied cases. This shows that shielded iron-core SFCL is preferred in solving recloser-fuse miscoordination.

Experimental and Simulation Study of Resistive Helical HTS Fault Current Limiters: Quench and Recovery Characteristics

Resistive type fault current limiters (SFCLs) have attracted lots of attention from research interests and engineering applications, due to their self-triggering, fast and effective fault current limitation ability. Fast recovery of SFCL after quench is highly attractive, yet still remains challenge when recover with load compared to recovering without load. We investigated the dependence of recovery time of a helical SFCL coil on the ratio of prospective current over critical current I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pros</sub> /I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> . A multilayer simulation model was built in MATLAB/Simulink to investigate the electro-thermal behavior of SFCL coil during a fault and recovery period, and the model was validated by experimental results. Quench simulations were carried out under different I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pros</sub> /I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> , ranging from 15 to 119 and in different recovery conditions including recovery with load condition and recovery without load condition, while keeping the fault duration of 100 ms. We observed that the SFCL coil reached 85 K and 195 K at the time when the fault was cleared, in the quench tests with I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pros</sub> /I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> = 15 and 119, respectively. SFCL coil recovered without load in 0.5 s to 10 s, depending on the ratio of I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pros</sub> /I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> .

Adaptive maximum second-order cyclostationarity blind deconvolution and its application for locomotive bearing fault diagnosis

Maximum second-order cyclostationarity blind deconvolution (CYCBD) outperforms other deconvolution methods in retrieving the weak periodic impulses related to bearing incipient faults. However, the main challenge in the practical application of CYCBD is how to set several key parameters appropriately, the uppermost of which is the targeted cyclic frequency or fault period. It may attribute to the fact that the advantage of CYCBD is greatly compromised by the provided period. To overcome the above limitations, an adaptive CYCBD (ACYCBD) is presented in this article. In the proposed method, a powerful tool, envelope harmonic product spectrum (EHPS), is tailored to estimate the true cyclic frequency or period precisely. Then, the estimated result instead of a coarsely provided value is regarded as the targeted cyclic frequency. Furthermore, in the presence of heavy energy harmonics or strong external noise, EHPS still has strong robustness in the fault period identification. Compared with the original CYCBD, ACYCBD can extract the weak impulses submerged in the raw vibration signal without any prior information about the period. Finally, the effectiveness and advantages of ACYCBD are revealed by employing it on the synthesized signals and experimental data collected from a locomotive bearing test rig.

Periodicity-enhanced sparse representation for rolling bearing incipient fault detection

Incipient fault detection of rolling bearings is a challenging task since the weak fault features are disturbed by heavy background noise. This paper develops a periodicity-enhanced sparse representation method to address this issue. Firstly, periodicity-enhanced basis pursuit denoising (PBPD) is proposed by the theoretical derivation. Fault proportion is defined to quantify the single fault severity of sparse signals, then a periodicity-decision criterion for determining the optimal potential fault period is designed to periodically filter the last sparse signal. Secondly, the suitable linear transformation for PBPD is investigated in comparison and maximal overlapping discrete wavelet packet transform is adopted eventually. Thirdly, adaptive selection strategies are developed for the key parameters of PBPD. Simulations and experimental verifications demonstrate PBPD’s excellent performance in rolling bearing incipient fault detection.

Research on gearbox composite fault diagnosis based on improved local mean decomposition

In order to solve the problem of modal aliasing in the processing of complex fault signal with background noise by local mean decomposition(LMD), and the difficulty of extracting and identifying the weak fault feature frequency in the complex fault signal, an improved LMD method is proposed. LMD can adaptively decompose a non-stationary, multi-component signal into a series of instantaneous frequency product functions with physical significance. However, under the influence of noise, the process of LMD will appear modal aliasing, resulting in missed diagnosis and misdiagnosis. In order to solve this problem, the maximum correlation kurtosis deconvolution is proposed to improve the LMD. Firstly, according to the multi-point kurtosis spectrum, the component of fault period contained in fault signal is obtained. According to the fault period, the maximum correlation kurtosis deconvolution is used to denoise the fault signal. Then, the denoised signal is decomposed into a series of components containing fault characteristics by means of LMD. Finally, the component with high correlation is selected for envelope spectrum analysis to extract the component. The characteristic frequencies of different faults and the types of faults are identified. The effectiveness of the proposed method is verified by analyzing the vibration signals of the broken gear-wear composite fault of the gears in the actual gearbox. Compared with the improved empirical mode decomposition method, the superiority of the proposed method is further highlighted.

An Optimal Parameter Selection Method for MOMEDA Based on EHNR and Its Spectral Entropy.

As a vital component widely used in the industrial production field, rolling bearings work under complicated working conditions and are prone to failure, which will affect the normal operation of the whole mechanical system. Therefore, it is essential to conduct a health assessment of the rolling bearing. In recent years, Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA) is applied to the fault feature extraction for rolling bearings. However, the algorithm still has the following problems: (1) The selection of fault period T depends on prior knowledge. (2) The accuracy of signal denoising is affected by filter length L. To solve the limitations, an improved MOMEDA (IMOMEDA) method is proposed in this paper. Firstly, the envelope harmonic-to-noise ratio (EHNR) spectrum is adopted to estimate the fault period of MOMEDA. Then, the improved grid search method with EHNR spectral entropy as the objective function is constructed to calculate the optimal filter length used in the MOMEDA. Finally, a feature extraction method based on the improved MOMEDA (IMOMEDA) and Teager-Kaiser energy operator (TKEO) is applied in the field of rolling bearing fault diagnosis. The effectiveness and generalization performance of the proposed method is verified through comparison experiment with three data sets.

High Impedance Fault Identification in TCSC-Compensated Power Transmission Lines

The conventional distance relaying scheme performs poorly under the presence of Thyristors-controlled series capacitors “TCSC”, and during the high impedance fault “HIF”. TCSC provide a variable impedance during an internal/external fault and HIF is undetectable by the conventional overcurrent relaying due to low-current amplitude with non-linear behavior. Therefore, this paper presents a new Method for identifying the high impedance fault in TCSC-compensated transmission line. It is use the square error ration of the current signals during the fault period and current signals during the safe operating period for extracting the fault. The cumulative sum is being used for enlarging the fault features and then output index is obtained in order to perform the high impedance fault. The proposed method has been tested under different fault circumstances such as multiple fault locations, and multiple fault inception time. Moreover, fault happened nearby the terminal, power flow change, and faults in the presence of noise are also being considered. The test results have shown that the proposed method is good in term of time response, and then it is more appropriate for high impedance fault in TCSC-compensated power line.

A novel blind deconvolution based on sparse subspace recoding for condition monitoring of wind turbine gearbox

Blind deconvolution (BD) methods have proven to be effective tools for condition monitoring of gearbox. Nevertheless, due to the severe operating environment and complex structure in the wind turbine (WT) gearbox, the prior knowledge of fault period is hard to obtain accurately, which results in a challenge to the traditional BD algorithms that exceedingly relies on this information. Motivated by this limitation, a novel BD approach based on sparse subspace recoding (SSRBD) is proposed for the condition monitoring of WT gearbox. In this work, singular value decomposition is initially introduced to convert the raw signal from the input space to feature subspaces. The coefficient of variation is then constructed to guide the choice of inverse filter length. Successively, an iterative Mahalanobis distance is designed to cluster the sensitive subspace with rich fault information. Finally, build upon the robust principal component analysis, the objective features are further separated by means of sparse recoding. The effectiveness and robustness of the proposed SSRBD are validated through several comparative analyses and experimental cases. The consequences demonstrate that the proposed approach overcomes the dependence of prior information and domain knowledge, while extracts the fault feature more effectively than the state-of-the-art methods.

Period-oriented multi-hierarchy deconvolution and its application for bearing fault diagnosis

Deconvolution methods have been proven to be effective tools to extract excitation sources from the noisy measured signal. However, its application is confined by the extraction of incomplete information. To tackle this problem, a new deconvolution method, named period-oriented multi-hierarchy deconvolution (POMHD) is proposed in this paper. Various filters are designed adaptively by the iterative algorithm to update the filter coefficient using the harmonic-to-noise ratio as the deconvolution orientation. Additionally, a novel index, called normalized proportion of harmonics, is proposed as the evaluation criteria for the fault feature. Based on upon, a harmonics proportion diagram is constructed for the diagnostic decisions. The new deconvolution method overcomes the disadvantages of the traditional methods. More importantly, without an accurate fault period as the prior knowledge, the proposed POMHD can simultaneously extract multiple latent fault components by using the adaptive filter and intuitively present different fault information in one diagram. Finally, the simulated and experimental data which includes the signals collected from bearings with both single faults and compound faults is used to evaluate the new method. The results validate the feasibility and robustness of the proposed POMHD.

Faulty Phase Identification for Transmission Line with Metal Oxide Varistor-protected Series Compensator

The nonlinear operation of metal oxide varistor (MOV)-protected series compensator in transmission lines introduces complications into fault detection approaches. The accuracy of a conventional fault detection schemes is adversely affected by continuous change of the system impedance and load current at the point of a series compensation unit. Thus, this study suggests a method for detecting the faulted phase in MOV-protected series-compensated transmission lines. Primarily, the fault feature is identified using the covariance coefficients of the current samples during the fault period and the current samples during the pre-fault period. Furthermore, a convenience fault detection index is established by applying the cumulative sum technique. Extensive validation through different fault circumstances is accomplished, including different fault positions, resistances, and inception times. The experimental results show that the proposed method performs well with high resistance or impedance faults, faults in noisy conditions, and close-in and far-end faults. The proposed method is simple and efficient for faulty phase detection in MOV-protected series-compensated transmission lines.

Relay vibration protection simulation experimental platform based on signal reconstruction of MATLAB software

Abstract For conceptual analysis of the principle of relay vibration protection, this article establishes the simulation system model of directional current protection in MATLAB/Simulink environment through the protection algorithm. Various outcomes have been achieved for the proposed approach during the faulty conditions. The outcomes obtained during the fault period reveals that the waveform of three-phase current changes greatly, and the amplitude of three-phase current at power supply side increases sharply. After 0.02s signal acquisition and processing, the action signal acts after 0.07s, and the fault is removed. In case of two-phase short-circuit, two-phase grounding short-circuit and other faults, the fault can be removed smoothly after signal acquisition and processing. In this paper, the directional current protection simulation system based on microcomputer protection model is built, and the changes of voltage, current and action signal are demonstrated through GUI interface, and analyzed and verified.

Fault Diagnosis of Rolling Bearing based on Permutation Entropy Optimized Maximum Correlation Kurtosis Deconvolution

An improved MCKD algorithm was proposed as an adaptive parameter selection approach. In this method, the optimal filter length of the MCKD algorithm was determined by the maximum permutation entropy value and the optimal fault period of the MCKD algorithm was determined by the maximum kurtosis value. The determined optimal filter length and optimal fault period were verified by simulation signals of the bearing as well as fault experimental signals of the inner and outer rings. Results demonstrate that in early fault diagnosis, the improved MCKD algorithm based on permutation entropy can extract faint characteristic information of early fault of rolling bearing effectively. It can highlight fault pulse signals which are covered by noises and get more ideal results than the minimum entropy deconvolution algorithm.

Effect of Tectonostratigraphic Units in Evolving Aqra Anticline Model

In the current study, a tectonic model for the structure of Aqra Anticline was proposed. The model was dependent on the rock properties, stratigraphic relationships and thickness variations as well as, the model was correlated with other previous studies. The study area is located within the Iraqi Zagros fold/ thrust belt (ZFTB) which represents the northeastern margin of the Arabian Plate. Stratigraphically, the anticline comprises of formations that are deposited between Early Cretaceous to Pliocene periods. These formations are the Sarmord, Qamchuqa, Aqra, Kolosh/Khurmala, Gercus, Pila Spi, Fat'ha, Injana, and the Makdadiya formations. they were deposited during four Tectonostratigraphic Megasequences (TMS). The older TMS contains formations that were deposited prior the development of the Zagros Foreland Basin, whereas the formations of other three Megasequences were deposited within Zagros Foreland Basin. During those times, the foreland basin was divided into three distinct parts. these are fore deep, bulge, and fore-bulge, which were discriminated via listric faults, which played as normal and reverse displacements after and before ophiolite obduction. Some contributions to the tectonostratigraphic model of the area are adopted. They are stages of basin development, determining the time of extension period of the listric faults and detecting the tectonic inversion of these faults. This model is described within the compressional tectonic framework between the Arabian and Eurasian plates.

A weak fault diagnosis scheme for common rail injector based on MGOA-MOMEDA and improved hierarchical dispersion entropy

Aiming at the problem that the common rail injector’s early fault characteristics are very weak and susceptible to random noise and other signal interference, this paper proposes a new common rail injector weak fault diagnosis method based on multipoint optimal minimum entropy deconvolution adjusted based on modified grasshopper optimization algorithm optimization algorithm (MGOA-MOMEDA), improved hierarchical dispersion entropy, and least square support vector machine. First, the fault period T is determined using the multipoint kurtosis spectrum. Through the MGOA optimization algorithm, the optimal filter length L of MOMEDA is obtained adaptively, and the optimal performance filter is used for filter processing. Then, improved hierarchical discrete entropy is used to measure the complexity of the filtered fuel pressure signal to extract weak fault features. Finally, the fault feature vector is input into the LS-SVM multi-classifier to realize the weak fault diagnosis and recognition of the common rail injector. Through experimental verification, the proposed method can effectively achieve the weak fault diagnosis of the common rail injector.

Recent developments on corrosion behaviors of Mg alloys with stacking fault or long period stacking ordered structures

Corrosion is one of the most drawbacks which restricts the wide applications of Mg alloys. In the last decade, the corrosion behaviors of Mg alloys with stacking fault (SF) and/or long period stacking ordered (LPSO) structures have obtained increasing attention. However, the corrosion mechanism of the SF– or LPSO–containing Mg alloys has not been well illustrated and even reverse results have been reported. In this paper, we have reviewed recent reports on corrosion behaviors of SF– or LPSO–containing Mg alloys to better clarify and understand the significance and mechanism. Moreover, some deficiencies are presented and advises are proposed for the development of corrosion resistant Mg alloys with SF or LPSO structures.

Detection and Diagnosis of Multi-Fault for through Silicon Vias in 3D IC

Through silicon via (TSV) is the enabling technology for three-dimensional integrated circuit (3D IC) realization. During the TSV manufacturing process, the TSV inevitably has a multi-fault with both resistive-open and leakage faults. The multi-fault will decrease the reliability of the 3D IC seriously. A method of classifying and diagnosing TSV multi-fault is proposed by combining ring oscillator and least square support vector machine (LSSVM). Firstly, the schmidt trigger (ST) as a TSV test receiver based on the initial ring oscillator test structure is implemented. The parameters such as the oscillation period and duty cycle are measured with the TSV as load. A variety of fault types can be detected by testing the changes of these parameters. For further increase the accuracy of the fault test, the oscillation period and duty cycle of different faults are utilized as the feature vectors set, and the set is trained by LSSVM to obtain the fault diagnosis model. In order to get the optimization parameters of the LSSVM model, the particle swarm optimization (PSO) is adopted. As the problem of PSO is tend to local optimization and premature convergence, it may lead to misjudgment of TSV fault. Based on this, W-PSO that dynamically changes the inertia weight is used to optimize the LSSVM. Finally, experiment results imply that the W-PSO-LSSVM fault diagnosis model has a higher fault diagnosis accuracy rate than the PSO-LSSVM fault diagnosis model.

A Bi-Level Interval Robust Optimization Model for Service Restoration in Flexible Distribution Networks

Soft normally open points (SNOPs) connected to distribution networks are instrumental in maintaining uninterrupted power supply and improving power quality during the fault period. In order to achieve the optimal service restoration scheme, a novel bi-level service restoration model based on the robust optimization method is proposed in this paper. The upper level of the proposed model aims at minimizing the risk of load loss. The switch statuses and range of power transmitted by SNOP terminals can be obtained. In the lower level of the model, the interval robust optimization method is adopted to cope with the uncertainties of DGs and loads. If there are no optimal solutions, the upper level model needs to be solved once more to adjust the network topology. Finally, a test system is established to verify the effectiveness of the proposed model and solution method. The effects of forecasting errors, the DG penetration, and the ratio of single terminal capacity of SNOP to line capacity on the optimization results are analyzed.

Transient Stability and Current Injection Design of Paralleled Current-Controlled VSCs and Virtual Synchronous Generators

With development of power electronic technology, the paralleled current-controlled voltage source converters (CCSs) and virtual synchronous generators (VSGs) system has advantages in providing power and voltage/frequency regulation at the same time in rural area or remote island. However, the paralleled system faces great challenges in safe and stable operation due to their limited thermal capacity and weak anti-disturbance ability, especially during fault periods. This article focuses on transient stability and stability-oriented control design of the paralleled CCS-VSG system. First, mathematical model of the paralleled system is established and then the effect of two kinds of CCSs' current injection angle (active current and reactive current) on VSG's transient stability has been revealed through extended equal area criterion. Based on the theoretical analysis results, transient stability improvement control is put forward by controlling the CCS to track the VSG's frame. Compared with the conditions that only active- or reactive current is provided by the CCS, the system can achieve the best transient performance when the proposed control is adopted. Moreover, the effect of CCS's capacity on transient stability of the VSG has also been discussed. Finally, both Lyapunov's method and simulation/experimental results are provided to validate the correctness of theoretical analysis.

Multi-Port DC-DC and DC-AC Converters for Large-Scale Integration of Renewable Power Generation

Numerous research studies on high capacity DC-DC converters have been put forward in recent years, targeting multi-terminal medium-voltage direct current (MVDC) and high-voltage direct current (HVDC) systems, in which renewable power plants can be integrated at both medium-voltage (MV) and high-voltage (HV) DC and AC terminals; hence, leading to complex hybrid AC-DC systems. Multi-port converters (MPCs) offer the means to promote and accelerate renewable energy and smart grids applications due to their increased control flexibilities. In this paper, a family of MPCs is proposed in order to act as a hybrid hub at critical nodes of complex multi-terminal MVDC and HVDC grids. The proposed MPCs provide several controllable DC voltages from constant or variable DC or AC voltage sources. The theoretical analysis and operation scenarios of the proposed MPC are discussed and validated with the aid of MATLAB-SIMULINK simulations, and further corroborated using experimental results from scale down prototype. Theoretical analysis and discussions, quantitative simulations, and experimental results show that the MPCs offer high degree of control flexibilities during normal operation, including the capacity to reroute active or DC power flow between any arbitrary AC and DC terminals, and through a particular sub-converter with sufficient precision. Critical discussions of the experimental results conclude that the DC fault responses of the MPCs vary with the topology of the converter adopted in the sub-converters. It has been established that a DC fault at high-voltage DC terminal exposes sub-converters 1 and 2 to extremely high currents; therefore, converters with DC fault current control capability are required to decouple the healthy sub-converters from the faulted one and their respective fault dynamics. On the other hand, a DC fault at the low-voltage DC terminal exposes the healthy upper sub-converter to excessive voltage stresses; therefore, sub-converters with bipolar cells, which possess the capacity for controlled operation with variable and reduced DC voltage over wide range are required. In both fault causes, continued operation without interruption to power flow during DC fault is not possible due to excessive over-current or over-voltage during fault period; however, it is possible to minimize the interruption. The above findings and contributions of this work have been further elaborated in the conclusions.