Module also offered within study programmes:
General information:
Name:
Mechatronic system indentification
Course of study:
2013/2014
Code:
RMS-2-104-MD-s
Faculty of:
Mechanical Engineering and Robotics
Study level:
Second-cycle studies
Specialty:
Mechatronic Design
Field of study:
Mechatronics with English as instruction languagege
Semester:
1
Profile of education:
Academic (A)
Lecture language:
English
Form and type of study:
Full-time studies
Course homepage:
 
Responsible teacher:
prof. dr hab. inż. Stepinski Tadeusz (tstepin@agh.edu.pl)
Academic teachers:
Module summary

Description of learning outcomes for module
MLO code Student after module completion has the knowledge/ knows how to/is able to Connections with FLO Method of learning outcomes verification (form of completion)
Skills
M_U001 Can perform experimental modal anamysis MS2A_U12 Report,
Execution of a project,
Execution of laboratory classes,
Completion of laboratory classes
M_U002 Can perform sampling of time-continuous signals and design anti-aliasing filter MS2A_U11, MS2A_U07 Project,
Report,
Execution of laboratory classes,
Completion of laboratory classes
M_U003 Can modify frequency responce of a dynamic structure using Laplace and z-transform MS2A_U07, MS2A_U01 Examination,
Project,
Report,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
M_U004 Can perform analysis of dynamical systems using Matlab MS2A_U07 Project,
Report,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
M_U006 Can design an analog filter and convert it to digital form MS2A_U07 Project,
Report,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
Knowledge
M_W001 Knows and understands relations between signal and system description in time- and frequency domain MS2A_W07 Report,
Execution of a project,
Execution of exercises,
Test results,
Completion of laboratory classes
M_W002 Knows and understands relations between continuous-time and discrete-time descriptions Report,
Execution of exercises,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
M_W003 Has basic knowledge of analog and digital filters MS2A_W01, MS2A_W07 Project,
Report,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
M_W004 Has basic knowledge of nonparametric and parametric spectrum estimation methods MS2A_W01, MS2A_W07 Report,
Execution of a project,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
M_W005 Has basic knowledge of system identification with focus on modal analysis MS2A_W01, MS2A_W07 Report,
Execution of a project,
Execution of laboratory classes,
Test results,
Completion of laboratory classes
FLO matrix in relation to forms of classes
MLO code Student after module completion has the knowledge/ knows how to/is able to Form of classes
Lecture
Audit. classes
Lab. classes
Project classes
Conv. seminar
Seminar classes
Pract. classes
Others
Zaj. terenowe
Zaj. warsztatowe
E-learning
Skills
M_U001 Can perform experimental modal anamysis - - + + - - - - - - -
M_U002 Can perform sampling of time-continuous signals and design anti-aliasing filter + - + + - - - - - - -
M_U003 Can modify frequency responce of a dynamic structure using Laplace and z-transform + - + + - - - - - - -
M_U004 Can perform analysis of dynamical systems using Matlab - - + + - - - - - - -
M_U006 Can design an analog filter and convert it to digital form + - + + - - - - - - -
Knowledge
M_W001 Knows and understands relations between signal and system description in time- and frequency domain + - + + - - - - - - -
M_W002 Knows and understands relations between continuous-time and discrete-time descriptions + - + + - - - - - - -
M_W003 Has basic knowledge of analog and digital filters + - + + - - - - - - -
M_W004 Has basic knowledge of nonparametric and parametric spectrum estimation methods + - + + - - - - - - -
M_W005 Has basic knowledge of system identification with focus on modal analysis + - + + - - - - - - -
Module content
Lectures:

1. Introduction to system identification
• Signal classification
• System models
• Non-parametric vs. parametric identification
2. Time domain analysis
• Linear time invariant systems
• Convolution, impulse response
• Impulse and step response
• Stability and causality
3. Frequency domain analysis
• Fourier series and Fourier transform
• Frequency response, Bode diagram
• Modeling mechanical systems
• Time-frequency analysis
4. Sampling and Laplace transform
• Sampling time-continuous signals
• Aliasing effects and anti-aliasing filters
• Laplace transform
• Poles and zeros, stability
• Analog filters
5. Discrete Fourier transform
• Truncation in time
• Discrete Fourier transform (DFT and FFT)
• DFT estimation, windows and zero-padding
6. Discrete-time systems
• Z-transform
• Relation between z- and s-plane
• Digital filter design methods
• Frequency domain decomposition
7. Stochastic signals
• Auto- and cross-correlation
• Power spectrum and coherence
• Nonparametric spectral estimation (periodogram, Welch method)
• Least squares model-based spectrum estimation

Laboratory classes:

Zaicev machine
Experimental model analysis (parametric)
Experimental modal analysis, impulse test (active)
Experimental modal analysis, impulse test (parameter estimation)
Operational modal analysis (passive test)
Operational modal analysis (parameter estimation)
Application of modal analysis (structure modification)
Application of modal analysis (structure modification verification)
Lamb waves

Project classes:

Convolution and RLC circuits
Sampling, decimation and down-sampling
Identification of audio system
Denoising
Filtering methods
Signal identification

Student workload (ECTS credits balance)
Student activity form Student workload
Summary student workload 185 h
Module ECTS credits 7 ECTS
Participation in lectures 45 h
Participation in laboratory classes 30 h
Participation in project classes 30 h
Examination or Final test 5 h
Preparation of a report, presentation, written work, etc. 30 h
Preparation for classes 15 h
Realization of independently performed tasks 10 h
Completion of a project 20 h
Additional information
Method of calculating the final grade:

Based on laboratory results (marks)

Prerequisites and additional requirements:

Prerequisites and additional requirements not specified

Recommended literature and teaching resources:
  • Zhi-Fang Fu, Jimin He, Modal analysis, Butterworth_Heinemann, 2001
  • J. S. Bendat, A.G. Piersol, Random Data: Analysis & Measurement Procedures, John Willey and Sons, New York, 2000
  • L. Ljung, System Identification: Theory for the User (2nd Edition), Prentice Hall Information and System Sciences Series, 1999
  • R.B. Randall, Frequency Analysis, Brüel&Kjær, 1987
  • S. Braun, Discover signal processing. An interactive guide for engineers, Wiley, 2008.
    David McMahon, Signals and Systems DeMYSTiFieD. A self-teaching guide. Mc Graw Hill, 2006
Scientific publications of module course instructors related to the topic of the module:

Additional scientific publications not specified

Additional information:

None