Challenges and opportunities of deep learning models for machinery fault detection and diagnosis: a review

• Main Authors: Saufi, Syahril Ramadhan, Ahmad, Zair Asrar, Leong, Mohd. Salman, Lim, Meng Hee
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2019
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/89405/1/SyahrilRamadhanSaufi2019_ChallengesandOpportunitiesofDeepLearningModels.pdf; http://eprints.utm.my/id/eprint/89405/; http://dx.doi.org/10.1109/ACCESS.2019.2938227

In the age of industry 4.0, deep learning has attracted increasing interest for various research applications. In recent years, deep learning models have been extensively implemented in machinery fault detection and diagnosis (FDD) systems. The deep architecture's automated feature learning pro...