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http://dx.doi.org/10.5757/JKVS.2011.20.3.165

Study on Vacuum Pump Monitoring Using Adaptive Parameter Model  

Lee, Kyu-Ho (Engineering Research Institute, Department of Mechanical and Aerospace Engineering, Seoul National University)
Lee, Soo-Gab (Engineering Research Institute, Department of Mechanical and Aerospace Engineering, Seoul National University)
Lim, Jong-Yeon (Korea Research Institute of Standards and Science)
Cheung, Wan-Sup (Korea Research Institute of Standards and Science)
Publication Information
Journal of the Korean Vacuum Society / v.20, no.3, 2011 , pp. 165-175 More about this Journal
Abstract
This paper introduces statistical features observed from measured batch data from the multiple operation state variables of dry vacuum pumps running in the semiconductor processes. The amplitude distribution characteristics of such state variables as inlet pressures, supply currents of the booster and dry pumps, and exhaust pressures are shown to be divided into two or three distinctive regions. This observation gives an idea of using an adaptive parametric model (APM) chosen to describe their statistical features. This modelling, in comparison to the traditional dynamic time wrapping algorithm, is shown to provide superior performance in computation time and memory resources required in the preprocessing stage of sampled batch data for the diagnosis of running dry vacuum pumps. APM model-based batch data are demonstrated to be very appropriate for monitoring and diagnosing the running conditions of dry vacuum pumps.
Keywords
Vacuum pump; Diagnosis; PCA; APM; State variables;
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Times Cited By KSCI : 2  (Citation Analysis)
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