Blar i NTNU Open på forfatter "Yin, Shen"
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A Data-Driven Approach for Fault Classification of a Manufacturing Process
Yousefi, Sina (Master thesis, 2022)Fault diagnosis is among the most crucial steps in maintenance strategies to sustain the health of machine tools. Traditionally, fault diagnosis was performed based on engineers' vast expertise and technical understanding. ... -
Data-driven design for fault prognosis: Application to industrial components, subsystems, and systems
Alfarizi, Muhammad Gibran (Doctoral theses at NTNU;2023:419, Doctoral thesis, 2023)Technical processes in diverse industries, like manufacturing, chemicals, and power generation, involve intricate operations that aim to achieve specific outcomes. These operations often entail complex interactions among ... -
Intelligent Fault Diagnosis of Manufacturing Processes Using Extra Tree Classification Algorithm and Feature Selection Strategies
Yousefi, Sina; Yin, Shen; Alfarizi, Muhammad Gibran (Journal article; Peer reviewed, 2023)Fault diagnosis is integral to maintenance practices, ensuring optimal machinery functionality. While traditional methods relied on human expertise, intelligent fault diagnosis techniques, propelled by machine learning ... -
A Novel Subspace-Aided Fault Detection Approach for the Drive Systems of Rolling Mills
Huo, Mingyi; Luo, Hao; Yin, Shen; Jiang, Yuchen; Kaynak, Okyay (Journal article; Peer reviewed, 2021)This brief proposes a subspace-aided fault detection approach for the drive systems of strip rolling mills. Considering the impact of the unknown periodic load generated by the strip rolling process, the primary contributions ... -
Optimizing the Inspection Schedule of an Offshore Wind Turbine with Reinforcement Learning
Røn, Ole Daniel Trandheim (Master thesis, 2023)Denne rapporten søker å utforske hvordan forsterket læring (RL) kan anvendes til å redusere vedlikeholdskostnader for offshore vindturbiner. Den valgte tilnærmingen er å optimalisere inspeksjonsplanleggingen, og å utforske ... -
Quo vadis artificial intelligence?
Jiang, Yuchen; Li, Xiang; Luo, Hao; Yin, Shen; Kaynak, Okay (Peer reviewed; Journal article, 2022)The study of artificial intelligence (AI) has been a continuous endeavor of scientists and engineers for over 65 years. The simple contention is that human-created machines can do more than just labor-intensive work; they ... -
Study on the Performance of Machine Learning Algorithms as Surrogate Models for a Representative Model
Espinoza Guzmán, José Nicolás (Master thesis, 2023)Nå til dags blir modellering og simulering mye brukt innen ingeniørfagene, både for produktive formål og forskning. Dette representerer en svært viktig disiplin, spesielt innen vitenskapelige og designfag. Modellenes ... -
Study on Uncertainty Quantification in Deep Learning and its Influence on AI-Enabled Decision-Making
Fosen, Thomas Lunde (Master thesis, 2023)Moderne fremskritt innen maskinlæring og kunstig intelligens har understreket behovet for pålitelige og effektive sikkerhetsrutiner knyttet til implementeringen av slike systemer i virkelighetsnære applikasjoner, da skade ... -
Use of Federated Learning and Neural Networks for Equipment Failure Detection
dos Santos, Luis Flavio Loureiro (Master thesis, 2023)This thesis aims to study and test the federated learning approach to predict the remaining useful life of operating machines. Federated learning is a method associated with a machine learning process to distribute the ...