Incipient Fault Diagnosis for DC–DC Converter Based on Multi-Dimensional Feature Fusion
Author:
Affiliation:
1. Space Engineering University, Beijing, China
2. Astronaut Center of China, Beijing, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10147122.pdf?arnumber=10147122
Reference26 articles.
1. Data-Driven Fault Classification for Non-Inverting Buck–Boost DC–DC Power Converters Based on Expectation Maximisation Principal Component Analysis and Support Vector Machine Approaches
2. Soft Fault Diagnosis for DC-DC Converters with Wavelet Transform and Fuzzy Cerebellar Model Neural Networks
3. Online Anomaly Detection in DC/DC Converters by Statistical Feature Estimation Using GPR and GA
4. Incipient fault diagnosis method for DC–DC converters based on sensitive fault features
5. Data-Driven Parameter Fault Classification for A DC–DC Buck Converter
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. Switch Open-Circuit Fault Diagnosis Method Using Bridge Arm Midpoint Voltage Integral for LLC Resonant Converter;IEEE Transactions on Power Electronics;2024-10
2. Soft Fault Diagnosis for DC–DC Converter Based on Improved ResNet-50;IEEE Access;2023
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