Multiple Open-circuit Faults Research Articles

Diagnosis of Multiple Open-Circuit Faults in Three-Phase Induction Machine Drive Systems Based on Bidirectional Long Short-Term Memory Algorithm

Availability and continuous operation under critical conditions are very important in electric machine drive systems. Such systems may suffer from several types of failures that affect the electric machine or the associated voltage source inverter. Therefore, fault diagnosis and fault tolerance are highly required. This paper presents a new robust deep learning-based approach to diagnose multiple open-circuit faults in three-phase, two-level voltage source inverters for induction-motor drive applications. The proposed approach uses fault-diagnosis variables obtained from the sigmoid transformation of the motor stator currents. The open-circuit fault-diagnosis variables are then introduced to a bidirectional long short-term memory algorithm to detect the faulty switch(es). Several simulation and experimental results are presented to show the proposed fault-diagnosis algorithm’s effectiveness and robustness.

Robust Diagnosis of Multiple Open-Circuit Faults in DFIG Wind Turbines in Both Sub- and Super-Synchronous Operating Modes

Robust Diagnosis of Multiple Open-Circuit Faults in DFIG Wind Turbines in Both Sub- and Super-Synchronous Operating Modes

Comprehensive HFSVI-Based Sensorless Control Method for Dual Three-Phase Motor Considering Multiple Open-Circuit Faults

Comprehensive HFSVI-Based Sensorless Control Method for Dual Three-Phase Motor Considering Multiple Open-Circuit Faults

Experimental investigation of a real-time singularity-based fault diagnosis method for five-phase PMSG-based tidal current applications

This paper presents a novel real-time singularity-based fault diagnosis method for tidal current applications, specifically utilizing a five-phase permanent magnet synchronous generator with trapezoidal back electromotive forces. The proposed method incorporates an innovative orthogonal signal generator through a second-order filter, enabling the extraction of detectable singularity signatures from phase current signals. The principle of the method is elucidated through step-by-step design procedures, outlining the indicator enhancement approach and adaptive thresholds employed for enhanced robustness and adaptability. Fault detection is performed based on the improved fault indicators and an adaptive threshold law, followed by immediate fault localization that is achieved via twice average operations of the phase currents. To demonstrate the effectiveness and efficiency of the proposed method, a comparative study is carried out with a classical mean current vector-based fault diagnosis method. A small-scale experimental platform emulating a tidal current application is established for a comprehensive evaluation of both methods. The experimental results highlight the superior fault diagnosis performance of the proposed method, particularly in detecting single and multiple open circuit faults in phases or switches, while exhibiting enhanced robustness against variations in torque and speed. The simplicity of implementation and rapid detection mechanism are principal merits for the proposed method.

Currents Analysis of a Brushless Motor with Inverter Faults—Part II: Diagnostic Method for Open-Circuit Fault Isolation

In this paper, a brushless motor with a three-phase inverter is investigated under healthy and multiple open-circuit faults. The occurrence of faults in an inverter will lead to atypical characteristics in the current measurements. This is why many usual entropies and multiscale entropies have been proposed to evaluate the complexity of the output currents by quantifying such dynamic changes. Among this multitude of entropies, only some are able to differentiate between healthy and faulty open-circuit conditions. In addition, another selection is made between these entropies in order to improve diagnostic speed. After the fault detection based on the mean values, the open-circuit faults are localized based on the fault diagnostic method. The simulation results ensure the ability of these entropies to detect and locate open-circuit faults. Moreover, they are able to achieve fault diagnostics for a single switch, double switches, three switches, and even four switches. The diagnostic time to detect and to isolate faults is between 10.85 ms and 13.67 ms. Then, in order to prove the ability of the fault diagnostic method, a load variation is performed under the rated speed conditions of the brushless motor. The validity of the method is analyzed under different speed values for a constant torque. Finally, the fault diagnostic method is independent from power levels.

Torque Ripple Reduction of Model Predictive Controlled Five-Phase PMSM Drives With Open-Circuit Faults

In this article, a fault-tolerant model predictive current control method is proposed to improve the fault-tolerant ability of a five-phase permanent synchronous magnet motor drive under single and multiple open-circuit faults operations. On the principle of the optimal current control, general reference currents are derived to suppress torque ripples. To obtain the reference currents, a Fast Fourier Transformation-based current estimation model is established. The torque ripple can be reduced by modifying the reference currents in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d3-q3</i> axis transformed from the estimation model. Finally, experimental results validate the effectiveness of the developed fault-tolerant control strategy and the robustness against operating points and motor parameter mismatches.

Open-Circuit Fault Detection and Location in AC-DC-AC Converters Based on Entropy Analysis

Inverters and converters contain more and more power electronics switches which may subsequently affect their reliability. Therefore, fault detection and location are essential to improve their reliability and to ensure continuous operation. In this paper, an AC−DC−AC converter with three-phase inverter is investigated under permanent, single and multiple open-circuit fault scenarios. Many entropies and multiscale entropies are then proposed to evaluate the complexity of the output currents by quantifying their entropies over a range of temporal scales. Among the multitude of entropies, only some entropies are able to differentiate healthy from open-circuit faulty conditions. Moreover, the simulation results show that these entropies are able to detect and locate the arms of the bridge with open-circuit faults.

A Concurrent Diagnosis Method of IGBT Open-Circuit Faults in Modular Multilevel Converters

The insulated-gate bipolar transistor (IGBT) is one of the most vulnerable components in the modular multilevel converter (MMC). One or more IGBT open-circuit faults may deteriorate the output performance of the MMC and even destroy the MMC systems. In this article, a concurrent and direct fault diagnosis method has been proposed. The capacitor voltages are estimated with an amending Kalman filter (KF). By comparing the measured and estimated values, the corresponding faulty submodule (SM) can be detected directly and quickly. The diagnosis process of SMs is independent of each other so that all the SMs can be monitored in real time and the diagnosis time will not increase with multiple open-circuit faults occurring. The proposed method can also identify which IGBT has occurred open-circuit fault in the faulty SM and has no special requirement for the modulation method. In addition, the amending KF has excellent robustness to the transient process and can overcome the divergence problem, which is applicable in the complex nonlinear MMC system. The effectiveness of the proposed fault diagnosis method is confirmed by simulation in MATLAB/Simulink and experimentation in a single-phase MMC prototype with eight SMs per arm.

Real-time hardware-in-loop based open circuit fault diagnosis and fault tolerant control approach for cascaded multilevel inverter using artificial neural network

Multilevel inverters (MLI) are finding widespread in various engineering and commercial applications owing to their immense performance. The cascaded H-bridge (CHB) inverter is the most potential MLI topology for renewable energy applications. The successful operation of the CHB-MLI depends on the integrity of the semiconductor devices and capacitors. Irrespective of its benefits the huge number of switches decreases the reliability of the inverter. Concerning reliability, this article proposes a fault-tolerant (FT) CHB MLI for solar photovoltaic applications. The proposed CHB MLI can withstand both the single and multiple open circuit faults in all the H-bridges of the CHB topology. The diagonally opposite switch pairs of CHB topology have similar fault features which lead to difficulty in finding the fault switches using the analytical fault diagnosis methods. Hence an artificial intelligence (AI) based fault diagnosis (FD) and FT operation of CHB MLI are interpreted. The proposed model offers complete FD and FT operation within one fundamental cycle which is advantageous relative to the existing methods. Compared to the existing methods, the proposed AI-based fault diagnosis strategy achieves a shorter diagnosis time and provides 96% classification accuracy between various fault conditions. Further, the simulation and HIL results demonstrated that the voltage magnitude and THD have been maintained at 8.24% before and after the fault state. In addition, the suggested FT structure ensures the constant output power over the post-fault operation for both single and multiple switch failure instances while improving the MLI resilience. The feasibility and performance of the proposed method have been investigated through related case studies using simulation and hardware-in-the-loop (HIL) tests on a single-phase fifteen-level CHB MLI.

Fault diagnosis of power converters in a grid connected photovoltaic system using artificial neural networks

Introduction. The widespread use of photovoltaic systems in various applications has spotlighted the pressing requirement for reliability, efficiency and continuity of service. The main impediment to a more effective implementation has been the reliability of the power converters. Indeed, the presence of faults in power converters that can cause malfunctions in the photovoltaic system, which can reduce its performance. Novelty. This paper presents a technique for diagnosing open circuit failures in the switches (IGBTs) of power converters (DC-DC converters and three-phase inverters) in a grid-connected photovoltaic system. Purpose. To ensure supply continuity, a fault-diagnosis process is required throughout all phases of energy production, transfer, and conversion. Methods. The diagnostic approach is based on artificial neural networks and the extraction of features corresponding to the open circuit fault of the IGBT switch. This approach is based on the Clarke transformation of the three-phase currents of the inverter output as well as the calculation of the average value of these currents to determine the exact angle of the open circuit fault. Results. This method is able to effectively identify and localize single or multiple open circuit faults of the DC-DC converter IGBT switch or the three-phase inverter IGBT switches.

Open-Circuit Fault Detection in PMSM Drives Using Model Predictive Control and Cost Function Error

This article proposes a cost function error-based approach to diagnose open-circuit faults (OCFs) in permanent magnet synchronous machine drives with model predictive current control. The intrinsic relations of motor currents and cost functions under fault conditions are investigated. The residuals of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis currents are utilized to detect the fault type associated with the number of faulty devices. Instead of deriving the explicit values of cost functions, an estimation model is built according to the analytical expressions of currents and the optimal voltage vector. The error between the estimated cost function and the actual one is analyzed for fault localization. The faulty switch is finally diagnosed by assessing the minimum average absolute value of the cost function error. Simulated and experimental results confirm that the developed approach can achieve a fast diagnosis of single and multiple OCFs with good robustness to the motor parameter and operating power variations.

Multiple Open-Circuit Faults Diagnosis in Six-Phase Induction Motor Drives Using Stator Current Analysis

In recent years, multiphase machines have been presented as a good alternative to the classical three-phase machines due to their ability to operate under fault-tolerant conditions. However, the transition from pre- to post-fault control needs a reliable fault diagnostics algorithm. Accordingly, this article presents a reliable diagnostics approach that allows the detection and identification of multiple open-switches and open-phase faults in power converters fed six-phase induction motors, including adjacent and nonadjacent phases. The proposed method provides normalized numerical signatures from the measured output currents without requiring either tuning effort or detection thresholds. The reliability and robustness of the proposed algorithm are proven through experimental tests.

Multiple open-circuit fault diagnosis of three-phase rectifier based on current data reconstruction

ABSTRACT A novel and real-time fault diagnosis method based on current data reconstruction for rectifiers is proposed in this article. The symmetry of a 3-phase pulse-width modulation rectifier’s topology can be used for fault diagnosis. The symmetry is broken when open-circuit faults happen, a similarity measurement algorithm based on current data reconstruction is used for fault detection. Fault characteristics for current lists and multi-scale entropy are proposed to locate different kinds of faults. The proposed diagnostic method doesn’t need additional hardware devices and costs low. It is convenient to be embedded in an existing control system as a subprogram without significant adjustments. The experimental results show the effectiveness of the proposed diagnostic method for both single and multiple open-circuit faults.

A Reduced Switch Count Symmetric T-type Multilevel Inverter with Single and Multiple Switch Open Circuit Fault Tolerant Capabilities

In this paper, a nine-level inverter topology is proposed with the least number of switches and other components for fault tolerant (FT) operation. The proposed fault tolerant topology requires only one additional switch to execute the fault tolerant operation. The proposed topology also results in reduced total harmonic distortion (THD) as compared with other reported fault tolerant topologies for a 9-level output. A detailed analysis of the topology is presented and the fault tolerant operation is demonstrated under any single, double, triple, and quadruple switch faults using MATLAB/ Simulation and OPALRT hardware in loop (HIL) real time simulator. The proposed concept is validated for single and multiple switch faults and R-L load variation on a low scale laboratory hardware set-up.

A Multiple Open-Circuit Fault Diagnosis Method for Two-Level Three-Phase Voltage Source Converters Based on Average-Phase Voltage Model

This article presents a fault diagnosis method in the two-level three-phase voltage source converter (VSC) systems based on the average-phase voltage (APV) model without additional sensors or hardware circuits, which can diagnose and locate multiple open-circuit (OC) faults correctly and quickly. First, based on the idea of APV within one switching period and the changing rules of basic voltage vector after OC faults, the APV model consisting of grid-side APV (GAPV) model, prefault converter-side APV (CAPV) model, and postfault CAPV model is proposed. The APV model can be used to estimate the phase voltage under different OC faults. And then, the residual feature between GAPV and CAPV is analyzed under different single or multiple OC faults. With the help of the proposed APV model, both single and multiple OC faults can be diagnosed by deviation polarity, which avoids the complex deviation polarity sequences judgment. Meanwhile, the fault diagnosis method has the ability of correctness verification, which can strengthen the robustness and prevent false alarms. Finally, the effectiveness of the proposed model and method is validated with experiments; the multiple OC faults can be located within 2.5 ms.

An open-circuit fault diagnosis method for PMSM drives using symmetrical and DC components

In this paper, a diagnostic method based on symmetrical and DC components is presented for multiple open-circuit faults (OCFs) in a three-phase permanent magnet synchronous motor drive. The remaining phase currents under faulty situations are theoretically analyzed based on the Fourier series method and the mechanism of torque generation. To evaluate the asymmetry and discriminate fault types, the magnitude ratio of the positive sequence to the negative sequence of phase currents is designed as a fault detection index. Thereafter, the DC components of the phase currents in different reference frames are utilized to locate faults. Specifically, the polarities of the DC contents in the natural reference frame are utilized to locate a single OCF and two OCFs in different legs. Two OCFs in the same leg are diagnosed by evaluating the signs of the phase currents in the dq reference frame with a negative rotating direction. The simulated and experimental results validate the effectiveness of the developed method in fault detection and robustness against operating point and motor parameter variations.

Multiple Open-Circuit Fault Diagnosis for Back-to-Back Converter of PMSG Wind Generation System Based on Instantaneous Amplitude Estimation

To increase the reliability and availability of wind turbines, a new diagnosis method was proposed for multiple open-circuit faults in the back-to-back converters of turbines using permanent magnet synchronous generators (PMSGs). This method is the first to use the instantaneous amplitude (IA) as the principal quantity for formulating diagnostic variables that can distinguish different states of any switch accurately without being affected by speed variations. The method also uses the weighted sliding Hilbert transform (WSHT) to estimate the IA to remove the influence of end effects and carry the information of multiple open-circuit faults. To locate faulty switches, a localization method using signal samples adaptive processing was employed to eliminate the influence of speed changes. Finally, combining these diagnostic variables with identification thresholds makes it possible to detect and locate 21 open-circuit fault combinations for the PMSG-side and grid-side converters. Compared to the conventional fault diagnosis methods, simulation and experimental results showed that the proposed method more efficiently and reliably detects and locates multiple open-circuit faults of PMSG wind power converters.

Open-Circuit Faults Diagnosis in Direct-Drive PMSG Wind Turbine Converter

The condition monitoring and fault diagnosis have been identified as the key to achieving higher availabilities of wind turbines. Numerous studies show that the open-circuit fault is a significant contributor to the failures of wind turbine converter. However, the multiple faults combinations and the influence of wind speed changes abruptly, grid voltage sags and noise interference have brought great challenges to fault diagnosis. Accordingly, concerning the open-circuit fault of converters in direct-driven PMSG wind turbine, a diagnostic method for multiple open-circuit faults is proposed in this paper, which is divided into two tasks: The first one is the fault detection and the second one is the fault localization. The detection method is based on the relative current residuals after exponential transformation and on an adaptive threshold, and the localization method is based on the average values of fault phase currents. The scheduled diagnosis method is available to both the generator-side converter and the grid-side converter, allowing to detect and locate single and double open-circuit faults. For validating this, robustness test and multiple open-circuit faults diagnosis are presented in a 2-MW direct-driven PMSG wind turbine system, the results validate the reliability and effectiveness of the proposed method.

A Novel Diagnostic Method for Multiple Open-Circuit Faults of Voltage-Source Inverters Based on Output Line Voltage Residuals Analysis

A novel diagnostic method for multiple open-circuit faults of voltage-source inverters (VSIs) is proposed based on output line voltage residuals (OLVRs) analysis. Possible OLVRs are characterized for single-phase and double-phase faulty operations. By analyzing the OLVRs, it is found that the OLVRs show different characteristics under different open-circuit (OC) fault conditions, and the positive and negative polarities of the line current residuals are deduced to be consistent with the corresponding OLVRs. Therefore, the fault can be located by line current residuals to avoid the use of extra sensors and meanwhile improve the diagnostic speed. In addition, the presented method has the features of simple structure, robustness against false alarms and being easily inserted to the existing control algorithms. Simulation and experimental results confirm the effectiveness of the proposed algorithm, and additional tests show that the diagnostic speed can be as fast as 5% and as slow as 83% of the current period.

An On-Line Multiple Open-Circuit Fault Diagnostic Technique for Railway Vehicle Air-Conditioning Inverters

The safety and reliability of inverters play a significant role in stable power electronic system operations. Considering a railway vehicle air-conditioning inverter as a case study, this paper presents a generic open-circuit fault diagnosis method that can be applied to various inverter and control schemes. First, a detailed model of three-phase output currents under both normal and fault status is derived, and then the concept of space trajectory is introduced based on the three-phase output currents. The open-circuit faults of the inverter lead to output phase current distortion. Therefore, different types of faults have different space trajectories, and the corresponding shape of the space trajectory is considered to be a fault feature. Then, the fault is located by the direction vector and center-of-mass coordinate. The effectiveness and reliability of the diagnosis method are verified and analyzed using a hardware-in-the-loop test platform.