Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.

Notebooks for applying AI/ML to predictive maintenance and industry

A notebook tutorial series for performing predictive maintenance using machine learning

Python code “Jupyter notebooks” for the paper entitled " Similarity-Based Predictive Maintenance Framework for Rotating Machinery" has been presented in the Fifth International Conference on Communications, Signal Processing, and their Applications (ICCSPA’22), Cairo, Egypt, 27-29 December 2022. Techniques used: statistical analysis, FFT, and STFT.

This repository contains a notebook that predicts future values for temperature and pressure, storing the results in a CSV file. These predictions are subsequently used to determine the operational status of a motor. Additionally, the notebook generates visualizations of the predicted temperature and pressure values.

Predicting really rare positives - a notebook on the pump_sensor data from kaggle. Including both simple indicator based approaches as well as machine learning.