A python based tutorial on prognostics and health management using vibration signal: signal processing, feature extraction and feature selection

• Published in: Journal of mechanical science and technology Vol. 36; no. 8; pp. 4083 - 4097
• Main Authors: Sim, Jinwoo, Min, Jinhong, Kim, Doyeon, Cho, Seong Hee, Kim, Seokgoo, Choi, Joo-Ho
• Format: Journal Article
• Language: English
• Published: Seoul Korean Society of Mechanical Engineers 01-08-2022; Springer Nature B.V; 대한기계학회
• Subjects: Control; Dynamical Systems; Engineering; Feature extraction; Industrial and Production Engineering; Matlab; Mechanical Engineering; Original Article; Python; Signal processing; Vibration; Websites; 기계공학; Tutorial; Prognostics and health management (PHM); Signal processing; MATLAB; Feature engineering; Gear; Python; Bearing
• ISSN: 1738-494X; 1976-3824
• DOI: 10.1007/s12206-022-0728-z

MATLAB is a convenient and well-established engineering tool used by many researchers and engineers in implementing the prognostics and health management (PHM). Recently however, Python has emerged as a new language platform for the same purpose due to its advantages of free access, high extensibility and plenty libraries. This paper provides a Python tutorial to aid the beginners in the PHM to implement the signal processing and feature engineering using the open access data of gears and bearings. The Python codes are provided at the web page
https://www.kau-sdol.com
so that they produce the same results as the MATLAB codes. As such, they are reliable as well as of practical value to those who want to learn how to implement the PHM by Python or to migrate from the MATLAB to Python.