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Condition Monitoring of Casting Process using Multivariate Statistical Method

Authors:
Hocine Bendjama
Kaddour Gherfi
Daoud Idiou
Jürgen Bast

Keywords: fault diagnosis; process monitoring; principal component analysis; Q-statistic; Q-residual contribution

Abstract:
Growing demand for higher performance, safety and reliability of industrial systems has increased the need for condition monitoring and fault diagnosis. A wide variety of techniques were used for process monitoring. This study will mainly investigate a technique based on principal component analysis in order to improve the accuracy for fault diagnosis of casting process. The process faults are identified using the following statistical parameters: Q-statistic, also called squared prediction error, and Q-residual contribution. The proposed method is evaluated using real sensor measurements from a pilot scale. The monitoring results indicate that the principal component analysis method can diagnose the abnormal change in the measured data.

Pages: 103 to 107

Copyright: Copyright (c) IARIA, 2014

Publication date: August 24, 2014

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-354-4

Location: Rome, Italy

Dates: from August 24, 2014 to August 28, 2014