Multiple device open circuit fault diagnosis for neutral-point-clamped inverters

Sital-Dahone, Marina; Saha, Apama; Sözer, Yilmaz; Mpanda, Augustin

doi:10.1109/apec.2017.7931065

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…In this signal, data such as current or voltage or both signals are directly used as fault signature information. Current-based fault diagnostic methods [18,[24][25][26][27][28][29][30][31][32][33][34][35][36][37][38] are more popular as they do not require any extra hardware. Some authors used voltage-based fault diagnostic methods [39][40][41][42][43][44][45][46].…”

Section: Signal Processing-based Fault Diagnostic Methodsmentioning

confidence: 99%

A Review of Open-Circuit Switch Fault Diagnostic Methods for Neutral Point Clamped Inverter

et al. 2022

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Due to numerous advantages, a neutral point clamped (NPC) inverter is a preferred choice for high-power applications and renewable technology. The reliability of the NPC inverter is a major concerning factor during the assessment of system performance as power semiconductor switches are vulnerable to abnormal conditions. Open-circuit (OC) switch faults are not as dangerous as short circuit (SC) faults but eventually have enough potential to cause cascaded failure to other components in the system and thus need to be supervised carefully. The OC faults result in a distortion of voltage and current signals in the NPC converter. Based on these signals, over the past few years, many efforts have been made to identify and localize the OC switch fault to the switch level in the NPC topology. In this paper, a review of different OC switch fault diagnostic methods is provided. Starting from the NPC inverter operation under healthy and faulty conditions, the various possible and unavailable switching states along with the deviation in pole voltage under different switch fault conditions is discussed. Then, based on the approach used for system-based fault detection, the OC fault detection methods are classified. The various OC methods are further discussed on the basis of signal, i.e., current, voltage or a combination of both signals used as a signature for fault detection. Emphasis is given to the principle involved, diagnostic variables utilized, the implementation approach and the diagnostic time required. Finally, the approaches are tabulated so as to provide a quick reference for NPC fault diagnostics.

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Section: Signal Processing-based Fault Diagnostic Methodsmentioning

confidence: 99%

A Review of Open-Circuit Switch Fault Diagnostic Methods for Neutral Point Clamped Inverter

et al. 2022

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“…In comparison to conventional two-level inverters, multilevel inverters generate lower harmonic voltage/current, since they are characterized by a multilevel quasi-sinusoidal waveform. Various multilevel inverter topologies have been proposed in the literature, such as the PUC5 topology [1][2][3][4][5][6][7][8][9][10][11][12][13], which was introduced to provide good quality power and reduce the number of components compared to its predecessors. Insulated gate bipolar transistors (IGBT) are typically used as power switches in multilevel inverters due to their high voltage and current ratings.…”

Section: Introductionmentioning

confidence: 99%

“…A three-phase current analysis for diagnosing the open-circuit faults for single and multiple switches is presented [3]. The method is based on normalized mean current park's vector modulus, and an angle that involves only three-phase output current was proposed in Reference [4]. A cascaded hbridge (CHB) multilevel inverter can be diagnosed by monitoring each cell's output voltage and current direction.…”

Section: Introductionmentioning

confidence: 99%

Open-Circuit Fault Detection in a Multilevel Inverter Using Sub-Band Wavelet Energy

Khan

Shees²,

Alsharekh

et al. 2021

Electronics

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Recent research has focused on sustainable development and renewable energy resources, thus motivating nonconventional cutting-edge technology development. Multilevel inverters are cost-efficient devices with IGBT switches that can be used in ac power applications with reduced harmonics. They are widely used in the power electronics industry. However, under extreme stress, the IGBT switches can experience a fault, which can lead to undesirable operation. There is a need for a reliable system for detecting switch faults. This paper proposes a signal processing method to detect open-circuit problems in IGBT switches. Relative wavelet energy has been used as a feature for a machine learning algorithm to diagnose and classify the faulted switches. The switching sequence can be altered to restore a healthy output voltage. Inverter faults have been diagnosed by using support vector machine (SVM) and decision tree (DT), and an ensemble model based on decision tree (DT) and XG boost algorithm was developed, which yielded 92%, 88%, and 94.12% accuracy, respectively.

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“…In [12], an open-circuit fault diagnosis method based on the normalized mean current Park's Vector Modulus (PVM) and angle was proposed. In [13], the average current parking vector was used to construct a three-level NPC signature table for possible fault conditions. A converter-based hybrid logic dynamic (MLD) model was used to estimate the opencircuit fault of grid current in [14].…”

Section: Introductionmentioning

confidence: 99%

NPC Three-Level Inverter Open-Circuit Fault Diagnosis Based on Adaptive Electrical Period Partition and Random Forest

Liu

Wan

et al. 2020

Journal of Sensors

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Fault detection can increase the reliability and efficiency of power electronic converters employed in power systems. Among the converters in the power system, a Neutral Point Clamped (NPC) three-level inverter is most commonly used to drive electric motors. In this paper, a new approach for open-circuit fault detection and location of the NPC three-level inverter for a shifting process using a constant voltage-to-frequency ratio is proposed. In order to diagnose open-circuit fault in as short a time as possible, an adaptive electrical period partition (AEPP) algorithm is proposed to pick single electrical periods from real-time three-phase current signals. The Maximal Overlap Discrete Wavelet Transformation (MODWT) and Park’s Vector Modulus (PVM) are used for feature analysis and normalization of electrical period signals. The statistical characteristics of the electrical period signals are extracted, and a random forest model is constructed to realize the state classification. Compared with the traditional fault diagnosis method, the proposed algorithm finds fault locations quickly and accurately. The effectiveness and accuracy of the proposed algorithm are verified by experiments.

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Multiple device open circuit fault diagnosis for neutral-point-clamped inverters

Cited by 7 publications

References 10 publications

A Review of Open-Circuit Switch Fault Diagnostic Methods for Neutral Point Clamped Inverter

A Review of Open-Circuit Switch Fault Diagnostic Methods for Neutral Point Clamped Inverter

Open-Circuit Fault Detection in a Multilevel Inverter Using Sub-Band Wavelet Energy

NPC Three-Level Inverter Open-Circuit Fault Diagnosis Based on Adaptive Electrical Period Partition and Random Forest

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