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Proceedings ArticleDOI

Fault detection and diagnosis of voltage source inverter using the 3D current trajectory mass center

TLDR
In this paper, the authors used the inverter output currents to obtain a typical pattern in a 3D referential, which is used to detect and identify the faulty power switch.
Abstract
This paper investigates the use of the current trajectory mass center in a three dimensional referential. The proposed approach uses the inverter output currents. These currents are used to obtain a typical pattern in a three dimensional referential. According the fault type different patterns is obtained. In this way, with the proposed approach it is possible to detect and identify the faulty power switch In order to automatically identify the different patterns, it is used an algorithm to obtain a mass center of the 3D current trajectory. This results in a fast and reliable fault detection method. The applicability of the proposed technique, are confirmed through several simulation and experimental results.

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Citations
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Journal ArticleDOI

Short-Circuit Fault Diagnosis for Three-Phase Inverters Based on Voltage-Space Patterns

TL;DR: A fault detection and isolation method for faulty metal-oxide-semiconductor field-effect transistors in a three-phase pulsewidth-modulated (PWM) voltage source inverter that can address the reliability problem of multilevel inverters in renewable electrical generation systems and can dramatically reduce the number of required sensors.
Proceedings ArticleDOI

Fault detection on multilevel power converter based on mass center of the voltage pattern

TL;DR: In this article, a new approach to detect and identify a faulty switch was proposed based on the mass center of the voltages patterns of the power converter output voltages, which is illustrated on a five-level cascaded H-bridge inverter.
Journal ArticleDOI

A Fast Classification Method of Faults in Power Electronic Circuits Based on Support Vector Machines

TL;DR: This paper presents a fast fault classification method for power electronic circuits by using the support vector machine (SVM) as a classifier and the wavelet transform as a feature extraction technique.
Proceedings ArticleDOI

Power Transistor Fault Diagnosis in SRM Drives Based on Indexes of Symmetry

TL;DR: A new fault detection and diagnosis method for transistor faults in a SRM drive based on symmetry indexes that are created from the analysis of the currents patterns, presenting immunity to different mechanical conditions is presented.
Proceedings ArticleDOI

Fault detection and diagnosis of six-phase voltage source inverter using trajectory mass current center

TL;DR: In this article, a fault detection and diagnosis method for a six-phase voltage source inverter (VSI) is proposed based on an equivalent six dimension of a current trajectory mass center of the VSI output currents.
References
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Journal ArticleDOI

A review of induction motors signature analysis as a medium for faults detection

TL;DR: The fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors are introduced.
Proceedings ArticleDOI

Condition monitoring and fault diagnosis of electrical machines-a review

TL;DR: Different types of faults and the signatures they generate and their diagnostics' schemes are described, keeping in mind the need for future research.
Proceedings ArticleDOI

A Literature Review of IGBT Fault Diagnostic and Protection Methods for Power Inverters

TL;DR: This paper presents a survey on existing methods for fault diagnosis and protection of insulated gate bipolar transistors with special focus on those used in three-phase power inverters, based on their performance and implementation efforts.
Journal ArticleDOI

Online Diagnosis of Induction Motors Using MCSA

TL;DR: An online induction motor diagnosis system using motor current signature analysis (MCSA) with advanced signal-and-data-processing algorithms is proposed, able to ascertain four kinds of motor faults and diagnose the fault status of an induction motor.
Journal ArticleDOI

Recent developments of induction motor drives fault diagnosis using AI techniques

TL;DR: A review of the developments in the field of diagnosis of electrical machines and drives based on artificial intelligence (AI) covers the application of expert systems, artificial neural networks (ANNs), and fuzzy logic systems that can be integrated into each other and also with more traditional techniques.
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