A Machine Learning Approach for Fault Detection and Diagnosis in Four-legged Inverters-Reference-Cited by-同舟云学术

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A Machine Learning Approach for Fault Detection and Diagnosis in Four-legged Inverters

Published:2023-04-27 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Kansas Power and Energy Conference (KPEC)
language:
Short-container-title:

Author:

Peykarporsan Rasool¹,Heidary Jalal²,Oshnoei Soroush¹,Lie Tek Tjing³

Affiliation:

1. Shahid Beheshti University of Tehran,dept. Electrical Engineering,Tehran,Iran

2. Amirkabir University of Technology,dept. Electrical Engineering,Tehran,Iran

3. Auckland University of Technology,School of Engineering, Computer and Mathematical Sciences,Auckland,new zealand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10215098/10215099/10215460.pdf?arnumber=10215460

Reference31 articles.

1. An FCS-MPC-based open-circuit and current sensor fault diagnosis method for traction inverters with two current sensors

2. Online Signal-Based Fault Detection and Diagnosis of EV Inverter During WLTP Driving Cycle

3. Effective Random Forest-Based Fault Detection and Diagnosis for Wind Energy Conversion Systems

4. Three-Level NPC Inverter Incipient Fault Detection and Classification using Output Current Statistical Analysis

5. Fault diagnosis of rolling element bearing with intrinsic mode function of acoustic emission data using APF-KNN

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multiple Open-Switch Fault Diagnosis for Three-Phase Four-Leg Inverter Under Unbalanced Loads via Interval Sliding Mode Observer;IEEE Transactions on Power Electronics;2024-06

2. Detection of Abnormal Operation of PV Inverters Based on Regressive Prediction Models With Recursive Least Squares Training;IEEE Journal of Emerging and Selected Topics in Industrial Electronics;2024-01

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