Short Circuit Fault Diagnosis Research Articles

Stator Current Spectrum Analysis Applied on Short-Circuit Fault Diagnosis of SRM

Stator Current Spectrum Analysis Applied on Short-Circuit Fault Diagnosis of SRM

A Current-Based Approach for Short-Circuit Fault Diagnosis in Closed-Loop Current Source Inverter

In this article, a method based on output currents is proposed to diagnose short-circuit faults of single or double switches in current source converter. The method only needs the feedback currents and their corresponding reference signals that can be obtained from the main control system. This diagnosis algorithm needs to calculate the average values of the feedback currents and the average absolute values of the current reference signals in one power frequency cycle. Diagnosis variables can be obtained from the ratio of the two values. Then, three detection thresholds are set to judge and locate the short-circuit power switches. The method can be implemented in the main control program directly, without additional voltage sensors and other auxiliary detection devices. Meanwhile, the method is simple and easy to implement in practice. The effectiveness of proposed algorithm is validated with experiments.

Sliding Mode-Based Active Fault-Tolerant Control for Induction Machine

This paper proposes an induction machine stator inter-turn short-circuit fault diagnosis and tolerance based on sliding mode. A Lyapunov stability-based integral sliding mode control is designed and kept in a healthy and faulty case. An online diagnosis using a high-order sliding mode observer allows the fault detection and phase identification on the one hand and provides signal alarm on the other. When the fault overcome such level, the proposed control cannot deal with the inter-turn short-circuit fault. So, it should be reconfigured. The signal alarm triggers the switch between affected stator current and healthy reconstructed ones. Then, fault impact will compensate and the integral sliding mode control still achieves the objectives. The simulation results are presented to illustrate the proposed fault-tolerant design.

Analytical Expressions of Isolation Indicators for Permanent-Magnet Synchronous Machines Under Stator Short-Circuit Faults

This paper proposes new analytical expressions of indicators for inter-turn and phase-to-phase short-circuit fault diagnosis in permanent-magnet synchronous machines. The proposed indicators are deduced from symmetrical components of phase currents in the $\alpha \beta$ reference frame. They are able to reflect the fault severity and location, are independent from the electrical pulsation and the rotor initial angle, and are robust regarding the loss of some measurements. Hence, they can be used for fault isolation and identification. Experimental tests have been carried out and show promising results. Furthermore, the presented algorithm does not use fast Fourier transforms and, therefore, avoids delays in fault isolation inherent to this technique.

Short-Circuit Fault Diagnosis Based on Rough Sets Theory for a Single-Phase Inverter

The short-circuit (SC) fault diagnosis in inverters is an important procedure for the continuity of the performance and the extension of its useful life. The methods of diagnosis of SC failures produce good results, however, they present unfavorable aspects: they detect only one of the faults of SC, that is to say, the hard switch fault (HSF) or the fault under load (FUL); depend on switch parameters; and use artificial intelligence (AI) techniques in their algorithms, which are executed simultaneously with the inverter operation. This article presents a method of diagnosing SC faults performed with a digital circuit. The proposed method identifies short-circuit faults: HSF and FUL; can be used with any switch, regardless of its parameters; and does not use AI algorithms and techniques concurrently with inverter operation. The digital diagnostic circuit is obtained with the use of rough sets theory (RST), which optimizes and defines a minimum set of variables necessary to diagnose faults. Applying RST to the variables obtains a set of diagnostic rules. These rules are performed with basic logic functions and, for this reason, a digital diagnostic circuit is obtained. The diagnostic variables are the command signals and the voltage source inverter switches currents. The simulation and experimental results validate the shown diagnostic method.

Calculation and Analysis of Rotor Thermal Static Field for Inter-Turn Short Circuit of Large Hydro-Generator Excitation Winding

Rotor winding inter-turn short circuit a common fault in hydro-generators. This fault would change the temperature, stress, and other thermal fields of a rotor and threaten the safe operation of the generator. In this paper, the Three Gorges hydro-generator is taken as an example. Mathematical models of three-dimensional temperature field and thermal stress field of rotor magnetic poles are established based on heat transfer theory and solved by finite element method. The temperature field, thermal deformation, and thermal stress distribution of magnetic poles in rotor winding inter-turn short circuit are calculated. On the basis of the calculation, the effects of the different turn numbers and positions of short circuit on the temperature, thermal deformation, and thermal stress of rotor magnetic poles are further studied. It is concluded that the thermal stress of the winding adjacent to the shorted turn would decrease, the thermal stress of the winding farther away from the shorted winding would increase, and so on. The results of this paper can provide references for inter-turn short circuit fault diagnosis and lay a foundation for the further studies of related faults.

A Dual-Winding Fault-Tolerant Motor Drive System Based on the Redundancy Bridge Arm

In order to adapt to the single power supply system of an aircraft, this paper proposes and investigates a novel dual-winding fault-tolerant (DF) motor drive system based on the redundancy bridge arm for aerospace applications. The proposed DF motor offers the advantages of magnetic isolation, physics isolation, thermal isolation, and small cogging torque ripple, inhibiting the short-circuit current and high fault tolerance. The proposed DF motor drive can adapt to the single power supply system of the aircraft, reduce the drive cost, and reduce the number of independent power sources and power switches. In addition, it can improve the power density, the reliability, and the utilization rate of the drive. At the same time, the drive system has stronger fault-tolerant ability, and it can achieve the fault-tolerant control for a one-phase-winding fault or a multiphase-winding fault. To realize the short-circuit fault diagnosis performance, the diagnosis and processing method of the short-circuit fault has been investigated. Then, to realize the short-circuit fault-tolerant performance, a novel space vector pulsewidth modulation (SVPWM) fault-tolerant control strategy based on the short-circuit fault diagnosis and processing method is proposed. Finally, the performances of the DF motor drive have been verified by experiments. The research results verify the reliability and effectiveness of the proposed DF motor drive system based on the redundancy bridge arm and the SVPWM fault-tolerant control strategy.

A Novel Diagnosis and Location Method of Short-Circuit Grounding High-Impedance Fault for a Mesh Topology Constant Current Remote Power Supply System in Cabled Underwater Information Networks

Cabled underwater information networks (CUINs) have evolved over the last decade to provide abundant power and broad bandwidth communication to enable marine science. To ensure reliable operation of CUINs, it is essential to have the technology for high-impedance fault diagnosis and isolation with high reliability and accuracy. The short-circuit grounding high-impedance fault status of mesh topology constant current remote supply system was diagnosed by analyzing the variation difference of equivalent current in the Laplace transform domain. Shore power feeding equipment (SPFE) supplied the power for underwater system individually from both terminals, and the fault location was located by calculating the shunt loss of the current in the trunk before and after the fault. Thus, the fault was isolated to maintain normal operation of the rest of the system and improve the reliability of CUINs. According to the established typical mesh topology constant current remote supply system circuit model, the fault location scheme was designed to simulate the faults of the cable sections in the different links in the constant current remote supply system, and the changes of current located at the primary nodes (PNs) in the Laplace transform domain before and after the fault were analyzed. The results show that the equivalent current of each PN changes when a fault occurs in the system, and the location of the fault point can be analyzed by comparing the shunt loss of the current in the trunk before and after the fault. The designed method of short-circuit grounding high-impedance fault diagnosis and location for a constant current remote supply system is suitable for the fault monitoring and judgment of CUINs with high feasibility and practicality. Furthermore, it provides technical support for the resulting effective determination of faults, isolation of faults, protection of equipment, and improvement of the system reliability.

On-Line Inter-Turn Short-Circuit Fault Diagnosis and Torque Ripple Minimization Control Strategy Based on OW Five-Phase BFTHE-IPM

This paper proposed an on-line inter-turn short-circuit (ITSC) fault diagnosis approach by observing the dc component in the torque deviation for the open-end winding (OW) five-phase brushless fault-tolerant hybrid-excitation interior permanent magnet motor (BFTHE-IPM). To eliminate the impact of ITSC fault on torque and guarantee a disturbance-free operation, the strategy of torque ripple minimization is proposed, in which the virtual direct-quadrature axis current feedforward compensator is adopted. Moreover, the compensation is obtained by measuring the zero-sequence current without calculating short-circuit turns ratio and short-circuit current. Therefore, computational quantity and complexity of the algorithm are greatly reduced. Simulation and experimental results verify the effectiveness of the proposed method.

Interturn Short-Circuit Faults in Permanent Magnet Synchronous Machines: An Extended Review and Comprehensive Analysis

This paper presents an extended review and recent advances in modeling and diagnosis of interturn short circuit (ITSC) faults in permanent magnet synchronous machines, supported with in-depth fault analysis. In the analysis part, the influence of the fault intensity on the machine’s parameters and performance is analyzed at various operating conditions through finite-element analysis, drive system models, and test bench measurements. The presented findings shed light on the fault signatures and factors that are affecting signature dynamics such as the fault intensity, operating conditions, resistance of the short-circuiting path, and controller action. Following the characterization of the ITSC fault, a detailed literature review on fault signature types and state-of-the art diagnosis methods are presented. The corresponding trends, shortcomings of current solutions, and potential research topics are discussed exhaustively.

Online Slight Inter-Turn Short-Circuit Fault Diagnosis Using the Distortion Ratio of Load Current in a Low-Voltage Induction Motor

Online Slight Inter-Turn Short-Circuit Fault Diagnosis Using the Distortion Ratio of Load Current in a Low-Voltage Induction Motor

On-line diagnosis of inter-turn short circuit fault for DC brushed motor

Extensive research effort has been made in fault diagnosis of motors and related components such as winding and ball bearing. In this paper, a new concept of inter-turn short circuit fault for DC brushed motors is proposed to include the short circuit ratio and short circuit resistance. A first-principle model is derived for motors with inter-turn short circuit fault. A statistical model based on Hidden Markov Model is developed for fault diagnosis purpose. This new method not only allows detection of motor winding short circuit fault, it can also provide estimation of the fault severity, as indicated by estimation of the short circuit ratio and the short circuit resistance. The estimated fault severity can be used for making appropriate decisions in response to the fault condition. The feasibility of the proposed methodology is studied for inter-turn short circuit of DC brushed motors using simulation in MATLAB/Simulink environment. In addition, it is shown that the proposed methodology is reliable with the presence of small random noise in the system parameters and measurement.

A fractional-order model-based battery external short circuit fault diagnosis approach for all-climate electric vehicles application

Abstract: The impact of SOC and temperature on external short circuit (ESC) faults characteristics of lithium-ion batteries, including the current and voltage variation and temperature increase, are analyzed. A fractional-order model (FOM) and a first-order RC model are both employed to describe the electrical behavior of the battery cells with the ESC fault. While the model parameters are identified by the genetic algorithm (GA). A comparison study is made on the prediction accuracy for the two models. An effective classification method based on a random forests (RF) model is proposed to recognize the electrolyte leakage behavior that occurs during the ESC fault experiments. Based on the above efforts, the three steps model-based diagnosis algorithm for identifying the ESC fault and even electrolyte leakage of the battery in real-time is proposed. Two indicators of the root mean square error (RMSE) of battery predicting voltage are applied to diagnose for the ESC fault only and ESC-leakage merged fault. The result of the leakage condition is obtained by a pre-trained RF classifier to confirm the leakage detection result based on the RMSE indicator. Several cases are verified that all the ESC cells can be diagnosed efficiently.

A novel perturbed particle swarm optimization-based support vector machine for fault diagnosis in power distribution systems

In this paper, a novel perturbed particle swarm optimization (PPSO) algorithm is investigated to improve the performance of a support vector machine (SVM) for short-circuit fault diagnosis in power distribution systems. In the proposed PPSO algorithm, the velocity of each particle is perturbed whenever the particles strike into a local optimum, in order to achieve a higher quality solution to optimization problems. Furthermore, the concept of proposed perturbation is applied to three variants of PSO, and improved corresponding algorithms are named perturbed C-PSO (PC-PSO), perturbed T-PSO (PT-PSO), and perturbed K-PSO (PK-PSO). For the purpose of fault diagnosis, the time- domain re ectometry (TDR) method with pseudorandom binary sequence (PRBS) excitation is considered to generate the necessary fault simulation data set. The proposed approaches are tested on a typical two-lateral radial distribution network.

A Model-Based Strategy for Interturn Short-Circuit Fault Diagnosis in PMSM

A model-based method for interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSMs) is proposed in this paper. The fault detection is realized based on a residual current vector (RCV) generated by the difference between the measured stator currents and the stator currents estimated by a state observer. In order to avoid false alarms due to possible undesired perturbations, the sequence decomposition of the RCV is performed by employing different reference-frames. Thus, the proposed RCV allows the correct detection of interturn short-circuit faults and quantification of the fault severity in any faulty stator-phase winding. Moreover, since the back-EMF generated by the magnets is proportional to the rotor shaft speed, the electrical angular speed is estimated through the stator voltages measurement, without using a speed sensor. Simulation results from the three-phase PMSM dynamic model that allows considering the interturn short-circuit fault in any stator phase-windings are presented. The proposed method is validated using a three-phase PMSM prototype with modified stator windings. The robustness and the reliability of the proposal was tested for several interturn fault conditions under transient conditions including different disturbances.

Induction Motor Stator Fault Diagnosis by Rotor Slots Harmonics Tracking Using Prony Improved Approach

The short-circuit fault diagnosis is essential in order to avoid irreversible damages that could affect the stator circuit of the induction motor. For this purpose, this paper addresses a new approach based on Prony's high resolution spectral analysis method to avoid the drawbacks of the well-known method based on the power spectral density estimation by Periodogram technique. This new approach, called Root-Prony, allows a better frequency resolution even on a very short acquisition time as well as a better detection even on very small magnitudes. Moreover, and in order to reduce the computation time of this approach, this paper proposes to analyze only the band around the first rotor slot frequencies. The choice of this band allows avoiding any confusion with the frequency signatures of external phenomena which appear most often in very low frequencies. The experimental results obtained show the efficiency and the reliability of this new approach in tracking the induction motor stator winding degradation.

An Early Stage Interturn Fault Diagnosis of PMSMs by Using Negative-Sequence Components

This paper proposes an early stage interturn short-circuit fault (ISCF) diagnosis method for permanent magnet synchronous machines. A fault indicator is suggested based on a new theoretical analysis of the relationship between the fault current and the rotor speed. The fault indicator is shown to be robust to the rotor speed changes in slight ISCFs. It is calculated by introducing negative-sequence components (NSCs). It is shown that the fault indicator using NSCs can diagnose slighter ISCFs than that using zero-sequence components. Experimental results demonstrate the effectiveness of the proposed method for diagnosing early stage ISCFs with a small number of short-circuited turns and low fault current.

Stator and Rotor Faults Diagnosis of Squirrel Cage Motor Based on Fundamental Component Extraction Method

Nowadays, stator current analysis used for detecting the incipient fault in squirrel cage motor has received much attention. However, in the case of interturn short circuit in stator, the traditional symmetrical component method has lost the precondition due to the harmonics and noise; the negative sequence component (NSC) is hard to be obtained accurately. For broken rotor bars, the new added fault feature blanked by fundamental component is also difficult to be discriminated in the current spectrum. To solve the above problems, a fundamental component extraction (FCE) method is proposed in this paper. On one hand, via the antisynchronous speed coordinate (ASC) transformation, NSC of extracted signals is transformed into the DC value. The amplitude of synthetic vector of NSC is used to evaluate the severity of stator fault. On the other hand, the extracted fundamental component can be filtered out to make the rotor fault feature emerge from the stator current spectrum. Experiment results indicate that this method is feasible and effective in both interturn short circuit and broken rotor bars fault diagnosis. Furthermore, only stator currents and voltage frequency are needed to be recorded, and this method is easy to implement.

Diagnosis and classification using ANFIS approach of stator and rotor faults in induction machine

Three-phase squirrel cage induction motors are one of the important elements of the industrial production system, and are mostly used because of their robustness, reliability, relatively simple construction and their low cost. Nevertheless, during their function in different process, this machine types are submitted to external and internal stresses which can lead to several electrical or mechanical failures. In this paper, we proposed a reliable approach for diagnosis and detection of stator short-circuit windings and rotor broken bars faults in induction motor under varying load condition based on relative energy for each level of stator current signal using wavelet packet decomposition which will be useful as data input of adaptive neuro-fuzzy inference system (ANFIS). The adaptive neuro-fuzzy inference system is able to identify the induction motor and it is proven to be capable of detecting broken bars and stator short-circuit fault e with high precision. The diagnostic ANFIS algorithm is applicable to a variety of industrial process based on the induction machine for detection and classified the any faults types. This approach is applied under the MATLAB software®.

Diagnosis of Short Circuit Faults Within Turbogenerator Excitation Winding Based on the Expected Electromotive Force Method

Short circuit faults in an excitation winding pose a potential threat to the safe and stable operation of turbine generators. Some turbine generators are forced to shut down for an overhaul whenever a fault occurs, and the economic losses can be serious. In this paper, a 2-D simulation model has been established using the basic electromagnetic and structural parameters of a generator. Here, the generator's excitation current at normal working conditions is calculated, and two binary function is used for the calculation of no-load electromotive force (EMF) expectations on the excitation current and active power is derived. Based on the fundamental characteristics associated with the reduction of effective turns in the excitation winding after a short circuit, the excitation winding short circuit fault can be determined using the deviation between the actual value and the desired value of generator no-load EMF. Fault examples showed that this method can achieve higher diagnosis accuracy, and that it can be used for the real-time monitoring and diagnosis of an overall excitation winding health inside a turbine generator.