대학원_논문_세미나_리뷰_발표(화공,환경,대기,PCA)
- 최초 등록일
- 2011.06.01
- 최종 저작일
- 2010.11
- 16페이지/ MS 파워포인트
- 가격 1,500원
소개글
대학원 시절 세미나 했던 논문 리뷰 발표 자료들입니다. 부담스러운 세미나 시간과 부족한 시간에 준비할 수 있는 발표 자료들 입니다. 약간만 가공하시면 바로 발표 가능한 자료입니다.
목차
1. Introduction
2. Theory
1) Principal Component Analysis (PCA)
2) Statistics
3) Quantitative Risk Assessment
3. Risk Assessment System
1) System Overview
2) Principal Component Analysis (PCA)
4. Case Study
1) Methylamine Process and Process Data
2) Data Analysis and Model Building
3) Fault Detection and Risk Assessment
5. Conclusions
본문내용
This study was performed to develop a Real-Time Risk Monitoring System which helps to do fault detection using the information from plant information systems in a chemical process.
In this study, to do fault detection, principal component analysis
(PCA) methods of multivariate statistical analysis were used.
PCA can reduce the dimension of variables with monitoring process. Therefore, they are known as suitable methods to treat enormous data composed of many dimensions.
The developed Real-Time Risk Monitoring System can analyze and manage the plant information on-line, diagnose causes of
abnormality and so prevent major accidents.
PCA was developed by Pearson in 1901 and used to analyze the relationship between variables by Hotelling.
PCA is one of the multivariate statistical analysis methods that can be used for feature extraction.
Fig.1 shows a data matrix,
where n rows mean observations
or samples and the data matrix
has m variables.
참고 자료
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