Fault Classification of Multi-Variate Time Series Data using 1D CNN 

#machinelearning #faultdetection #dataanalysis #exploratorydataanalysis
#conditionmonitoring #predictivemaintenance
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In this video, we showcase the use of 1D CNN for fault classification of multi-variate time series data in the Tennessee Eastman Process. We explain the challenges of fault detection in complex industrial processes, and how 1D CNN can be used to analyze time series data. Through a step-by-step walkthrough of the data preprocessing, model training, and performance evaluation, viewers will gain a better understanding of the potential of 1D CNN for fault detection and its implications for industrial processes.
I'll leave the link of the video, where we did some data preprocessing techniques : • Detecting Process Faul...
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GitHub (Jupyter Notebook file of this video) - github.com/moh...
dataset link - www.kaggle.com...
Full Playlist - • Machine Learning for F...
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Hello everyone! My name is Mohan, and I'm currently pursuing my PhD in artificial intelligence. My research focuses on fault diagnosis of green hydrogen multi-source hybrid systems, which is an exciting field that contributes to the development of sustainable energy technologies.
E-mail - mohandash96@gmail.com
Google Scholar - scholar.google...
LinkedIn - / balyogi-mohan-dash
GitHub - github.com/moh...