Parsimonious network based on a fuzzy inference system (PANFIS) for time series feature prediction of low speed slew bearing prognosis

• Main Authors: Caesarendra, Wahyu, Pratama, Mahardhika, Kosasih, Buyung, Tjahjowidodo, Tegoeh, Glowacz, Adam
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Computer science and engineering; Engineering::Mechanical engineering; Prognosis; Slew Bearing
• Online Access: https://hdl.handle.net/10356/164885
• Institution: Nanyang Technological University

In recent years, the utilization of rotating parts, e.g., bearings and gears, has been continuously supporting the manufacturing line to produce a consistent output quality. Due to their critical role, the breakdown of these components might significantly impact the production rate. Prognosis, which...