Open AccessTracking Operation Status of Machines through Vibration Analysis using Motif Discovery.
Author(s) -
Yon-Qing Lee,
Woan Lin Beh,
Boon-Yaik Ooi
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1529/5/052005
Subject(s) - vibration , computer science , work (physics) , process (computing) , work in process , retrofitting , automotive engineering , engineering , reliability engineering , operations management , mechanical engineering , physics , quantum mechanics , operating system , structural engineering
Industrial revolution 4.0 is inevitable for developing countries and created an urgency for many small and medium enterprises (SME) manufacturers to modernize their operations. Unfortunately, the process of modernization is expensive and it may not be justifiable for SMEs. This work is part of our existing effort in developing retrofitting sensors solution to help in reducing the cost and risk of SMEs moving towards Industry 4.0. This work focuses on tracking operation of machine through vibration data. Vibration analysis is not new and there are many existing works especially in the area of machine condition monitoring. This work is different from machine condition monitoring because the aim of this work is to track operation status of machines. The operation status of machines are crucial for manufacturers to manage maintenance and estimate the throughput of their operation. However, the main challenge of tracking operation status is that there are no prior knowledge on the machine’s vibration. The success of Motif Discovery has provided an opportunity to distinguish and identify the operation status of a machine from its vibration with minimal interference to the machine’s operation. This work puts Matrix Profile to test; using 15 sets of vibration data from 2-speed (high and low speed) industrial fan and exhaust hood, with the period for each collection at 10 minutes. From the experimental results, this work showed that it is possible to track the operation status of a machine through its vibration data and the accuracy can be as high as 99%.