A Mold Damage Monitoring Algorithm for Power Metallurgy Molding Machines Using Bidirectional Long Short-Term Memory on an Internet of Things Platform

A Mold Damage Monitoring Algorithm for Power Metallurgy Molding Machines Using Bidirectional Long Short-Term Memory on an Internet of Things Platform

In this paper, an analysis and monitoring algorithm is proposed for mold health evaluation using vibration data. Two inertial measurement units (IMUs) and an embedded system are first used to acquire vibration data from a powder metallurgy molding machine. These data are collected on an Internet of...

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Bibliographic Details
Main Authors: Hao-Pu Lin, Yuan-Chieh Chen, Chin-Chuan Han, Yu-Chi Wu, Jin-Yuan Lin
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Sensors
Subjects:
intelligence system
vibration data
Internet of Things (IoT)
deep learning
inertial measurement unit (IMU)
mean square error
Online Access:https://www.mdpi.com/1424-8220/25/7/2143
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