Thermoremanent Behavior in Synthetic Samples Containing Natural Oxyexsolved Titanomagnetite
Sign Up to like & getrecommendations! Published in 2018 at "Geochemistry, Geophysics, Geosystems"
DOI: 10.1029/2017gc007354
Abstract: Understanding Earth's geodynamo provides us a window into the evolution of the Earth's core, which requires accurate data about how its strength varies with time. Classic Thellier-style paleointensity experiments assume that studied specimens contain only… read more here.
Keywords: synthetic samples; oxyexsolved titanomagnetite; samples containing; behavior synthetic ... See more keywords
Intelligent Condition-Based Monitoring of Rotary Machines With Few Samples
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2020.3008177
Abstract: Recently, intelligent condition based monitoring systems build on deep learning methods have gained popularity. The success of these methods relies upon the large labeled training datasets, which are crucial to collect in industries. Therefore, building… read more here.
Keywords: synthetic samples; condition based; based monitoring; intelligent condition ... See more keywords
A Weakly Supervised Learning-Based Oversampling Framework for Class-Imbalanced Fault Diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Reliability"
DOI: 10.1109/tr.2021.3138448
Abstract: With the lack of failure data, class imbalance has become a common challenge in the fault diagnosis of industrial systems. The oversampling methods can tackle the class-imbalanced problem by generating the minority samples to balance… read more here.
Keywords: synthetic samples; fault diagnosis; class imbalanced; framework ... See more keywords