About this document
Hybrid CNN-LSTM for Predictive Maintenance by S. Chaitanya is a document available to read on EtoBox.
This document presents an IoT-based vibrational monitoring system for predictive maintenance of industrial equipment, utilizing a hybrid deep learning model that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for improved remaining useful life (RUL) prediction of aircraft engines. The model is trained on the NASA C-MAPSS dataset and demonstrates superior accuracy compared to standalone models, achieving low error rates in RUL estimation. The findings indicate the eff
- Author
- S. Chaitanya
- Language
- EN