Open-circuit Fault Diagnosis Research Articles

An FCS-MPC-based open-circuit and current sensor fault diagnosis method for traction inverters with two current sensors

Effective fault diagnosis methods can improve the reliability of the two-level inverter used in traction systems. Both the open-circuit (OC) fault and current sensor fault can affect the phase currents of the inverter, which makes it difficult to distinguish them. In this paper, a diagnosis method for OC faults and current sensor faults is proposed, which is based on finite control set-model predictive control (FCS-MPC). First, the cost function is constructed and the inverter is controlled by the FCS-MPC. Then, the actual and estimated values of the cost function are calculated. The difference between them is applied to fault detection. Next, Combine the command signals and current direction, the number of affected sampling points in a period is counted and normalized. Different faults correspond to different percentages and this feature is used to determine fault location. Finally, the hardware-in-the-loop (HIL) platform is built, the feasibility and effectiveness of the proposed fault diagnosis method are verified by the HIL tests.

Power switch open circuit fault diagnosis strategy for novel fault-tolerant electric drive system based on fuzzy logic

A novel fault-tolerant electric drive system based on dual-winding permanent magnet motor (DWPMM) has been proposed to enhance the reliability of electric drive system. The proposed electric drive system with strong fault-tolerant capability not only possesses the superiority of high reliability, but also can reduce the cost of drive system and adapt to single power supply. Due to temperature mutation, line aging, electromagnetic interference, and low hardware reliability, the intermittent open circuit fault will be caused in power switches by the failure of drive signal. The power switch intermittent open circuit fault is a fault between normal state and complete fault state, which is not a complete open circuit fault and cannot be diagnosed by the conventional fault diagnosis methods. The fuzzy logic means to imitate the way of judgment and reasoning of uncertain concepts in human brain, and reason to overcome the fuzzy information problem which is difficult to solve by regular methods. In this paper, the power switch open circuit fault diagnosis strategy for novel fault-tolerant electric drive system based on fuzzy logic is proposed and investigated. Through theoretical analysis and verification, the research results indicate that the proposed power switch open circuit fault diagnosis strategy based on fuzzy logic can detect and locate the general and intermittent open circuit fault in real time and accurately.

A data-driven method for IGBT open-circuit fault diagnosis for the modular multilevel converter based on a modified Elman neural network

Modular multilevel converter is widely used in electrical energy with many advantages, its safety and reliability has become a research hotspot. Since the structure of MMC is composed of multiple cascaded sub-modules, including a large number of IGBTs and capacitors. Therefore, fault diagnosis measures must be taken to quickly eliminate the faults. In order to solve this problem, a data-driven method is proposed based on a modified Elman neural network. By comparing the distance Ek between the predicted and true value of bridge arm current, this method can quickly realize fault detection. The original contribution of this paper is using the modified cuckoo search (MCS) to optimize the parameters of Elman model, so as to achieve the optimal balance between fault diagnosis accuracy and diagnosis speed. The simulation results proved that it can quickly detect the open-circuit fault of IGBT by data-driven, and the detection time is about 20 ms.

A Hypothesis Method for T-Type Three-Level Inverters Open-Circuit Fault Diagnosis Based on Output Phase Voltage Model

The open-circuit (OC) faults for T-type three-level inverters often share similar distorted output features, which are usually distinguished by adopting invasive methods. The purpose of this article is to locate the OC fault by rebuilding the established phase voltage model according to the hypothesis method. Based on the vector decomposition principle and voltage-second balancing theory, the output phase voltage model is established considering neutral point voltage unbalance and time-offset injection. The hypothetical phase voltage vector and residual for fault reasoning can be obtained by inputting the suspected OC faults positions to the model. The hierarchical fault diagnosis scheme involves two steps. First, the group-level fault can be located according to voltage residual vector amplitude and angle. Considering the impact of parameter error, dead time, and delay time, an adaptive residual vector amplitude threshold is designed. Next, the device-level fault can be located by building two suspected phase voltage models to approximate the real system. Furthermore, the fault location rules under zero-crossing (ZC) and non-ZC conditions are summarized. Especially, the proposed hypothesis method has correctness verification ability to avoid misdiagnosis. Experimental results show the robustness and effectiveness of the proposed low coupling fault diagnosis method.

A Novel Diagnostic Method for Single and Dual Power Switch Open-Circuit Faults of Six-Phase FTPMSM System Even in Fault Tolerant Operation

This article proposes a new diagnostic method based on average current Park vector (ACPV) for single and dual power switch open-circuit faults of six-phase fault-tolerant permanent magnet synchronous motor (FTPMSM) system, which can be applied for the system both in nonfault and fault tolerant operation conditions. The fault diagnosis structure is composed of two parts: the ACPV moduli-based fault detection and the ACPV polarity-based fault location. By analyzing the ACPV before and after the fault, the normalized ACPV moduli-based fault detection is proposed by using the ACPV components in three orthogonal subspaces, which has good robustness to the speed and load changes. The ACPV polarity-based fault location is then proposed to locate the faulted power switches of the FTPMSM system. Finally, the effectiveness of the proposed fault diagnosis method is validated by a six-phase FTPMSM experimental platform. The fault diagnosis approach has the advantageous features of simple implementation, good robustness to various disturbances, no requirement of the extra sensors, and low computational burden, which can achieve single and dual power switch open-circuit fault diagnosis for the FTPMSM system both in normal and fault tolerant operation conditions.

Open-circuit faults diagnosis and Fault-Tolerant Control scheme based on Sliding-Mode Observer for DFIG back-to-back converters: Wind turbine applications

One of the most common types of wind turbines is the Doubly-Fed Induction Generator with a back-to-back converter. The Insulated Gate Bipolar Transistor switch’s open-circuit fault rate compared to the fault total rate in the wind turbine is noteworthy. The converter Insulated Gate Bipolar Transistor open-circuit causes a drawback in output current and as a result, the production performance of the turbine is reduced. In this article, a new method is presented for multiple Insulated Gate Bipolar Transistor open-circuit faults for open-circuit faults diagnosis. After the fault occurs, to maintain the performance of the turbine, fault compensation is performed based on the new Fault-Tolerant Control scheme. The proposed method is inexpensive, and for fault detection and location determining no need for additional sensors and hardware. This method uses residual output based on the Sliding Mode Observer with SAT function to detect faulty phase and overcome chattering Doubly-Fed Induction Generator converter. To residual evaluate and reduce the false alarm rate against changes in operating points and transient currents, the adaptive threshold is used. For efficient control of active or reactive power and dc-link voltage, a six-leg converter control based on Simplified Space Pulse Width Modulation is replaced by a five-leg converter based on Space Vector Modulation. Several experimental results using hardware in the loop Doubly-Fed Induction Generator test setup with a back-to-back converter are presented. It is shown the fault diagnostic algorithm is effective and robust against false alarms for both rotor and stator-side converters. The experimental result presents that the Fault Tolerant Control scheme can make power switch fault easily managed by the hardware reconfiguration and new control strategy adjusting.

Multiple Open-Circuit Fault Diagnosis Method in NPC Rectifiers Using Fault Injection Strategy

This article proposes an open-circuit fault diagnosis method in power semiconductors of three-level neutral-point-clamped (3L-NPC) rectifiers by using a fault injection strategy. To enhance the anti-interference ability of the diagnosis method, an improvement is made in the traditional calculation method of phase-to-phase pole voltage residuals by selectively adopting the quantifying operation according to the current level. Then, the normalized and quantified residuals are obtained as the diagnosis variables. All signals for calculations are derived from the controller and pre-existing sensors, avoiding the requirement of extra hardware. To improve the diagnosis accuracy and speed, a fault injection strategy is designed. A preidentification method provides guidance for choosing the type of fault to inject. On this basis, the fault injection is implemented by revising the switching signals sent from the modulation module for a short time. In this way, inner-switch faults and outer-switch faults are easier to be differentiated, and the misdiagnosis of simultaneous multiple-switch faults is avoided. Therefore, the proposed diagnosis method is accessible to detect single-switch faults as well as multiple-switch faults in 3L-NPC rectifiers more accurately and fast. The experiments are carried out to confirm the effectiveness and the robustness of the proposed fault diagnosis method.

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.

Fault-Tolerant Control for Reducing Harmonic Distortion of Dual Three-Phase Permanent Magnet Synchronous Motor

Aiming at the open circuit fault of a dual three-phase permanent magnet synchronous motor, a normalized current method is used for open circuit fault diagnosis. Then, a fault-tolerant control strategy for reducing the harmonic distortion of a dual three-phase permanent magnet synchronous motor is proposed, which is based on current model prediction control and keeps the decoupling transformation matrix unchanged. The fault-tolerant control method based on current model prediction considers the influence of the control quantity on the future state of the system, and effectively reduces the total harmonic distortion. Two fault-tolerant control strategies for the motor are analyzed, with minimizing stator copper consumption and maximizing torque output as control objectives. Through simulation and experiment of fault-tolerant control strategies for a dual three-phase permanent magnet synchronous motor, the results verify the effectiveness and feasibility of the strategy.

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.

FPGA Implementation of AI-Based Inverter IGBT Open Circuit Fault Diagnosis of Induction Motor Drives.

In modern industrial manufacturing processes, induction motors are broadly utilized as industrial drives. Online condition monitoring and diagnosis of faults that occur inside and/or outside of the Induction Motor Drive (IMD) system make the motor highly reliable, helping to avoid unscheduled downtimes, which cause more revenue loss and disruption of production. This can be achieved only when the irregularities produced because of the faults are sensed at the moment they occur and diagnosed quickly so that suitable actions to protect the equipment can be taken. This requires intelligent control with a high-performance scheme. Hence, a Field Programmable Gate Array (FPGA) based on neuro-genetic implementation with a Back Propagation Neural network (BPN) is suggested in this article to diagnose the fault more efficiently and almost instantly. It is reported that the classification of the neural network will provide the output within 2 µs although the clone procedure with microcontroller requires 7 ms. This intelligent control with a high-performance technique is applied to the IMD fed by a Voltage Source Inverter (VSI) to diagnose the fault. The proposed approach was simulated and experimentally validated.

Open Circuit Fault Diagnosis in Five-Level Cascaded H-Bridge Inverter

The development of power electronic converter, especially multilevel converter, is remarkable for several decades. The complex switching and increased power of semiconductor devices are prime reasons for faults in multilevel inverters and have raised question about reliability. To improve the reliability, a cost-effective solution in terms of fault diagnosis is essential. In this context, this study proposed an open circuit fault (OCF) diagnosis technique for a switching device in a five-level cascaded H-bridge multilevel inverter using fuzzy logic control. The OCF features like output voltage total harmonic distortion (THD) and normalized average output voltage are fuzzed as input variables of the fuzzy logic controller. These input variables are divided into various triangular antecedent membership function (MF). The output produced by the fuzzy controller as consequent MFs is divided into different levels to identify the faulty switch. In order to make a complete fault-tolerant structure, a reduced modulation index-based postfault control is suggested to get a balanced output voltage. The MATLAB/Simulink results and prototype results are the evidence to support the proposed fault diagnosis technique.

Open-Circuit Fault Diagnosis for MMC Based on Event-Triggered and Capacitor Current State Observation

The module multilevel converter (MMC) is composed of dozens of the insulated gate bipolar transistors (IGBT) and its reliability should be seriously considered. This brief presents a fault diagnosis and localization (FDI) method for open-circuit fault of the IGBT in an MMC, which combines event-based capacitor voltage with capacitor current state observation. Under the event-triggered mechanism, the fault diagnosis program is activated only when the capacitor voltage of submodules (SMs) violated the designed event-triggering condition, which can effectively reduce the computational burden for the controller. The current direction of the capacitor will change when the submodule has an open-circuit gault. This characteristic is extracted and used for diagnose and locate the fault IGBT by comparing the observed value with the theoretical value of capacitor current. The proposed FDL method can effectively reduce the computation intensity of the controller and do not require extra hardware. Simulation results show that the proposed FDL can diagnose and locate the open-circuit fault of IGBT accurately within two fundamental periods.

An Intelligent Control Strategy for a Highly Reliable Microgrid in Island Mode

An intelligent control strategy based on a membership cloud model in a high reliable off-grid microgrid with a reconfigurable inverter is proposed in this paper. The operating principle of the off-grid microgrid with the reconfigurable inverter is provided, which contains four operating modes. An open-circuit fault diagnosis for the inverter is presented first. The polarities of the midpoint voltages defined in the paper are used to recognize the faulty power switch. The reconfigurable inverter allows the power switches of different bridges to be reconfigured, when there are power switches faulty, to let the inverter operate in faulty state. The working principle of the reconfigurable inverter is given. The membership cloud model with two output channels is built to obtain the virtual impedance to suppress the circulating currents between inverters when the reconfigurable inverter is in faulty state. A pulse resetting method is presented. The general intelligent control strategy for the reconfigurable inverter is formed as the droop-virtual impedance-voltage-current-pulses resetting control. The validity of the intelligent control strategy of the system is verified by simulation.

Online Fault Diagnosis Method for Grid-Connected Inverters Based on Finite-Set Mixed Logical Dynamical Model Prediction

The grid-connected inverter is a key device in the renewable energy power generation system and large-scale energy storage system, which the operational stability and reliability are the basis for the efficient and safe application of electrical energy. A real-time fault diagnosis method of a three-phase for grid-connected application combining a mixed logic dynamic (MLD) model and finite control set model predictive control (FCS-MPC) is proposed. This paper not only realizes the open circuit fault diagnosis and location of the switching devices in the main power circuit, but also discusses the threshold issues and post-fault operations. The advantage of the proposed method is that it directly uses the control data and measurement signals of the controller without extra sensors and calculation, which will shorter the fault diagnosis time and occupy less calculation resource of the main processor. Simulation results illustrate the quickness of the fault identification and accurate position with robustness to the interference of the diagnosis method. Finally, the effectiveness of the diagnosis method was verified by a 1500W experimental prototype in a laboratory.

A currentless multiple switch open-circuit faults diagnosis strategy for modular multilevel converter with nearest level modulation in HVDC system

A currentless multiple switch open-circuit faults diagnosis strategy for modular multilevel converter with nearest level modulation in HVDC system

Open-Circuit Fault Diagnosis of NPC Inverter Based on Improved 1-D CNN Network

With the increasing popularization of a three-level neutral point clamped (NPC) inverter, realizing an accurate and fast fault diagnosis is also required. However, most methods are either not accurate enough or require a long period of time to collect signals as input. To compensate for these drawbacks, a novel 1-D convolution neural network (CNN) with the improved stochastic gradient optimization method is proposed in this article. First, the input data are segmented to ensure that the fault diagnosis can be completed if the current of a period is collected at any time in a period. Then, the feature of the waveform is extracted by the proposed network. In the meantime, the improved Adamod (IAdamod) method is implemented to better adaptively adjust the learning rate during the training process. Specifically, the learning rate is bigger at the beginning and smaller at the end. Finally, the classifier softmax is used for classification. The experimental results demonstrate the effectiveness of the proposed method in detecting and locating the faulty devices, which has shown that it perfectly realizes the fault diagnosis with 100% accuracy and can be diagnosed online with the time of less than 0.25 ms, far less than one cycle. The proposed method is also compared the traditional methods, and shows a better performance both in speed and accuracy, the loss can be less than 0.5 in iteration 220 and achieve zero in 1000.

A Generalized, Fast and Robust Open-Circuit Fault Diagnosis Technique for Star-connected Symmetrical Multiphase Drives

Multiphase drives with fault-tolerant capability are favored in high-reliability applications. In most fault-tolerant multiphase drives, the fault types and locations must be known prior to the fault-tolerant control. Therefore, fault diagnosis is an indispensable procedure. This paper proposes a generalized method to detect and identify the open-circuit faults (including open-switch and open-phase faults) in star-connected symmetrical multiphase drives with different phase numbers. The selected fault diagnosis signals are calculated solely from simple arithmetical operations of measured phase currents, resulting in easy real-time implementation. As fault detection signals are derived from the physical constraint imposed by the neutral point, the proposed method is naturally robust and not sensitive to operating points, machine transients and harmonics in stator currents. Therefore, a relatively small fault detection threshold can be used and fast detection can also be achieved. After the fault has been detected, the fault type is further identified according to the polarity of the integration of phase currents. Experimental results on nine-phase and five-phase induction machine drives verify the generality, fast diagnosis speed and robustness of the proposed method.

An Open-Circuit Faults Diagnosis Approach for Three-Phase Inverters Based on an Improved Variational Mode Decomposition, Correlation Coefficients, and Statistical Indicators

To ensure the reliability and robustness of the three-phase inverter, it is important to accurately detect the faults of insulated gate bipolar transistor (IGBT) switches. Signal processing is widely used for monitoring and fault diagnosis of the three-phase inverters. The current signals are usually noisy, which can lead to a loss of fault information. This article proposes a new approach for identifying and detecting the IGBTs open-circuit faults of a three-phase inverter. This approach is based on an improved version of the variational mode decomposition (IVMD) technique associated with correlation coefficients and statistical indicators (variance and mean value). First, the IVMD is applied to the three-phase current signals to obtain an elementary function called the band-limited intrinsic mode functions (BLIMFs). Second, the correlation coefficients between the original signals and theirs BLIMFs are used to select the relevant modes. The variances of the modes that have the highest correlation coefficients among those selected are calculated to detect the faulty phase and, therefore, the faulty leg. Finally, the mean value of the mode that has the lowest correlation coefficients among those selected of the faulty phase is calculated to localize the fault position in either the upper or the lower IGBTs of the faulty leg. Different experimental data are used to test the effectiveness of the proposed approach. The results obtained show the merits of the proposed approach for the diagnosis and detection of open-circuit IGBTs compared to the conventional method.

Open-circuit fault diagnosis for OEW-PMSM drives based on finite-control-set model predictive control

Open-circuit fault diagnosis for OEW-PMSM drives based on finite-control-set model predictive control