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primary topic: Noncontact machinery operation status monitoring system with gated recurrent unit model

Noncontact machinery operation status monitoring system with gated recurrent unit model
type: AcademicArticle
type: Article
abstract: In manufacturing industry, assembly line monitoring provides statistical information about overall performance and reliability of the legacy machines, ensuring that the machines give maximum yield output. However, most legacy machines lack internet connectivity and advanced functionality, increasing the difficulty for tracking task. Therefore, this work seeks to introduce a noncontact acoustic method to track machines rather than the mainstream vibrational approach. In order to provide accurate tracking of the daily machine operation for our machine tracking system, we consider scenario of background noises such as environmental sounds from multiple sources as well as neighbouring machine's sound. Thus, several neural networks are employed to recognize the machine status accurately. The objective of our work is to investigate the effect of machine types and states on recognition performance of neural network models under extremely noisy environments as well as to demonstrate the possibility of recognizing the sound on edge device. The main contribution of this article is the proposal of lightweight recurrent and convolutional-based models for machine sound recognition. The experimental results of our extensive testing included with multiple types of machines and background noises show that the proposed system with gated recurrent unit model has the best recognition accuracy of F1 score 0.913 with standard uncertainty of 0.026 with decent inference speed on edge device. © 2022 Turkiye Klinikleri. All rights reserved.
date: 2022
volume: 30
issue: 6
is part of: Turkish Journal of Electrical Engineering and Computer Sciences
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository

Turkiye Klinikleri
type: Organization

Turkish Journal of Electrical Engineering and Computer Sciences
type: Collection
issn: 13000632

Wai Kong Lee
type: Person
given name: Wai Kong
family name: Lee

Boonyaik Yaik Ooi
type: Person
given name: Boonyaik Yaik
family name: Ooi

Soung Yue Liew
type: Person
given name: Soung Yue
family name: Liew

Jason Jing Wei Lim
type: Person
given name: Jason Jing Wei
family name: Lim

Teik Boon Tan
type: Person
given name: Teik Boon
family name: Tan

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primary topic: Noncontact machinery operation status monitoring system with gated recurrent unit model