Fault diagnosis in diode clamped multilevel inverter drive using wavelet transforms

Vinothkumar, V.; Muniraj, C.

doi:10.1109/icghpc.2013.6533925

Cited by 11 publications

(2 citation statements)

References 8 publications

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“…The park's transform vector pattern is used for the fault diagnosis in the voltage source inverter fed AC drives [5] [6]. The classification of the fault wasdependent on the load characteristics as current is considered for fault detection.The different fault detection methods are reviewed [7], voltage histogram based fault detection is carried out in [8][9].The wavelet analysis of the output voltages and input DC currents for fault diagnosis is carried out in [10][11].Since the current waveform would be a problem when large variation in the loads would lead to misinterpretation the wavelet analysis based fault detection is carried out [12]. Output voltage frequency analysis [13] [14][15] are also proposed which are complex to implement.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Different Meta Heuristics Method in Intelligent Fault Detection of Multilevel Inverter with Photovoltaic Power Generation Source

Manjunath¹,

Kusagur

2018

IJPEDS

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<p>Meta Heuristic methods have made a deep impact in the area of optimization in different streams of engineering. The performance of these algorithms is of importance because the hardware implementation of these algorithms is to be carried out for different engineering applications. As an important application in High Voltage DC (HVDC) transmission and Industrial Drives the multilevel inverter fault diagnosis is carried out using the different meta-heuristic methods with Neural Network as the decision making algorithm. The optimization of the weight and the bias values in the neural network diagnosis system is carried out in order to analyze the performance by means of comparing the Mean Square Error (MSE) while the Neural Network is getting trained for different fault conditions in the multilevel inverter. Matlab based implementation is carried out and the results are tabulated and inferred for a Multilevel Inverter fed from the Photovoltaic power generation system. In order to increase the robustness of the fault detection, with renewable energy based power generation system as the source for the Multilevel Inverter, the feature extracted from the multilevel inverter are positive, negative and zero sequence voltage along with the THD of the output voltage. The optimization algorithm used is Particle Swarm Optimization (PSO), Cuckoo Search Algorithm(CSA), Genetic Algorithm(GA) and Tabu Search Algorithm (TSA).</p>

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Section: Introductionmentioning

confidence: 99%

Analysis of Different Meta Heuristics Method in Intelligent Fault Detection of Multilevel Inverter with Photovoltaic Power Generation Source

Manjunath¹,

Kusagur

2018

IJPEDS

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“…However, fault detection and diagnosis in multilevel inverter found notable movements only in the last decade. Various methods are introduced for fault detection of the converter and/or identification of faulty power semiconductor switch in them, based on current-vector patterns [11], output voltage frequency analysis [12], park's vector approach [13], wavelet transform [14], sliding mode observer [15], mass centre of the voltage pattern [16], normalized phase current and the change of the neutral-point voltage [17] in multilevel inverters.…”

Section: Introductionmentioning

confidence: 99%

Open transistor fault detection in asymmetric multilevel inverter

Raj

George

Jagadanand

2015

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES)

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The number of power semiconductor switches and DC sources will increase with the increase in the number of levels of output voltage of the multilevel inverter. As the number of power semiconductor switches increases, the possibility of its failure and hence the breakdown of the inverter operation also escalate in a nonlinear manner. Hence, the detection of the failure of the power semiconductor switch is of paramount importance, considering the availability and reliability of the system is concerned. The gate unavailability or the transistor open circuit fault detection in asymmetrical multilevel inverter by means of monitoring the mean value of the output voltage is presented in this paper. Simulation of this method is carried out in both binary and trinary combinations of asymmetric multilevel inverter. Keywords-Multilevel inverter (MLI), cascaded H-bridge (CHB), power semiconductor switch fault, fault detection, condition monitoring, asymmetric multilevl inverter.

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Improvement in Fault Clearance Time of the Cascaded H-Bridge Multilevel Inverter Using Novel Technique Based on Frequency Detection

Phukan

Singh

2021

Modeling, Simulation and Optimization

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Fault diagnosis in diode clamped multilevel inverter drive using wavelet transforms

Cited by 11 publications

References 8 publications

Analysis of Different Meta Heuristics Method in Intelligent Fault Detection of Multilevel Inverter with Photovoltaic Power Generation Source

Analysis of Different Meta Heuristics Method in Intelligent Fault Detection of Multilevel Inverter with Photovoltaic Power Generation Source

Open transistor fault detection in asymmetric multilevel inverter

Improvement in Fault Clearance Time of the Cascaded H-Bridge Multilevel Inverter Using Novel Technique Based on Frequency Detection

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