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Open-Circuit Fault Analysis and Recognition in Three-Level Inverters Based on Recurrence Plot and Convolution Neural Network

Power electronics is vital to modern infrastructure, but it is susceptible to open-circuit faults that can cause serious damage. Three-level inverters are commonly used in such equipment, but their high sensitivity and probability of failure make them particularly challenging to diagnose. In this gr...

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Bibliographic Details
Published in:International transactions on electrical energy systems 2023, Vol.2023, p.1-17
Main Authors: Yan, Jianjun, Huang, Yanxing, Yuan, Shuai, Lu, Yufan, Yu, Zeyu
Format: Article
Language:English
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Summary:Power electronics is vital to modern infrastructure, but it is susceptible to open-circuit faults that can cause serious damage. Three-level inverters are commonly used in such equipment, but their high sensitivity and probability of failure make them particularly challenging to diagnose. In this groundbreaking study, we present a new method for accurately detecting and locating open-circuit faults in three-level, neutral-clamped inverters. Using advanced simulation tools and nonlinear dynamic methods, we develop a new diagnostic model that outperforms existing fault classification algorithms. By converting the current signal into an unthreshold recurrence plot (URP) and mapping its nonlinear features to a two-dimensional plane, it is possible to extract key spatial information and train a residual neural network model for fault diagnosis. The method represents a major advance in power electronics and has the potential to save equipment from costly damage. By accurately detecting and locating open-circuit faults in three-level inverters, the reliability and safety of power electronics can be guaranteed for years to come.
ISSN:2050-7038
2050-7038
DOI:10.1155/2023/4755960