A model based approach for fault diagnosis in converter of photovoltaic systems

Chavan, Shamkumar; Chavan, Mahesh S.

doi:10.1109/gcwcn.2014.7030859

Cited by 12 publications

(9 citation statements)

References 5 publications

(3 reference statements)

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“…Therefore, timely detection and treatment of faults at an early stage can effectively increase the safety and reliability of train operations. As effective tools, model-based and data-driven fault detection (FD) methods are widely used [2][3][4][5] . As we have observed, the FD methods designed by the model have become one of the most advanced methods in the field of transportation [6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Data-driven fault detection for traction systems of high-speed trains based on segmental autoencoder

Zhou

2023

Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023)

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Faults inevitably occur during high-speed train operations and affect the security of the system. In order to improve train reliability, the paper proposes a fault detection (FD) framework for traction systems based on the segmental autoencoder (SAE), and within this framework, the target fault detection work is implemented in combination with a data-driven method base. The main objective of the proposed scheme is to determine the generalized kernel representation based on the knowledge learned from the autoencoder and to complete the construction of a residual generator by means of a special structure to obtain the final FD results. To verify the FD effect of the method on the traction system, the results are verified by a simulation experimental platform to ensure the effectiveness of the method on the target system.

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Section: Introductionmentioning

confidence: 99%

Data-driven fault detection for traction systems of high-speed trains based on segmental autoencoder

Zhou

2023

Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023)

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“…affect the performance of BOS module. Use of model based approach for fault diagnosis in converter of PV system is discussed (6) . References (7)(8)(9)(10)(11) present redundancy based fault diagnosis and tolerant strategies for reliability improvement.…”

Section: Introductionmentioning

confidence: 99%

Simulation paradigm to study circuit performance in presence of component level fault

Chavan¹,

Chavan²

2020

IJST

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“…The detection process is done without threshold setting. Others researchers [22] had the idea to build his approach of IGBT open-circuit fault detection on the monitoring and comparison of the instantaneous RMS value of the current of a DC-DC converter at the rated normal RMS. The significant change in the RMS value relative to the normal RMS is considered as an indication of the fault detection and localization.…”

Section: Introductionmentioning

confidence: 99%

A Combined RMS-MEAN Value Approach for an Inverter Open-Circuit Fault Detection

Khelif

Bendiabdellah

Chérif

2019

Period. Polytech. Elec. Eng. Comp. Sci.

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Currently, with the power electronics evolution, a major research axis is oriented towards the diagnosis of converters supplying induction machines. Indeed, a converter such as the inverter is susceptible to have structural failures such as faulty leg and/or opencircuit IGBT faults. In this paper, the detection of the faulty leg and the localization of the open-circuit switch of an inverter are investigated. The fault detection technique used in this work is based essentially upon the monitoring of the root mean square (RMS) value and the calculation of the mean value of the three-phase currents. In the first part of the paper work, the faulty leg is detected by monitoring the RMS value of the three-phase currents and comparing them to the nominal value of the phase current. The second part, the open-circuit IGBT fault is localized simply by knowing the polarity of the calculated mean value current of the faulty phase.The work is first accomplished using simulation work and then the obtained simulation results are validated by experimental work conducted in our LDEE laboratory to illustrate the effectiveness, simplicity and rapidity of the proposed technique.

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A model based approach for fault diagnosis in converter of photovoltaic systems

Cited by 12 publications

References 5 publications

Data-driven fault detection for traction systems of high-speed trains based on segmental autoencoder

Data-driven fault detection for traction systems of high-speed trains based on segmental autoencoder

Simulation paradigm to study circuit performance in presence of component level fault

A Combined RMS-MEAN Value Approach for an Inverter Open-Circuit Fault Detection

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