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http://dx.doi.org/10.3795/KSME-A.2017.41.6.517

Real-time Monitoring System for Rotating Machinery with IoT-based Cloud Platform  

Jeong, Haedong (Dept. of System Design and Control, Ulsan Nat'l Institute Science and Technology)
Kim, Suhyun (Dept. of System Design and Control, Ulsan Nat'l Institute Science and Technology)
Woo, Sunhee (Dept. of System Design and Control, Ulsan Nat'l Institute Science and Technology)
Kim, Songhyun (Dept. of System Design and Control, Ulsan Nat'l Institute Science and Technology)
Lee, Seungchul (Dept. of System Design and Control, Ulsan Nat'l Institute Science and Technology)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.41, no.6, 2017 , pp. 517-524 More about this Journal
Abstract
The objective of this research is to improve the efficiency of data collection from many machine components on smart factory floors using IoT(Internet of things) techniques and cloud platform, and to make it easy to update outdated diagnostic schemes through online deployment methods from cloud resources. The short-term analysis is implemented by a micro-controller, and it includes machine-learning algorithms for inferring snapshot information of the machine components. For long-term analysis, time-series and high-dimension data are used for root cause analysis by combining a cloud platform and multivariate analysis techniques. The diagnostic results are visualized in a web-based display dashboard for an unconstrained user access. The implementation is demonstrated to identify its performance in data acquisition and analysis for rotating machinery.
Keywords
Smart Factory; Internet of Things; Cloud Platform; Machine Learning; Rotating Machinery;
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Times Cited By KSCI : 2  (Citation Analysis)
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