Notebooks for applying AI/ML to predictive maintenance and industry
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Updated
Jul 16, 2023 - Jupyter Notebook
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.
Predicting really rare positives - a notebook on the pump_sensor data from kaggle. Including both simple indicator based approaches as well as machine learning.
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.
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