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Development of AGV as test bed for fault detection

Modern machines are still susceptible to faults and breakdown. On the onset of Industry 4.0, machines are equipped with various sensors. This paper describes the development of an (Automated Guided Vehicle) AGV to be used as a test bed to simulate fault condition and generate sensor data which can b...

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Main Authors: Dares, Marvin, Goh, Kai Woon, Koh, Ye Sheng, Yeong, Che Fai, Eileen Su, Eileen Su, Tan, Ping Hua
Format: Conference or Workshop Item
Published: 2020
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/92964/
http://dx.doi.org/10.1109/ICCAR49639.2020.9107977
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spelling my.utm.929642021-11-07T05:55:08Z http://eprints.utm.my/id/eprint/92964/ Development of AGV as test bed for fault detection Dares, Marvin Goh, Kai Woon Koh, Ye Sheng Yeong, Che Fai Eileen Su, Eileen Su Tan, Ping Hua TK Electrical engineering. Electronics Nuclear engineering Modern machines are still susceptible to faults and breakdown. On the onset of Industry 4.0, machines are equipped with various sensors. This paper describes the development of an (Automated Guided Vehicle) AGV to be used as a test bed to simulate fault condition and generate sensor data which can be used to generate fault detecting models. The AGV is a two wheels diiferential drive mobile robot with motor on each wheel. The AGV is controlled by a microcontroller board connected to a Single Board Computer (SBC). Sensors are installed to monitor the performance of the AGV and the data generated by these sensors are logged to the SBC. The AGV and its sensors are tested. The AGV is functional, can simulate simple fault and fault detection. 2020 Conference or Workshop Item PeerReviewed Dares, Marvin and Goh, Kai Woon and Koh, Ye Sheng and Yeong, Che Fai and Eileen Su, Eileen Su and Tan, Ping Hua (2020) Development of AGV as test bed for fault detection. In: 6th International Conference on Control, Automation and Robotics, ICCAR 2020, 20 - 23 April 2020, Singapore. http://dx.doi.org/10.1109/ICCAR49639.2020.9107977
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Dares, Marvin
Goh, Kai Woon
Koh, Ye Sheng
Yeong, Che Fai
Eileen Su, Eileen Su
Tan, Ping Hua
Development of AGV as test bed for fault detection
description Modern machines are still susceptible to faults and breakdown. On the onset of Industry 4.0, machines are equipped with various sensors. This paper describes the development of an (Automated Guided Vehicle) AGV to be used as a test bed to simulate fault condition and generate sensor data which can be used to generate fault detecting models. The AGV is a two wheels diiferential drive mobile robot with motor on each wheel. The AGV is controlled by a microcontroller board connected to a Single Board Computer (SBC). Sensors are installed to monitor the performance of the AGV and the data generated by these sensors are logged to the SBC. The AGV and its sensors are tested. The AGV is functional, can simulate simple fault and fault detection.
format Conference or Workshop Item
author Dares, Marvin
Goh, Kai Woon
Koh, Ye Sheng
Yeong, Che Fai
Eileen Su, Eileen Su
Tan, Ping Hua
author_facet Dares, Marvin
Goh, Kai Woon
Koh, Ye Sheng
Yeong, Che Fai
Eileen Su, Eileen Su
Tan, Ping Hua
author_sort Dares, Marvin
title Development of AGV as test bed for fault detection
title_short Development of AGV as test bed for fault detection
title_full Development of AGV as test bed for fault detection
title_fullStr Development of AGV as test bed for fault detection
title_full_unstemmed Development of AGV as test bed for fault detection
title_sort development of agv as test bed for fault detection
publishDate 2020
url http://eprints.utm.my/id/eprint/92964/
http://dx.doi.org/10.1109/ICCAR49639.2020.9107977
_version_ 1717093399725604864
score 13.211869

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