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Predictive Maintenance with MATLAB

CODE MLPM
  • Training Time 2 Day
  • Training Level Basic Medium Advanced
  • Who Should AttendEngineers, Designers, Academics, Students
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  • SORU SOR
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AMAÇLARI

This two-day course focuses on data analytic, signal processing, and machine learning techniques needed for predictive maintenance and condition monitoring workflows. Attendees will learn about importing, preprocessing, organizing data. Using signal processing techniques to extract time- frequency information. Estimate Remaining Useful Life (RUL) and apply machine learning techniques. Build flexible user interfaces to monitor conditions and visualize results.

TRAINING CONTENT

  • Importing and organizing data
  • Creating custom visualizations
  • Creating classification and regression models
  • Preprocessing to improve data quality, including filling data gaps, resampling, smoothing, aligning signals, finding and removing outliers, and handling non-uniformly sampled signals
  • Estimating Remaining Useful Life
  • Laying out apps in the App Designer environment
  • Creating and updating graphical objects in apps

REQUIREMENTS

  • MATLAB Fundamentals