Bearing fault diagnosis using extreme learning machine based on artificial gorilla troops optimizer

• Main Authors: Isham, Muhd. Firdaus, Saufi, Mohd Syahril Ramadhan, Abu Hasan, Muhammad Danial, Abdul Saad, Wan Aliff, Leong, Muhammad Salman, Lim, Meng Hee, Ahmad, Zair Asrar
• Format: Conference or Workshop Item
• Published: 2023
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/108293/; http://dx.doi.org/10.1007/978-981-19-8703-8_8
• Institution: Universiti Teknologi Malaysia

Bearing diagnosis is important to ensure smooth machinery operation and safety. Machine learning methods have been used widely in bearing diagnosis study, and one of the recent methods used is an extreme learning machine (ELM). The ELM method offers ease of implementation, rapid learning rate, and b...