Rethinking Model-based Fault Detection: Uncertainties, Risks, and Optimization Based on a Multilevel Converter Case Study
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https://ieee-dataport.org/documents/rethinking-model-based-fault-detection-uncertainties-risks-and-optimization-based
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资源简介：
This study is utilized for model-based fault detection uncertainty analysis using Monte Carlo simulation. The dataset consists of 8 uncertainty factors and 15 system variables under four operation scenarios. The 1000 sets of uncertainty factor samples are generated randomly as initial configuration of the system. This study is utilized for model-based fault detection uncertainty analysis using Monte Carlo simulation. The dataset consists of 8 uncertainty factors and 15 system variables under four operation scenarios. The 1000 sets of uncertainty factor samples are generated randomly as initial configuration of the system.
提供机构：
Liao, Yantao
