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COURSE SYLLABUS

Measurement systems: design, modeling and computational methods 7.5 Credits

Mätsystem: design, modellering och beräkningsmetoder
Second cycle, S7013E
Version
Course syllabus valid: Autumn 2018 Sp 1 - Present
The version indicates the term and period for which this course syllabus is valid. The most recent version of the course syllabus is shown first.

Syllabus established
by Jonny Johansson, HUL SRT 15 Feb 2016

Last revised
by Jonny Johansson, HUL SRT 15 Feb 2018

Education level
Second cycle
Grade scale
G U 3 4 5
Subject
Computer Science and Engineering
Subject group (SCB)
Computer Technology

Entry requirements

Basic circuit theory (E0003E), and mathematical statistics (S0001M). More specifically, good understanding of mathematical analysis, linear algebra, probability density functions, expectations and variance, RLC circuits, Laplace and Fourier transforms is required (M0018M).


More information about English language requirements


Selection

The selection is based on 20-285 credits



Course Aim

After completion of the course, the students shall have knowledge and understanding concerning:

  • Fundamental physical and mathematical principles of a selection of measurement systems.
  • Mathematical and statistical principles necessary for conducting a detailed uncertainty analysis of a specific measurement system, given uncertainties of the system’s components.
  • Methods for design of experiments targeted at the construction of empirical and/or physical models of measurement systems.
  • Fundamental principles of numerical computations for linear and non-linear systems of equations.

After completion of the course, the students shall be able to:

  • Construct basic circuits for measurement of electrical quantities.
  • Use and evaluate numerical computational methods for linear and non-linear systems of equations,  and to apply these methods for estimating parameters of models of measurement systems.
  • Build empirical models of a system and estimate parameters of these.
  • Evaluate models with respect to functionality, reliability, and computational complexity.
  • Motivate and present the results orally and in written reports.  

The students should also be able to judge:

The possibilities and limitations of a given measurement system.

Contents

Measurement technology is a wide area, spanning from modeling of the physical process being studied, through construction of measurement systems, parameter estimation and system identification, to a detailed analysis of data and error sources.

This course focuses primarily on the problem of modeling a process and then identifying model parameters and analysis of the results.

A major part of the course therefore deals with the analysis, since an understanding of how error sources (measurement noise, model errors, etc.) affect the system as a whole.

The practical experience will be given by laborations, where both sensors and basic electronics are assembled and connected to a physical process. The theoretical analysis is then performed using MATLAB, and the results are summarized in written reports.


Realization

The teaching is divided in lectures, problem demonstrations, and practical laborations.   


Examination

Mandatory seminars, project work, and written exam with differentiated grades.


Remarks
The course can be offered in English. This course can not be combined with E7021E.

Examiner
Johan Carlson

Literature. Valid from Autumn 2018 Sp 1 (May change until 10 weeks before course start)
J.E. Carlson, Measurement Systems Engineering: Design, Modeling, and Computational Methods, 1st Ed., JEC E.M.P. 2018.

Course offered by
Department of Computer Science, Electrical and Space Engineering

Items/credits
NumberTypeCreditsGrade
0003Written exam3.0TG G U 3 4 5
0004Laboratory work3.0TG G U 3 4 5
0005Seminars1.5TG U G#