An automated machine learning approach for real-time fault detection and diagnosis

HIGHLIGHTS

• who: Denis Leite and collaborators from the Mekatronik ICAutomacao Ltda, R. Itapeva, a-Imbiribeira, Recife, Brazil Institute of Technological Innovation, University of Pernambuco, R. Benfica, Madalena have published the research: An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis, in the Journal: Sensors 2022, 22, 6138. of /2022/
• what: Keeping in mind the improvement of the manufacturing industry performance by reducing downtime with better fault diagnosis, this work proposes a novel and domainspecific AutoML approach for RT-FDD in DMMs. Once the model is implemented, it can be applied to perform the . . .
  

   

  

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