Machinery fault diagnosis based on a modified hybrid deep sparse autoencoder using a raw vibration time-series signal.

• Main Authors: Saufi, Syahril Ramadhan, Isham, Muhammad Firdaus, Ahmad, Zair Asrar, Abu Hasan, M. Danial
• Format: Article
• Published: Springer Science and Business Media Deutschland GmbH 2023
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/106231/; http://dx.doi.org/10.1007/s12652-022-04436-1
• Institution: Universiti Teknologi Malaysia

Intelligent fault diagnosis (IFD) is an effective system to ensure the safe operation of mechanical components such as bearings, gears, and blades. The main challenge of IFD using traditional methods lies in finding the good features that reflect the machine conditions that need prior knowledge and...