Tier 2 Case Studies on Data Reconciliation
This article consists of four chapters with three case studies covering the detection and analysis of steady state, nonlinear, and unsteady state problems through the use of computer tools for data reconciliation.
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About Tier 2 Case Studies on Data Reconciliation
PowerPoint presentation about 'Tier 2 Case Studies on Data Reconciliation'. This presentation describes the topic on This article consists of four chapters with three case studies covering the detection and analysis of steady state, nonlinear, and unsteady state problems through the use of computer tools for data reconciliation.. The key topics included in this slideshow are Data Reconciliation, Gross Errors, Observability, Redundancy Analysis, Nonlinear DR,. Download this presentation absolutely free.
Presentation Transcript
1. Tier 2: Case Studies
2. Case Studies Table of Contents Chapter 1 Introduction Useful Computer Tools for Data Reconciliation Chapter 2 Case Study #1 Steady-State Nonlinear DR and Detection of Gross Errors through Analysis Chapter 3 Case Study #2 A Gross Error Detection Problem Using Observability and Redundancy Analysis Chapter 4 Case Study #3 An Unsteady-State Problem
3. Introduction: Useful Computer Tools for Data Reconciliation
4. Introduction Jumping Jiminy Cricket! Excel and MATLAB!?
5. Introduction Matrix Algebra Data Reconciliation MATLAB EXCEL
6. Introduction Some useful syntax in MATLAB: A = AB A T A -1 QR factorization of A QR factorization with permutation A = [1 0 0 1; 0 1 1 0; 1 0 1 1] A*B A inv(A) [Q,R] = qr(A) [Q,R,E] = qr(A)
7. Introduction Some useful syntax in Excel: Suppose A = (cells A1:B2) B = (cells D1:E2) 1 0 0 1 1 1 1 0 Then AB AT A-1 MMULT(A1:B2, D1:E2) TRANSPOSE(A1:B2) MINVERSE(A1:B2)
8. Introduction AB = C In order to calculate C and place it in cells G1:H2: 1) Highlight cells G1:H2 2) Type = MMULT(A1:B2, D1:E2) 3) Press Control, Shift and Enter simultaneously A ( 2 x2), B (2x 2 ) C ( 2 x 2 )
