Short-circuit Fault Research Articles

Circuit fault diagnosis for 12-pulse power converter in HL-3 based on Meta Pseudo Labels

The application of deep learning in the field of power electronics fault diagnosis has garnered considerable attention and research interest. In the coil power supply of the HL-3 tokamak device, there exist practical challenges in dealing with fault data from 12-pulse thyristor power converters, including large data volume, variable frequency operation, and sensor noise, among others. To solve these problems, this paper proposes a method that combines wavelet threshold denoising and Meta Pseudo Labels. Firstly, discrete wavelet transform is used to transform the original voltage signals of the 12-pulse thyristor rectifier operating across a wide frequency range into the wavelet domain. Subsequently, a reasonable threshold is employed to filter out high-frequency noise, resulting in the output of wavelet threshold denoising. Then, Meta Pseudo Labels algorithm, an idiographic semi-supervised learning approach, is applied to learn the features of the denoised data, yielding classification models and experimental results. The model identifies three types of states in single thyristor branches of the rectifier circuit, which are normal, short-circuit fault, and open-circuit fault. The experimental results indicate that the accuracy and robustness of the model trained using the Meta Pseudo Labels algorithm outperform those of a convolutional neural network with the same network architecture. Especially, one of the experiments accomplishes a diagnosis accuracy exceeding 90% while training with the whole unlabeled training dataset and only 10% of stratified subsamples from the labeled training dataset.

Application of Static Synchronous Compensator for Improvement of Power System Transient Stability

Transient stability is the power system’s ability to maintain synchronism when exposed to severe disturbances such as loss of generation, rapid load changes, transmission lines tripping, switching operations and faults. Transient instability causes cascading outages, system collapse and economical losses. This study employed static synchronous compensator (STATCOM) for power system transient stability improvement. The system’s steady state and transient responses were respectively modelled with Newton-Raphson power flow and modified-Euler linearized swing equations. A balanced three-phased short circuit fault was introduced on selected buses for transient stability analysis. The steady state and transient responses of the system were simulated with and without STATCOM. The critical fault clearing time (CFCT) was obtained from the generators’ swing curves. The IEEE 9-bus and 14-bus power networks were used as test cases. The voltage magnitudes of all buses in both networks fell within the specified 0.95 to 1.1 p.u. voltage limit with and without compensation. The total active line loss on IEEE 9-bus and 14-bus networks which were 4.641 and 13.514 MW without compensation reduced to 4.600 and 13.014 MW, respectively with STATCOM’s application. The total reactive line losses of both networks which were 92.160 and 31.393 MVAr without compensation decreased to 90.160 and 30.693 MVAr, respectively with STATCOM’ utilization. The CFCT for fault on bus 8 of the IEEE 9-bus system without compensation were 0.2100 and 0.2700 s for generators 2 and 3, respectively. The system’s stability was, however, extended beyond 0.2700 s due to compensation from STATCOM. In the case of IEEE 14-bus system, the CFCT for fault on bus 6 was 0.36364 s for generators 2, 3, 4 and 5, respectively without compensation. The STATCOM inclusion, however, enhanced the system’s stability beyond 0.36366 s where all the four had lost synchronism. This work established that the use of STATCOM on the considered networks appropriately extended the CFCT such that the stability of the systems was not lost in the event of fault application via robust compensation of reactive power.

A novel estimation methodology for multi-resonance equivalent inductance of transformer winding for inter-turn short-circuit fault detection

A novel, indirect measurement technique for estimating equivalent inductance associated with multi-resonance behavior of an isolated transformer winding is reported for both healthy and inter-turn short-circuit fault-condition. For healthy winding, the authors proposed measuring two unique admittance magnitude responses of the winding followed by utilizing their natural frequencies for estimating the said inductance. Here, the one response is for line-end excitation with neutral-end grounded and the other one is for two equal and opposite polarity excitations from two ends of the winding. For inter-turn shorting, driving-point admittance magnitude response with neutral-end open is also utilized. This inductance seems to be one important parameter for verifying the design constraint mainly for impulse behavior as well as for identifying inter-turn shorting of the winding. The proposed method was also verified by experimental measurements on two actual transformer windings; one of which incorporated an iron core within it. All pertinent analytical derivations and the associated results are also included in the paper.

A Detection Method for Slight Inter-Turn Short-Circuit Fault in Dry-Type Air-Core Shunt Reactors

Dry-type air-core shunt reactors are integral components in power transmission and distribution networks, designed to control reactive power and enhance system stability. However, inter-turn short-circuit faults (ISCFs) are common occurrences in shunt reactors, which are caused by various factors, including manufacturing defects, insulation degradation, or operational stresses. At the early stage of the ISCFs, the current does not reach a sufficient level to activate the protective equipment. These faults may lead to serious consequences, such as overheating, insulation breakdown, and even catastrophic failures, posing risks to the entire power system. Therefore, developing an effective and reliable detection method for ISCFs at the early stage is paramount. In this paper, a new method named the fault detection factor (FDF) based on equivalent resistance is presented to detect the slight ISCFs in dry-type air-core shunt reactors considering insulation resistance. In addition, the effect of noise signal existence in the monitoring process is taken into account. A moving average filter is adopted to guarantee both the sensitivity and the reliability of the proposed method. Ultimately, the simulation results of the FDF under different conditions are presented, which show the effectiveness and potential of the proposed method in observing and monitoring slight ISCFs.

The influence of ITSF on vibration of high voltage Line-Start permanent magnet synchronous motor

PurposeThe purpose of this paper is to present the influence of inter-turn short circuit faults (ITSF) on electromagnetic vibration in high-voltage line-starting permanent magnet synchronous motor (HVLSPMSMS).Design/methodology/approachIn this paper, the ampere–conductor wave model of HVLSPMSM after ITSF is established. Second, a mathematical model of the magnetic field after ITSF is established, and the influence law of the ITSF on the air-gap magnetic field is analyzed. Further, the mathematical expression of the electromagnetic force density is established based on the Maxwell tensor method. The impact of HVLSPMSM torque ripple frequency, radial electromagnetic force spatial–temporal distribution and rotor unbalanced magnetic tension force by ITSF is revealed. Finally, the electromagnetic–mechanical coupling model of HVLSPMSM is established, and the vibration spectra of the motor with different degrees of ITSF are solved by numerical calculation.FindingsIn this study, it is found that the 2np order flux density harmonics and (2 N + 1) p order electromagnetic forces are not generated when ITSF occurs in HVLSPMSM.Originality/valueBy analyzing the multi-harmonics of HVLSPMSM after ITSF, this paper provides a reliable method for troubleshooting from the perspective of vibration and torque fluctuation and rotor unbalanced electromagnetic force.

A Search Coil Design Method of PMSM for Detection of Inter-Turn Short-Circuit Fault

Fault diagnosis systems based on search coils are widely used for detecting the inter-turn short-circuit (ITSC) fault, which is one of the most common electrical faults in electrical machines. Although various search coil structures have been proposed, there is not a systematic method proposed for the design of search coils. In addition, there is not a quantitative evaluation standard to evaluate the performances of search coils in each aspect, making it difficult to judge whether the proposed search coil structure is the optimal one. In this paper, the reliability, sensitivity and positioning ability of search coils are derived and evaluated by four defined characteristic indexes. And based on these four characteristic indexes, a systematic search coil design method based on the mutual inductance matrix is also proposed. With the proposed design method, the optimal search coil structures for different permanent magnet synchronous machines (PMSMs) are designed and optimized. It is found that the search coils designed by the proposed method have good performance in reliability, sensitivity and positioning ability. The performances of designed search coils are validated by the finite element analysis (FEA) and experiment.

Diversified Diagnosis Strategy for PMSM Inter-Turn Short-Circuit Fault via Novel Sliding Mode Observer

Diversified Diagnosis Strategy for PMSM Inter-Turn Short-Circuit Fault via Novel Sliding Mode Observer

A parameter-free fault location method for cross-bonding cable based on ranging equations

With the increasing application of long-distance high-voltage cables using the cross-bonding grounding method in urban power grids, the effectiveness and accuracy of the single-phase short-circuit fault location method for cross-bonded cables have gradually gained attention. To reduce positioning errors caused by inaccurate or unknown line parameters, a fault location method independent of line parameters is proposed. Firstly, the changes in sheath circulating current before and after the fault occurrence are analyzed, and based on these changes, a criterion for fault identification is established to determine the approximate range of fault occurrence. Secondly, considering the three-phase electromagnetic coupling of cross-bonded cables, an equivalent model for single-phase short-circuit faults in cross-bonded cables is established based on the double-π model. The along-line voltage and current are calculated by deducing electrical quantities at the ends of the cable. Then, the fault location equations are formulated based on the fault section, and the trust-region algorithm is employed to solve for fault distances and unit-length parameters of the cable in each equation group. Finally, a cable fault model is built using the PSCAD/EMTDC simulation platform, and the influence of different factors on the fault location method is analyzed. The results show that the fault location error of the proposed method is around 0.2 %, demonstrating high accuracy.

Experimental study of a teeth flux sensor for detection, location and severity evaluation of induction machine stator faults

PurposeThis paper aims to investigate the efficacy of teeth flux sensors in detecting, locating and assessing the severity of short-circuit faults in the stator windings of induction machines.Design/methodology/approachThe experimental study involves inducing short-circuit winding turn variations on the induction machine’s stator and continuously measuring the RMS values across teeth flux sensors. Two crucial steps are taken for machine diagnosis: measurements under load operating conditions for fault detection and measurements under no-load conditions to determine fault location and severity.FindingsThe experimental results demonstrate that the proposed approach using teeth flux sensors is reliable and effective in detecting, locating and evaluating the severity of stator winding faults.Research limitations/implicationsWhile this study focuses on short-circuit faults, future research could explore other fault types and alternative sensor configurations to enhance the comprehensiveness of fault diagnosis.Practical implicationsThe methodology outlined in this paper holds the potential to significantly reduce maintenance time and costs for induction machines, leading to substantial savings for companies.Originality/valueThis research contributes to the field by presenting an innovative approach that uses teeth flux sensors for a comprehensive fault diagnosis in induction machines. The originality lies in the effectiveness of this approach in providing reliable fault detection, location and severity evaluation.

Calculation of electromagnetic force and temperature distribution of amorphous transformers in different operating modes by finite element method

The study used the Finite element method (FEM) by ANSYS 3D software to calculate the distribution of electromagnetic force (EMF) and temperature on the high voltage and low voltage windings (HLVWs) of the amorphous steel core 3 phase transformer (ASCT) which has a power of 1000kVA –22/0.4kV under different load cases: No load, full load and short circuit (SC). The obtained results show the exact temperature distribution and location where the highest temperature is found on the HLVWs of ASCT. From the analysis of the temperature distribution on the HLVWs, it is shown that when the transformer falls into an SC fault, it causes the greatest EMF and thermodynamic force, causing extremely heavy consequences for the transformers. The obtained results help designers, manufacturers, and operators have the most suitable options to improve strength of SC and increase the life of the transformer.

A battery internal short circuit fault diagnosis method based on incremental capacity curves

The safe operation of battery energy storage systems (BESSs) has become one of the research priorities in this industry. And it is usually threated by various faults caused by design flaws, environmental conditions, and operating conditions et al. Among these faults, the internal short circuit (ISC) faults pose a significant threat to the safety of BESSs. Relevant studies focus on ISC fault diagnosis itself and ignore the impact of battery aging within the pack on fault diagnosis. To solve this problem, this paper proposes an ISC fault diagnosis method based on incremental capacity (IC) curves. And a qualitative differentiation between ISC batteries and aging ones is first achieved by leveraging the characteristic variations of IC curves. Then, an equivalent circuit model is constructed for ISC batteries. Further, a joint estimation of ISC resistance and SOC of the faulty battery is performed by combining Extended Kalman Filtering (EKF) and Forgetting Factor Recursive Least Squares (FFRLS). Finally, an experimental platform is established to verify the proposed method. Results show the proposed method can effectively differentiate between ISC batteries and aging batteries. Moreover, the estimation errors of SOC are less than 0.26% and the estimation accuracy of ISC resistance is more than 99.42%.

Transient Synchronous Stability Analysis of Grid-Forming Photovoltaic Grid-Connected Inverters during Asymmetrical Grid Faults

Compared with the traditional grid-following photovoltaic grid-connected converter (GFL-PGC), the grid-forming photovoltaic grid-connected converter (GFM-PGC) can provide voltage and frequency support for power systems, which can effectively enhance the stability of power electronic power systems. Consequently, GFM-PGCs have attracted great attention in recent years. When an asymmetrical short-circuit fault occurs in the power grid, GFM-PGC systems may experience transient instability, which has been less studied so far. In this paper, a GFM-PGC system is investigated under asymmetrical short-circuit fault conditions. A novel Q-V droop control structure is proposed by improving the traditional droop control. The proposed control structure enables the system to accurately control the positive- and negative-sequence reactive current without switching the control strategy during the low-voltage ride-through (LVRT) period so that it can meet the requirements of the renewable energy grid code. In addition, a dual-loop control structure model of positive- and negative-sequence voltage and current is established for the GFM-PGC system under asymmetrical short-circuit fault conditions. Based on the symmetrical component method, the composite sequence network of the system is obtained under asymmetrical short-circuit fault conditions, and positive- and negative-sequence power-angle characteristic curves are analyzed. The influence law of system parameters on the transient synchronous stability of positive- and negative-sequence systems is quantitatively analyzed through the equal area criterion. Finally, the correctness of the theoretical analysis is verified by simulation and hardware-in-the-loop experiments.

Arm integrated double capacitor submodule for modular multilevel solid-state transformers with DC short-circuit fault ride-through capability

Arm integrated double capacitor submodule for modular multilevel solid-state transformers with DC short-circuit fault ride-through capability

A Behavior Model of SiC DMOSFET Considering Thermal-Runaway Failures in Short-Circuit and Avalanche Breakdown Faults

Accurate fault simulation and failure prediction have long been challenges for SiC MOSFETs users. This paper presents a behavior model of Silicon Carbide (SiC) double-implanted MOSFET (DMOSFET), considering thermal-runaway failures in short-circuit and avalanche breakdown faults on the basis of cell-level physical processes. The proposed model can simulate the faults with extremely high accuracy and precisely predict SiC DMOSFET’s short-circuit withstand time and critical avalanche energy. By finite-element simulations, cell-level physical processes of short-circuit and avalanche breakdown faults are clarified. The mechanisms of thermal-runaway failures are deeply discussed with references to existing studies. Based on semiconductor and device physics mechanisms, the proposed model is constructed upon a traditional behavior model of SiC MOSFET with several parallel branches that are proposed to describe the thermal-runaway failures during both faults. The Cauer thermal network model is used for estimating junction temperature within it. The proposed model is constructed in Simulink, and it is validated using short-circuit and unclamped inductive switching (UIS) tests.

A fault diagnosis method of battery internal short circuit based on multi-feature recognition

The internal short circuit (ISC) fault has been considered as one of the most serious problems, which may pose a threat to the operation safety of the battery system. To solve this problem, this paper proposes an ISC fault diagnosis method based on multi-feature recognition to distinguish aging and ISC fault. The ISC equivalent circuit model is established first. In addition, three characteristic parameters, including the slope of the “rebound” voltage curve, the “valley” ordinate in the differential voltage (DV) curve, and the electric quantity, namely high segment charging capacity (HSCC) between the valley point of the DV curve and the end of charging position, are extracted to distinguish the ISC battery from aging battery. The results show that the proposed method can effectively distinguish between ISC batteries, aging batteries, and normal batteries. Moreover, the ISC resistance is able to be estimated accurately, with an error of less than 5.44%.

Diagnosis of Multicomponent Faults in SRM Drives Based on Auxiliary Current Reconstruction Under Soft-Switching Operation

Switched reluctance motors (SRMs) are considered a potential candidate for utilization in numerous safety-critical applications including electric vehicles (EVs) and more/all electric aircraft (MEA), etc., where the reliability of the drive system is critically important. An SRM drive system suffers from various electrical, mechanical, and sensor faults during operation. The existing fault detection schemes investigated each fragile component separately and proposed different approaches for each fault, which not only make the system complex but also less reliable for real-time implementation in safety-critical applications. Thus, a more sophisticated algorithm to detect and discriminate each of these faults in real time becomes attractive. A simple fault detection and isolation scheme for multiple faults in SRM drive systems is reported in this paper. The investigated faults include open- and short-circuit faults in power switches, open-phase winding, and zero-output current sensors faults. An auxiliary phase current for each phase was reconstructed from the dc-link and the faults are identified and discriminated effectively through the digital analysis of the fundamental current and the auxiliary current in real-time. The feasibility of the proposed scheme is verified by the extensive simulation and experiments conducted on a three-phase 12/8 SRM drive system.

Fault-Tolerant Control for Single-Phase Open-Circuit and Short-Circuit Fault in Five-Phase PMSM With Third-Order Harmonic Back EMF Using Coefficients Reconfiguration

Fault-Tolerant Control for Single-Phase Open-Circuit and Short-Circuit Fault in Five-Phase PMSM With Third-Order Harmonic Back EMF Using Coefficients Reconfiguration

One-Dimensional LSTM-Regulated Deep Residual Network for Data-Driven Fault Detection in Electric Machines

Achieving a model which accurately diagnoses faults in electric machines is a vital step in data-driven fault detection approaches. To this aim, this paper proposes a Long Short-Term Memory (LSTM) regulated deep residual network for data-driven fault diagnosis purposes in electric machines. The advantages of the proposed network are that it is more general in terms of fault type and measurement, results in a more accurate model for fault classification, and has faster convergence compared with other networks, such as conventional deep residual networks. In order to prove these advantages of the proposed network, it is evaluated by two different types of datasets. One is the Inter-Turn Short Circuit (ITSC) fault in a Permanent Magnet Synchronous Motor (PMSM) with the data of measured three-phase current. The second one is the Case Western Reverse University (CWRU) bearing fault dataset with the vibration measurements. The performance of the network is also compared with other networks. Results reveal that the model can accurately detect both types of faults by two different measurements with a test accuracy of 100%. Furthermore, it converges faster than other networks in the training procedure.

Skewness Driven DFIG's DC Link Bus Short and Open Circuit Faults Diagnosis Using Rotor and Stator Currents

Skewness Driven DFIG's DC Link Bus Short and Open Circuit Faults Diagnosis Using Rotor and Stator Currents

Fuzzy-Kalman-Filter-Based Short-Circuit Fault Diagnosis Design for Lithium-Ion Battery

Fuzzy-Kalman-Filter-Based Short-Circuit Fault Diagnosis Design for Lithium-Ion Battery