Open-circuit Fault Detection Research Articles

Short and Open Circuit Fault Detection in On-Grid Photovoltaic Systems 1MWP Bangli Based on Current and Voltage Observation

Photovoltaic (PV) systems as clean and green electrical energy generators have increased sharply in the last 10 years. The installation of a PV system in an open area is one of the causes of frequent faults/damage to the PV system. Fault in the PV system causes a decrease in efficiency, weak reliability, and disruption of the continuity of the electrical power distribution, which in turn causes the low performance of the system. This research does on the on-grid PV system 1MWp Bangli which consists of 278 PV arrays and 5004 monocrystalline solar modules 200Wp, which started operation in 2013. This research aims to find open circuit and short circuit faults that occur in the PV system Bangli. The method used in this research is the current and voltage observation method. Current and output voltage measurements from the PV array are carried out as well as measurements of working module temperature and solar irradiance. To calculate the output PV array's current (RI) and voltage (RV) indicators; Calculation of the current (RIM) and voltage (RVM) indicators under fault-free conditions, and the short circuit (TIO) and open voltage (TVS) threshold are calculated. As a result, this study succeeded in determining short and open circuit faults that occur in PV systems on grid 1MWp Bangli.

A Novel Open-Circuit Fault Detection and Location for Open-End Winding PMSM Based on Differential-Mode Components

Detecting and locating the open-circuit (OC) fault of an insulated-gate bipolar transistor (IGBT) rapidly and accurately is very important to improve the security and reliability of the drive system. However, due to the symmetry of the dual-inverter topology, it is difficult to achieve fault detection for open-end winding permanent magnet synchronous motor (PMSM). Thus, this article proposes a fault diagnosis technology for open-end winding PMSM fed by a dual inverter with a common dc bus. In this method, the faulty phase and the faulty case are identified by the average value of the output of the closed-loop controller, which is used to eliminate the differential-mode current in the system. Then, the faulty phase is isolated by removing the gate signals. Finally, the faulty IGBT is located by restructuring the faulty phase and analyzing the current of the faulty phase. In this method, the OC fault can be detected and the faulty IGBT can be located accurately. Experimental results are shown to validate the proposed detection method.

A Series-Winding Topology Converter With Capability of Fault-Tolerant Operation for Active Magnetic Bearing Drive

Magnetic bearing is an important part of modern high-speed rotating machinery. The performance of power electronic converter highly determines the quality of magnetic bearing drive. In this article, a fault-tolerant converter with series-winding topology is introduced. Compared with the traditional topology, the current stress of phase leg is reduced while the utilization of dc voltage is guaranteed, and fault-tolerant operation can be realized in the case of open-circuit fault of the switching device. This article introduces the characteristics of the series-winding topology and the current control method. Open-circuit fault detection methods and countermeasures are also analyzed. Experimental results show the effectiveness of the proposed topology. Fault-tolerant experiments under static suspension and rotation of the rotor demonstrate the performance of the topology. This kind of series-winding topology provides a new scheme with good performance and high reliability for the design of magnetic bearing controllers.

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.

FAULT DETECTION BASED ON THE DISCRETE WAVELET TRANSFORM FOR THE CONVERTER OF A WIND POWER GENERATOR SYSTEM OPERATING UNDER DISTURBANCES IN THE GRID

In this work, an open-circuit fault detection scheme for the converter of a wind power generation system is proposed and evaluated, which is robust to false detections under grid disturbance conditions such as sags and swells. The wind energy system is composed of a doubly-fed induction generator (DFIG) that supplies energy to the electrical grid through a power electronics converter based on the neutral point-clamped topology in a back-to-back configuration (NPC-BTB). The converter operates with a field-oriented-control (FOC) scheme, whereas the fault detection method is based on the processing of the current signals flowing through the converter at the rotor and stator sides of the generator using the discrete wavelet transform (DWT) with the Haar and Daubechies4 wavelet types. The fault detection scheme is evaluated verifying that false detections do not arise, analyzing cases where magnitude variations in the grid voltage of 15%, 30% and 50% occur, with respect to the nominal operating condition.

Detection of Open-Circuit Faults in Multi-Level Hybrid Active Neutral Point Clamped Inverters

Detection of Open-Circuit Faults in Multi-Level Hybrid Active Neutral Point Clamped Inverters

Fault detection for power electronic converters based on continuous wavelet transform and convolution neural network

With the rapid development of new energy vehicles, the reliability and safety of Brushless DC motor drive system, the core component of new energy vehicles, has been widely concerned. The traditional open circuit fault detection method of power electronic converters have the problem of poor feature extraction ability because of inadequate signal processing means, which lead to low recognition accuracy. Therefore, a fault recognition method based on continuous wavelet transform and convolutional neural network (CWT-CNN) is proposed. It can not only adaptively extract features, but also avoid the complexity and uncertainty of artificial feature extraction. The three-phase current signal is converted into time-frequency spectrum by continuous wavelet transform as the input data of AlexNet. At the same time, the changes of time domain and frequency domain under different fault modes are analyzed. Finally, the softmax classifier with Adam optimizer is used to classify the fault features extracted by CNN to realize the state recognition of different fault modes of power electronic converter. The experimental results show that the CWT-CNN model achieves satisfactory fault detection accuracy under different working conditions and different fault modes. The effectiveness and superiority of the proposed method are verified by comparing with other networks.

Open-Circuit Fault Detection and Isolation Method for Five-Level PUC Inverter Based on the Wavelet Packet Transform of the Radiated Magnetic Field

This article proposes a noninvasive open-switch fault detection method based on the analysis of the high-frequency signals. The faulty power switch is detected by metering the emitted near-field above a new topology using the wavelet packet transform and considering a complex control algorithm. The proposed method is tested on a single-phase five-level packed U-cell (PUC5) inverter. The latter is controlled using the finite-control set model predictive control (FCS-MPC) technique that generates the gate signals with a variable switching frequency. Moreover, unlike the conventional pulsewidth modulation strategy, the switching pattern provided by the FCS-MPC technique is not known in advance. Despite these complexities, the proposed fault detection method proves its high performance and effectiveness. Experimental studies are carried out on a single-phase PUC5 inverter using the real-time controller (OP4510) from OPAL-RT and prove the capability of this method to properly identify the faulty switch in this multilevel topology.

An Open-Circuit Fault Detection and Localization Scheme for Cascaded H-Bridge Multilevel Converter Without Additional Sensors

In this article, a new model-based fault detection and localization scheme is proposed for cascaded H-bridge (CHB) multilevel converter to localize the open-circuit faults without needing any additional sensors. The grid current is estimated from the gird voltage, switching states, and dc bus voltages, and compared with the measured grid current. Any significant deviations in the estimated and actual grid currents of the CHB trigger an open-circuit (OC) fault. Once the fault is detected, modulation scheme is switched from phase-shifted unipolar SPWM to phase-shifted bipolar sine pulse width modulation (SPWM) to localize the OC faults. At selected time instants, the change in measured grid current for a specific period is calculated and compared with the estimated change in grid current from the system model. The abovementioned comparisons are used to localize the OC faults in the CHB. The proposed method is validated on a scale-down CHB prototype developed in the laboratory environment, and experimental results are presented to demonstrate the effectiveness of the proposed method.

An Automotive-Grade Monolithic Masterless Fault-Tolerant Hybrid Dickson DC–DC Converter for 48-V Multi-Phase Applications

Autonomous-driving features necessitate a fault-tolerant (FT) power-management unit in 48-V automotive applications. This article presents a monolithic single-phase closed-loop masterless FT four-to-one hybrid Dickson converter IC for high-conversion-ratio 48-V automotive multi-phase applications. The chip includes: 1) a mixed-signal droop-based valley-current ON-time quasi-fixed-frequency control, which enables masterless multi-phase operation capability; 2) single-point short-circuit fault and open-circuit fault detection and blocking of any power switches or flying capacitors; 3) an optimized high-voltage (HV) power stage with fully integrated flying-capacitor-sourced gate drivers without any external bootstrap capacitors; 4) a glitch-free cross-coupled bootstrapped HV level shifter; and 5) a dual-leg bidirectional closed-loop current-sensing circuit optimized for the hybrid Dickson topology. The design was fabricated in a 0.13- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> 90-V automotive silicon-on-insulator (SOI) bipolar-CMOS–DMOS (BCD) process. The measured results confirm the operation over 20–60-V input, 3.3-V nominal output, 3-A maximum load, and 320-kHz effective switching frequency within the automotive-grade −40 °C–+125 °C ambient temperature. The design achieves above 90% measured efficiency at maximum conversion ratio and load at room temperature. A three-phase system is used to evaluate and confirm the fault-blocking capability and continuous power delivery upon detection of a fault.

New open circuit fault detection in aDC‐DCconverter

New open circuit fault detection in a<scp>DC‐DC</scp>converter

A Novel Open-Circuit Fault Detection and Localization Scheme for Cascaded H-Bridge Stage of a Three-Stage Solid-State Transformer

A three-stage solid-state transformer (SST) is a preferred replacement for line frequency transformer as it provides ancillary services in addition to stepping-up/down of grid voltages. Each active switch in SST is a potential source of failure, and a quick fault detection and isolation help in reducing the downtime. In this article, a novel fault detection and localization algorithm is proposed to localize the open-circuit (OC) faults (be it a single switch fault or multiple switch faults in multiple modules) in the cascaded H-bridge (CHB) stage of the SST. The proposed method is designed such that only one voltage sensor is needed to measure the grid-side voltage of the CHB for fault detection and localization. By comparing the estimated grid-side voltage of the CHB with the measured values, OC fault is detected. Once the fault is detected, the modulation scheme is switched from phase-shifted unipolar sinusoidal pulsewidth modulation (SPWM) to phase-shifted bipolar SPWM to localize the faults. The difference in the measured grid-side voltage of the CHB before and after each module's state change is calculated and faults are localized. The presented algorithm is substantiated using experimental results from a 1-kVA SST prototype. The main advantage of the proposed algorithm is that it requires only 2n comparisons to localize the faulty modules in a CHB with n H-bridges, which takes less than a line cycle to complete.

GSM Based Underground Cable Open and Short Circuit Fault Detection

The underground cable system is a common practice followed in many urban areas. While a fault occurs for some reason, at that time the repairing process related to that particular cable is difficult due to not knowing the exact location of the cable fault. Hence, the main objective of this project is to determine the distance of underground cable fault from base station in kilometers using an Arduino board and GSM. The project uses the standard concept of Ohms law and voltage division rule to detect and locate the fault. The fault occurring at a particular distance and the respective phase is displayed on a LCD interfaced to the Arduino board and information regarding fault occurrence is sent to control areas using GSM modules.

Open-Circuit Fault Detection and Classification of Modular Multilevel Converters in High Voltage Direct Current Systems (MMC-HVDC) with Long Short-Term Memory (LSTM) Method.

Fault detection and classification are two of the challenging tasks in Modular Multilevel Converters in High Voltage Direct Current (MMC-HVDC) systems. To directly classify the raw sensor data without certain feature extraction and classifier design, a long short-term memory (LSTM) neural network is proposed and used for seven states of the MMC-HVDC transmission power system simulated by Power Systems Computer Aided Design/Electromagnetic Transients including DC (PSCAD/EMTDC). It is observed that the LSTM method can detect faults with 100% accuracy and classify different faults as well as provide promising fault classification performance. Compared with a bidirectional LSTM (BiLSTM), the LSTM can get similar classification accuracy, requiring less training time and testing time. Compared with Convolutional Neural Networks (CNN) and AutoEncoder-based deep neural networks (AE-based DNN), the LSTM method can get better classification accuracy around the middle of the testing data proportion, but it needs more training time.

Open Circuit Switch Fault Detection in Flying Capacitor and Cascaded H-Bridge Multilevel Converters

This article proposes a simple and fast active power device open circuit fault detection and localization technique. The proposed technique applies to the family of flying capacitor multilevel converters (FCMCs), including dc/dc FCMCs, single or multi-phase H-bridge FCMCs, and cascaded H-bridge multilevel converters. The localization technique needs to sense the voltage and direction of current at the output terminals of converters to detect and localize the fault. A circuit with multiple window detectors is utilized to track the output voltage level and current direction with high bandwidth. The algorithm compares the measured and expected terminal voltage, considering the commanded switch states and the terminal current direction. Once potential fault locations are identified, healthy switches are filtered out from the set of potential faulty switches over successive switching transitions. The proposed technique is experimentally validated on a single phase H-bridge FCMC. The switch state commands and pulsewidth modulation (PWM) is handled by a DSP while the fault detection and localization algorithm is implemented on a separate field programmable gate array (FPGA). The asynchronous operation of the DSP and FPGA is discussed.

Fault Detection and Tolerance of a Hybrid Five Level Inverter

Multilevel inverters (MLIs) have received a significant attention in literature due to advent of various topologies utilising power semiconductor switches with reduced voltage stress. However, the increased component count and susceptible nature of semiconductor components increase the chance of failure in inverter. The fault in power switches, either open circuit or short circuit, if persist for long time may result in complete system shutdown. This damage can be avoided by detecting and diagnosing the fault in less period of time to continue the healthy operation. The present paper studies an open-circuit fault detection method on conventional five-level NPC inverter topology with output voltage waveform analysis by discrete wavelet packet transform (DWPT) and classifying the fault location by artificial neural network (ANN). The strategy to tolerate both abovementioned type of failure on any location after detection is proposed by implementing a novel redundant architecture in conventional five-level inverter. This architecture has an advantage of utilising less device count to tolerate fault on single as well as multiple switch combinations. The proposed work is studied in MATLAB/Simulink and validated experimentally.

IGBT open-circuit fault detection for voltage source inverters using DC bus magnetic field signal

This paper proposes a detection method of open-circuit fault of insulated-gate bipolar transistor in the voltage source inverters. The magnetic field signal at the DC bus of the inverter is collected and analysed to detect the fault. First, the simulation is developed for a voltage source inverter-fed induction machine drive which operates in healthy state and single switch open-circuit conditions. The faulty characteristic frequencies in the spectrum of DC-link current signal are derived on the basis of the power balance analysis through the inverter. Second, laboratory tests are implemented with a test bed of voltage source inverter-based induction machine drive in which a Hall sensor suited for the geometry complexity of the DC bus structure is utilized for measuring the magnetic field signal, which can be considered as an image of the simulated DC-link current. The fast Fourier transform of the magnetic field signal shows sharp increases in spectrum amplitude at the fundamental, second-order and third-order harmonics that they can be used as the indication to detect the fault. The approach using proposed signal offers several advantages such as single-sensor requirement, non-invasive and less costly device.

Time-Domain Characterization and Detection of Open Circuit Faults for H-Bridge Power Cell

This article presents the time-domain characterization of semiconductor open-circuit switch faults (OCSFs), such as an open switch with a healthy diode and switch–diode pair open for the H-bridge power cell. The inverter fault signatures under diagonally opposite open switch fault conditions with a healthy diode are approximately similar; therefore, this article presents a detection algorithm with a unique identification of each faulty switch within the H-bridge power cell. The proposed algorithm is also designed to detect and identify multiple OCSFs. The nonideal characteristics of semiconductor switches are considered for the identification of switch faults. The well-known unipolar sinusoidal pulsewidth modulation technique is used for the switching of semiconductor devices for the single power cell. The mathematical expressions have also been derived to find out the effect of the switch fault using a double Fourier integral solution and the switching states. The analytical expressions have been developed for the switched output voltage waveforms under ideal switching conditions. The behavior of the switch faults has been analyzed using inverter output voltage, load current, and total harmonic distortion of the pulsewidth-modulated inverter output voltage.

Open Circuit Fault Detection and Switch Identification for LS-PWM H-Bridge Inverter

The increases in number of power semiconductor devices in multilevel inverters increase the probability of fault occurrence and resulting the reduction in the system reliability. The semiconductor switch faults reduce the production quality and with increased duration of fault occurrence may also be the reason for complete system damage. In H-bridge inverters, the fault signatures of diagonally opposite switch fault conditions are approximately similar. Therefore, a fast fault detection with accurate switch identification technique is required. This brief presents a novel fast fault detection with accurate switch identification technique for an H-bridge inverter. The open switch fault with healthy diode is considered for the analysis. The non-ideal characteristics of semiconductor switches are used to identify open switch fault. This brief also proposed a switching time-domain open circuit fault detection technique. The pulse-width modulated inverter (PWMI) output voltage and load current have been used for detection and identification of the switch faults. The level-shifted pulse width modulation (LS-PWM) technique is used for three-level inverter voltage output.

Open‐circuit fault diagnosis method for three‐level neutral point clamped inverter based on instantaneous frequency of phase current

Because the three-level neutral point clamped (NPC) inverter has the advantages of a large output capacity and high output voltage, it is widely used in wind energy and solar energy power generation. Unfortunately, the three-level NPC inverter often suffers from open-circuit faults, which leads to system security problems and great economic losses. To guarantee the secure operation of the three-level NPC inverter, an open-circuit fault diagnosis method for a three-level NPC inverter based on the instantaneous frequency (IF) of the phase current is proposed here. First, different open-circuit fault signals of the NPC inverter are analysed. Then, the IF of the phase current is used to obtain the fault diagnosis variables. Simultaneously, the Hilbert transform (HT) is used to estimate the IF of the phase current, which carries the information of open-circuit faults. Meanwhile, the average value of the normalised current is provided to locate faulty switches. Finally, by combining the diagnostic variables with the identification threshold, the detection and localisation of open-circuit faults in the NPC three-level inverter are determined. Compared to other fault diagnosis methods, the proposed method is more stable and makes it easier to diagnose open-circuit faults. The correctness and robustness of the method are verified by simulation results.