Fault Detection Method for DG Disconnection in Inverter-Interfaced Microgrids with Photovoltaic System

2016 ◽

Vol 7 (4) ◽

pp. 1294 ◽

Cited By ~ 2

Author(s):

Bilal Boudjellal ◽

Tarak Benslimane

Keyword(s):

Fault Detection ◽

Detection Method ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Mean Value ◽

Boost Converter ◽

Photovoltaic System ◽

Current Form ◽

Fault Indicator ◽

Open Switch

This paper presents the study of an open switch fault tolerant control of a grid-connected photovoltaic system. The studied system is based on the classical DC–DC boost converter and a bidirectional 6-pulse DC–AC converter. The objective is to provide an open-switch fault detection method and fault-tolerant control for both of boost converter and grid-side converter (GSC) in a grid-connected photovoltaic system. A fast fault detection method and a reliable fault-tolerant topology are required to ensure continuity of service, and achieve a faster corrective maintenance. In this work, the mean value of the error voltages is used as fault indicator for the GSC, while, for the boost converter the inductor current form is used as fault indicator. The fault-tolerant topology was achieved by adding one redundant switch to the boost converter, and by adding one redundant leg to the GSC. The results of the fault tolerant control are presented and discussed to validate the proposed approach under different scenarios and different solar irradiances.

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ANOVA fault detection method in photovoltaic system

2020 7th International Conference on Control, Decision and Information Technologies (CoDIT) ◽

10.1109/codit49905.2020.9263843 ◽

2020 ◽

Author(s):

T. ANDRIANAJAINA ◽

D.T. RAZAFIMAHEFA ◽

N. HERAUD ◽

E.J.R. SAMBATRA

Keyword(s):

Fault Detection ◽

Detection Method ◽

Photovoltaic System

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A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset207430 ◽

2020 ◽

pp. 129-139

Author(s):

Weihai Sun ◽

Lemei Han

Keyword(s):

Fault Detection ◽

Signal Analysis ◽

Energy Analysis ◽

Detection Method ◽

Sound Signal ◽

Practical Significance ◽

Time Frequency ◽

Detection Approach ◽

Machine Fault ◽

Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

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