Fault diagnosis of modular multilevel converter based on 1DCNN and LSTM network

Author:

Ke Longzhang1,Yang Yuqing1,Liu Xiaojun1,Liu Yi1

Affiliation:

1. Huanggang Normal University,School of Electromechanical and Automobile Engineering,Huanggang,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Reference16 articles.

1. Diagnosis and Location of Open-Circuit Fault in Modular Multilevel Converters Based on High-order Harmonic Analysis. Diagnosis and location of open-circuit fault in modular multilevel converters based on high-order harmonic analysis;ke;Technical Gazette,2020

2. Fault diagnosis with synchrosqueezing transform and optimized deep convolutional neural network: An application in modular multilevel converters

3. Diagnosis and location of the open-circuit fault in modular multilevel converters: An improved machine learning method

4. Degradation assessment of bearings with trend-reconstruct-based features selection and gated recurrent unit network

5. Remaining Useful Life Prediction of Lithium-ion Batteries with Adaptive Unscented Kalman Filter and Optimized Support Vector Regression;xue;Neurocomputing,2019

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1. Data-Based Soft Fault Diagnosis of a Three-Phase DC/AC Converter;2024 IEEE 7th International Electrical and Energy Conference (CIEEC);2024-05-10

2. Artificial Intelligence Applications in the Control and Performance Improvement of Modular Multilevel Converters: A Review;2023 IEEE 14th International Conference on Power Electronics and Drive Systems (PEDS);2023-08-07

3. Hybrid MQTTNet: An Intrusion Detection System Using Heuristic-Based Optimal Feature Integration and Hybrid Fuzzy with 1DCNN;Cybernetics and Systems;2022-11-17

4. Fault Diagnosis and Location Approach of Modular Multilevel Converter Based on Dual One-Dimensional Convolutional Neural Network;2022 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC Asia-Pacific);2022-10-28

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