Universiti Teknologi Malaysia Institutional Repository

Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC

Harun, Noorlisa and Ibrahim, Kamarul Asri (2004) Fault detection and diagnosis, FDD via improved univariate statistical process control charts, USPC. In: 18th Symposium of Malaysian Chemical Engineers (SOMChe) 2004, 13 - 14 Dec. 2004, UTP, Perak, Malaysia.

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Abstract

A new approach for detecting and diagnosing fault via correlation technique is introduced in this study. The correlation coefficient is determined using multivariate analysis technique, Partial Correlation Analysis (PCorrA). Individual charting technique such as Shewhart, Exponential Weight Moving Average (EWMA), and Moving Average and Moving Range (MAMR) charts are a used to facilitate the Fault Detection and Diagnosis (FDD). A precut multi component distillation is used as the case study in this work. Based on the result from this study Shewhart control chart gives the best performance with the highest FDD efficiency.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Exponential weight moving average (EWMA) chart, fault detection and diagnosis (FDD), moving average and moving range (MAMR) chart, partial correlation Analysis (PcorrA), Shewhart chart
Subjects:T Technology > T Technology (General)
Divisions:Chemical and Natural Resources Engineering (Formerly known)
ID Code:5943
Deposited By: Norhani Jusoh
Deposited On:29 Jul 2008 06:25
Last Modified:01 Jun 2010 15:36

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