Condition-Based Monitoring and Anomaly Detection of Industrial Equipment using Autoencoder

• Main Authors: Lagazo, Daniel, de Vera, Jose Alfredo, Coronel, Andrei D, Jimenez, Joseph Mark, Gatmaitan, Emman
• Format: text
• Published: Archīum Ateneo 2021
• Subjects: Computer science; Wires; Manuals; Feature extraction; Real-time systems; Data models; Manufacturing; Auto-encoder; CNN; wire equipment; MFCC; spectrogram; reconstruction error; density score; condition-based monitoring; anomaly detection; sound pressure; Computer Sciences; Databases and Information Systems; Theory and Algorithms
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/316; https://ieeexplore.ieee.org/document/9497816
• Institution: Ateneo De Manila University

Real-time Condition-based Monitoring (CbM) of wire manufacturing equipment of a partner facility involves the manual process of listening to the sound pressure of the equipment by the personnel assigned to it. This is to prevent further damage and to mitigate costs by monitoring the earliest signs o...