Early Detection of Faillure in Conveyor Chain Systems by Wireless Sensor Node

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet


  • Ghada Bouattour
  • Lidu Wang
  • Sajidah Al-Hammouri
  • Jiachen Yang
  • Christian Viehweger
  • Olfa Kanoun

In the ever-growing industrial landscape, the early detection of failures in machines with high accuracy becomes more and more crucial and essential to safe and dependable operations. Based on this concept, a machine learning algorithm is investigated for early detection of failure for conveyor chain systems. The proposed approach is based on the integration of wireless sensor nodes in the conveyor chain to measure the vibrations. The collected data has been acquired in different working conditions including slight imbalances as well as early failure scenarios that do affect the plastic chain. The data was collected using a conveyor chain with a length of 2 meters and with programmable speed and movement scenarios. Furthermore, different loads and forces have been considered during the data collection to mimic real applications in the lab. The selection of features to avoid correlation between them is considered. After comparison between different machine learning algorithms, the C-SVM algorithm is selected with an accuracy of 96.5%, which guarantees high precision and selectivity to the failures.

TitelIEEE SENSORS 2023 : Conference Proceedings
Anzahl der Seiten4
VerlagInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)979-8-3503-0388-9
ISBN (elektronisch)979-8-3503-0387-2
PublikationsstatusErschienen - 2023
Extern publiziertJa
Veranstaltung2023 IEEE SENSORS, SENSORS 2023 - Vienna, Österreich
Dauer: 29.10.202301.11.2023