Open-circuit Fault Detection Research Articles

Machine learning based fault detection technique for hybrid multi level inverter topology

AbstractMultilevel inverters (MLIs) have a significant contribution in many industrial sectors due to their improved power quality and lesser voltage stress, over the conventional three‐level inverters. However, the implementation of MLIs with an increased device count creates the scope of development in MLIs topologies. In this regard, a hybrid MLI topology is studied in this paper whose architecture is based on conventional two‐level inverters. This topology has lesser device count characteristics when compared to conventional and most of the recently presented configurations for nine‐level output voltage generation. The major issue of capacitor voltage balancing is resolved by employing an appropriate switching strategy. However, the semiconductor switches are the most vulnerable components and causes the open circuit faults frequently that creates issues in real time operation. Hence, it is important to detect the open circuit fault in switches in the least possible time. A new approach to open circuit fault detection technique based on the analysis of load voltage waveform is proposed in this paper. The wavelet transform technique has been implemented for feature extraction of load voltage. Later, the classification of the fault has been achieved by training an artificial neural network (ANN). The proposed work has been studied in MATLAB/simulation and the obtained results are verified experimentally.

Capacitor voltage balancing, capacitance monitoring, and fast fault detection in a nested neutral point clamped (NNPC) converter with the reduced number of sensors

In multilevel converters (MCs), system components such as capacitors and semiconductor switches are very susceptible to damage. Furthermore, utilizing voltage sensors to balance capacitor voltages increases the system's cost and complexity while decreasing reliability. This paper presents methods for voltage balancing of capacitors, capacitance monitoring and open-circuit fault detection in nested neutral point-clamped (NNPC) converter with a reduced number of voltage and current sensors. In the proposed method, converter capacitors' voltage and current sensors are eliminated, and only the output sensors are employed to control the converter. In order to balance the voltage of capacitors, their voltages are estimated in three cases without using individual sensors. Comparing the capacitors' measured and estimated voltage change ratios is used to assess their health in the monitoring method. Thus, the capacitors' status can be checked by considering the system's health indicator during each period. Furthermore, the open-circuit fault detection method can identify defective switches within one processing cycle by comparing the converter's measured and standard output voltages in all switching states. The proposed methods have been evaluated in an experimental study of the system, and the results confirmed the effectiveness of the methods based on the new system configuration.© 2017 Elsevier Inc. All rights reserved.

Intermittent open-circuit fault diagnosis of inverters based on DC-link electromagnetic field signal

For the objective of improving the reliability of converters in electric drives, research on a method for early detection of intermittent open-circuit faults of power valves is reported in this article. Intermittent open circuit condition is the incipient form of power valve open-circuit fault in power converters. Prompt detection of this fault allows for timely remediation of permanent open circuit defects that is a commonly subsequent process. This study introduces an investigation of this fault, which occurs in the voltage source inverter of induction motor drives. Intermittent faults are created through interference with the control pulse of the power valve. Wavelet transform with the Mexican hat mother function is utilized for signal processing. Appropriate ranges of the scale are selected to obtain a high magnitude of the wavelet coefficient at faulty instants. The analysis for the direct current recorded at the DC-link in simulation and the electromagnetic signal measured at the DC-bus of the inverter can be effectively used for the fault diagnosis.

Advanced detection and localization of open circuit faults in two-level three-phase IGBT-based inverters using machine learning approaches and discrete wavelet transform

Advanced detection and localization of open circuit faults in two-level three-phase IGBT-based inverters using machine learning approaches and discrete wavelet transform

A Fast and Low-Cost Open-Circuit Fault Detection and Isolation Technique for Three-Phase Dual-Active-Bridge Converters Based on Finite State Machines

A Fast and Low-Cost Open-Circuit Fault Detection and Isolation Technique for Three-Phase Dual-Active-Bridge Converters Based on Finite State Machines

Universal Short-Circuit and Open-Circuit Fault Protection and Detection for a Power Converter's Power Device

Universal Short-Circuit and Open-Circuit Fault Protection and Detection for a Power Converter's Power Device

A Fast and Robust Open-Circuit Fault Detection Method for Voltage-Source-Inverter with Integrated High-Frequency Sensor

A Fast and Robust Open-Circuit Fault Detection Method for Voltage-Source-Inverter with Integrated High-Frequency Sensor

Detection, Classification, and Location of Open-Circuit and Short-Circuit Faults in Solar Photovoltaic Array: An Approach Using Single Sensor

Detection, Classification, and Location of Open-Circuit and Short-Circuit Faults in Solar Photovoltaic Array: An Approach Using Single Sensor

Open circuit fault diagnosis for a five-level neutral point clamped inverter in a grid-connected photovoltaic system with hybrid energy storage system

Introduction. Recently, the number of high and medium voltage applications has increased dramatically. The connection between these different applications requires series-parallel combinations of power semiconductors. Multilevel converter topologies provide major advantages to these applications. In this paper, a grid-connected photovoltaic system with a hybrid energy storage system using a five-level neutral point clamped inverter is studied. Although the multilevel inverter has many advantages over the two-level inverter, it has a high probability of experiencing an open circuit fault. In this context, the five-level inverter has 24 controllable switches, one of which may experience an open circuit fault at any time. Therefore, it plays an important part in the reliability and robustness of the whole system. The novelty of this paper presents an approach to accurately detect the open circuit fault in all insulated gate bipolar transistors of a five-level neutral point clamped inverter in a photovoltaic power generation application with a hybrid energy storage system. Purpose. Before using fault-tolerant control to ensure service continuity, fault diagnosis techniques must first be used, which are the crucial phase of reliability. Methods. A detection method based on the maximum and minimum error values is proposed. These errors are calculated using the expected and measured line-to-line pole voltages. Results. The open circuit fault detection method is implemented using MATLAB/Simulink. Simulation results showed the accuracy of detecting the open circuit fault in all insulated gate bipolar transistors in a short time. Moreover, this method is adaptable to several applications and is also robust to transient regimes imposed by solar irradiation and load variations.

Switch Open-Circuit Fault Detection and Localization for Modular Multilevel Converters Based on Signal Synthesis

Switch Open-Circuit Fault Detection and Localization for Modular Multilevel Converters Based on Signal Synthesis

An Open-Circuit Fault Detection Method of PMSM Fed by Dual Inverter With High Robustness

Power semiconductor is one of the most fragile components in the drive system of electric vehicles. In order to diagnose the failure timely, this paper proposes a diagnosis method of the open-circuit fault for open-end winding permanent magnet synchronous motor (OEW-PMSM) fed by dual inverter with a single dc source. The OEW- PMSM can improve the speed range and tolerance capacity of driving systems. However, the open-circuit fault diagnosis methods for Y-connected PMSMs cannot judge the faulty switch because of the symmetry of the dual inverter structure. The first step of the proposed method is to detect the faulty switch combinations by the error of normalized average value and average value of the zero-sequence reference voltage. The next step is to judge the faulty switch from a certain fault combination. The experimental results show that the open-circuit fault can be diagnosed accurately.

Electrical Signature Analysis for Open-Circuit Faults Detection of Inverter With Various Disturbances in Distribution Grid

This paper proposes an electrical signature analysis method for open-circuit faults (OCFs) detection of inverter with various disturbances in distribution grid. According to the fault mechanism, the fundamental value, rated harmonics and direct current component of three-phase currents are used as fault electrical signatures. The signatures are estimated by unscented Kalman filter (UKF) and recognized by extreme learning machine (ELM) for fault detection. Both OCF of single switch and OCFs of multiple switches are tested with consideration of direct disturbances such as load change, overcurrent and bias current, and indirect disturbances such as grid frequency variation, background harmonics and unbalanced voltage dip. The simulations and experiments show that the OCF detection of the new method is still accurate even with these disturbances, and reveal that only the signatures of the faulty phase current are immune to the disturbances while the ones of unfaulty phases are not. The robustness when facing the various disturbances and all explainable detection results make the new method suitable and effective for OCF of inverter detection in complicated distribution grid environment.

Open-circuit fault detection of inverter fed PMSM for electrical powertrain applications

<p>This paper aims to enhance the reliability of power electronic converters fed<br />permanent magnet synchronous machine for electrical powertrain applications.<br />Many faults like open circuit may affect the power converter and quickly lead to<br />a decline in supplied power quality and all the power train components behavior.<br />In this framework, this paper proposes an open circuit fault detection scheme for<br />inverters. First, the dynamic models of the powertrain subsystems were developed.<br />In fact, all the mathematics models of the motor, inverter, power converter,<br />battery and charger are presented. Then, a detection scheme of open-circuit fault<br />in inverter/motor. The control schemes were elaborated based on current analysis<br />method. The diagnosis strategy under discontinuous switch-ing dynamics of<br />the DC/AC inverter is proposed.</p>

An Open-Circuit Faults Diagnosis Method for MMC Based on Extreme Gradient Boosting

The diagnosis of open circuit faults is required for the reliability of modular multilevel converters (MMC) and the complex operating environment of MMC may cause missing data and external noise in signal detections, where some of the present open circuit fault detection methods can be disabled. This paper proposed a machine learning (ML) diagnosis strategy for open circuit faults in MMC based on extreme gradient boosting (XG-Boost). In this method, after data processing, the data segments composed of real-time capacitance voltage and current data are input into the trained XG-Boost multi-classification model for fault diagnosis without manually setting the empirical threshold, as is required in traditional change-of-rate-of-voltage-based diagnosis methods. This method has excellent robustness against external noise and missing data while better accuracy, higher speed and lower real-time calculation cost than existing ML-based methods are achieved. The effectiveness of the proposed method is verified by experiment results. It can diagnose the fault within 20ms with accuracy as high as 99.6%, even under the interference of Gaussian (GS) noise and the capacitor voltage data missing.

Currents Analysis of a Brushless Motor with Inverter Faults—Part I: Parameters of Entropy Functions and Open-Circuit Faults Detection

In the field of signal processing, it is interesting to explore signal irregularities. Indeed, entropy approaches are efficient to quantify the complexity of a time series; their ability to analyze and provide information related to signal complexity justifies their growing interest. Unfortunately, many entropies exist, each requiring setting parameter values, such as the data length N, the embedding dimension m, the time lag τ, the tolerance r and the scale s for the entropy calculation. Our aim is to determine a methodology to choose the suitable entropy and the suitable parameter values. Therefore, this paper focuses on the effects of their variation. For illustration purposes, a brushless motor with a three-phase inverter is investigated to discover unique faults, and then multiple permanent open-circuit faults. Starting from the brushless inverter under healthy and faulty conditions, the various possible switching faults are discussed. The occurrence of faults in an inverter leads to atypical characteristics of phase currents, which can increase the complexity in the brushless response. Thus, the performance of many entropies and multiscale entropies is discussed to evaluate the complexity of the phase currents. Herein, we introduce a mathematical model to help select the appropriate entropy functions with proper parameter values, for detecting open-circuit faults. Moreover, this mathematical model enables to pick up many usual entropies and multiscale entropies (bubble, phase, slope and conditional entropy) that can best detect faults, for up to four switches. Simulations are then carried out to select the best entropy functions able to differentiate healthy from open-circuit faulty conditions of the inverter.

Open Circuit Fault Detection of T-Type Grid Connected Inverters Using Fast S Transform and Random Forest.

To detect open circuit faults of grid-connected T-type inverters, this paper proposed a real-time method based on fast S transform and random forest. The three-phase fault currents of the inverter were used as the inputs of the new method and no additional sensors were needed. Some fault current harmonics and direct current components were selected as the fault features. Then, fast S transform was used to extract the features of fault currents, and random forest was used to recognize the features and the fault type, as well as locate the faulted switches. The simulation and experiments showed that the new method could detect open-circuit faults with low computation complexity and the detection accuracy was 100%. The real-time and accurate open circuit fault detection method was proven effective for grid-connected T-type inverter monitoring.

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 Novel Detection and Localization Approach of Open-Circuit Switch Fault for the Grid-Connected Modular Multilevel Converter

The open-circuit fault detection and localization (FDL) technique can improve the reliability of the modular multilevel converter (MMC). However, the conventional software-based FDL methods usually have a heavy computation burden or a limited localization speed. This article proposes a simplified and fast software-based FDL approach for the grid-connected MMC. First, the errors between the measured state variables (the output current and the circulating current) and their estimated values are calculated. By comparing these errors with their threshold values, the switch fault can not only be detected but also be localized to the specific arm. Then, the capacitor voltages in this faulty arm are collected, and the submodule (SM) with the highest capacitor voltage is selected. To confirm the switch fault in this SM, a modified <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Pauta</i> criterion is presented to check the abnormal voltage data. As a result, the computation burden of the proposed software-based FDL approach is significantly reduced, and the faulty SM can be localized in a short period. Simulation and experimental results verify that the proposed approach can effectively detect and localize different open-circuit faults, and it is immune to the step of power references.

Contribution of the two rectifiers reconfiguration to fault tolerance connected to the grid network to feed the GMAW through processor-in-the-loop

This study aims to propose a new diagnosis technique based on the Park’s vector and the polar coordinates of electric currents for the detection and location of open-circuit faults (OC) at the level of two rectifiers connected to the grid network to feed the Gas Metal Arc Welding process (GMAW). This diagnosis technique allows the early location of faulty switches (Thyristors) to overcome the negative effect of faulty rectifiers on welding current, welding voltage, and droplet diameter. For that, the reconfigurable rectifiers have been integrated to accomplish the welding process. The proposed diagnosis technique is applied to reconfigurable rectifiers connected to the GMAW system through numerical simulations using MATLAB/Simulink and real-time processor-in-the-loop (PIL) implementation via DSpace ds 1103 card. The simulation and PIL experimental results show similar trends and great success of the diagnosis technique and the two rectifiers reconfiguration for overcoming the open circuit faults and obtaining high welding quality while maintaining the work-piece and avoiding the distortions caused by the faulty rectifiers, which affecting the grid network and on the GMAW system at the same time.

Output voltage and conducted EMI-based open-circuit fault detection signatures in a single-phase packed U-cell inverter

Output voltage and conducted EMI-based open-circuit fault detection signatures in a single-phase packed U-cell inverter