machinery-condition-monitoring topic
ml-tool-wear
Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as described in article "Self-Supervised Learning for Tool Wear Mo...
cbm_codes_open
This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.
rul_codes_open
This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.
Induction-Motor-Faults-Detection-with-Stacking-Ensemble-Method-and-Deep-Learning
This is a induction motor faults detection project implemented with Tensorflow. We use Stacking Ensembles method (with Random Forest, Support Vector Machine, Deep Neural Network and Logistic Regressio...