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

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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Lagazo, Daniel, de Vera, Jose Alfredo, Coronel, Andrei D, Jimenez, Joseph Mark, Gatmaitan, Emman
التنسيق: text
منشور في: Archīum Ateneo 2021
الموضوعات:
CNN
الوصول للمادة أونلاين:https://archium.ateneo.edu/discs-faculty-pubs/316
https://ieeexplore.ieee.org/document/9497816
الوسوم: إضافة وسم
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المؤسسة: Ateneo De Manila University
الوصف
الملخص: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 of defects in the form of anomalous sound. We augmented the facility's CbM system by deploying an acoustic recorder and by building an autoencoder that is trained using the normal sound pressure of the wire extruding machine. This paper discusses a process for sound pressure acquisition, data pre-processing and preparation, feature extraction, anomaly detection, model evaluation, and case studies of downtime incidents. The objective of this paper is to automate the monitoring of the condition of the equipment and to find possible symptoms of unhealthy sound pressure prior to the reported downtimes. A comparative analysis of density score and reconstruction error, our chosen anomaly detection techniques, is presented in this paper.