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Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2018/2019
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 097525 - ADVANCED MEASUREMENT TECHNIQUES
Docente Manzoni Stefano
Cfu 6.00 Tipo insegnamento Monodisciplinare

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - BV (483) MECHANICAL ENGINEERING - INGEGNERIA MECCANICA*AZZZZ097525 - ADVANCED MEASUREMENT TECHNIQUES

Obiettivi dell'insegnamento

The aim of the course is to present to students the main techniques related to the fields of industrial automation, data analysis, and experimental activities in mechanical engineering.

More specifically, the student is expected to learn how to apply tools and methods in the field of experimental identification of systems and industrial devices.

 


Risultati di apprendimento attesi

The student will learn how to carry out experiemental tests, design tests, and process data to the aim of system identification (e.g. modal analysis for mechanical systems, acoustic source detection for acoustic systems, and so on).

 

More in details, at the end of the teaching, the student is expected to reach the following learning outcomes

Knowledge and comprehension

  • Data analysis
  • System identification
  • Design of experimental tests

Ability in the application of knowledge

  • Design experimental tests in dynamcs and acoustics
  • Perform experimental tests
  • Ability to check data after acquisition
  • Identify the correct data acquisition and data analysis techniques for signal processing
  • Estimate parameters in mechanical and acoustic systems

Authonomy in judgement

  • Select actuators/sensors for carrying out experimental tests
  • Select methods for checking data reliability
  • Select the best signal processing technique for evidencing machine characteristics
  • Select the best identification algorithm for given problems

Communication skills

  • Students will learn to present a technical report on the basis of data acquired during the semester

Argomenti trattati

The topics treated are: the methods for the characterisation of mechanical systems used both in experiments and in industrial diagnostics, the advanced techniques of time-variant data, the digital transmission techniques of data in the field of control and industrial automation, the use of image processing to the purpose of mechanical measurements. The students will have the possibility to choose one specific topic among those characterised by the symbol (*), depending on their interests and on time-availability.

Description of the topics :

Experimental techniques for identification of mechanical systems: Frequency response function of systems: models, data acquisition and analysis, estimation, data representation methods, examples of applications. Basic concepts of modal analysis and parameter identification techniques (SDOF and MDOF systems). Principles of diagnostics and industrial monitoring.

Time-frequency analysis: Algorithms and applications

Methods for identification of noise sources (moving or not): basics of sound phenomena and measurement, beamforming, arrays of microphones.

Digital image analysis (*): Digital images, basic concepts, storage methods, acquisition chain, analogical cameras (standard and progressive) and digital cameras (CCD and CMOS), analogical and digital frame grabber (IEEE1394, Camera link and USB), basics of optical systems and illuminating engineering, conditioning of images on a single pixel and on an area, convolution and transforms, system calibration and image correction, use of images for measuring position and bi-dimensional displacements (edge detection, blob detection, pattern matching), use of images for measuring tri-dimensional displacements (stereoscopy, laser triangulation, use of structured light).

Non-destructive techniques (*): Basics and advanced techniques (e.g. thermography, fiber optics strain gauges, structural health monitoring).

Measurements in the automotive field (*): Measurement of comfort in vehicles, measurements for safety systems and vehicles controllers, feed-back systems in automatic controllers, self-diagnostic systems


Prerequisiti

The student is expected to have rooted bases in mechanical measurements, digital signal processing, and dynamics of mechanical systems.


Modalità di valutazione

Attendance to lectures and labs is not mandatory, but warmly suggested.

The exam is composed by two parts: a discussion/presentation about experimental tests on modal analysis carried out by the student during the labs + written test about theory.

The two parts can be given in any order, according to the student's preferences.

In the discussion/presentation about experimental modal analysis tests carried out by the student during the course, the student is expected to explain her/his choices for testing and identifying a given mechanical system (e.g. decisions and methods about the design of the sensor mesh), how the experimental tests were carried out, and how the signals were processed in order to estimate the modal parameters.

 

Therefore, the written exam allows to evaluate the student's comprehension of the theoretical topics, while the discussion/presentation allows to evaluate her/his capability to apply theory in practical cases and to judge the reliability of the consequent results. Furthermore, the discussion/presentation is also able to evidence the student's capability to synthetise concepts and to focus on the main issues/results of the tests.


Bibliografia
Risorsa bibliografica obbligatoriaslides of the course Beep
Risorsa bibliografica facoltativaD.J. Ewins, Modal testing - theory, practice and application - 2nd edition, Editore: Baldock: Research studies press Ltd, Anno edizione: 2000
Risorsa bibliografica facoltativaVan Trees, Optimum Array Processing: Part IV of Detection, Estimation, and Modulation Theory, Editore: Wiley-Interscience

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
33:00
49:30
Esercitazione
2:24
3:36
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
24:36
36:54
Laboratorio Di Progetto
0:00
0:00
Totale 60:00 90:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.6.5 / 1.6.5
Area Servizi ICT
24/02/2021