Metodi e Strumenti per la Diagnostica
Methods and Instruments for Diagnostics Gian Marco Revel
The students should have basic knowledge of the principal instruments for mechanical and thermal measurements.
KNOWLEDGE AND UNDERSTANDING:
The course provides knowledge for the design, management and implementation of measurement systems , analysis algorithms and procedures for quality control , industrial and structural monitoring diagnosticsCAPACITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
The student will know how to choose the appropriate experimental technique diagnostics , both for the instrumental component and for the algorithmic; this is discussed with reference to a number of application cases , both in classroom teaching mode through laboratory exercisesTRANSVERSAL SKILLS:
The course will cover techniques for diagnostics with application examples chosen in different contexts engineering ( mechanical , civil / construction , etc . ) , as well as in non- engineering context , fostering a multidisciplinary approach to the study
Contents (lectures, 32 hours)
The objectives are the design, management and application of measurement systems and diagnostic procedures for quality control, industrial diagnostics and non-destructive testing.
Diagnostics and quality control. Signals typologies: acustical, vibrational, images.
Elements of data analysis for industrial and clinical diagnostics: Time domain, Frequency domain, Cepstrum domain, Modulated signals and envelope analysis, Joint time-frequency analysis and wavelets, Rotating machinery and order tracking, 2D domains (images).
The features for machinery health monitoring with reference to the main components constituting the industrial plants (unbalanced shafts, electrical motors, centrifugal and axial turbomachines, alternative machinery, gears, belt transmission, rolling bearings and lubricated bearings).
Measurement instrumentation for the quality control: instrumentation, metrological requirements.
Non destructive testing: magnetoscope, ultrasound, shearography, infrared thermography.
Feature extraction and signal classification by neural networks.
Laboratory experiences (16 hours)
Practical experiences with instruments for diagnostics, application to real cases. Signal analysis and classification using Matlab e Labview.
Development of the examination
LEARNING EVALUATION METHODS
Oral examination and optional discussion of a final project carried out in the laboratoies of the Department of Industrial Engineering and Mathematical Sciences.
LEARNING EVALUATION CRITERIA
The student, during the oral examination, will have to demonstrate to have the fundamental knowledge of the design, management and application of measuerement systems and procedures for quality control, insutrial diagnostic and non-destructive testing. In order to pass the exam with positive results, the student will have to show an overall knowledge of the course contents, which will have to be exposed with sufficient and correct use of technical terms. The maximum score will be achieved by demonstrating a deep knowledge of the course contents presented with a fully appropriate technical approach
LEARNING MEASUREMENT CRITERIA
Score in a scale with 30 levels (e.g. 27/30) based on knowledge and capacities demonstrated by the student and measured according to the Learning Evaluation Criteria.
FINAL MARK ALLOCATION CRITERIA
For each question (usually 3) posed to the student, a score in the scale with 30 levels will be assigned. The final overall score will correspond to the average of the scores for each single question. The presentation and discussion of the optional final project will substitute one of the questions with a score in the same scale. The Laude will be assigned to the students that, having achieved the maximum score, will also demonstrate an outstanding knowledge in the discussed topics.
Print of the course slides provided by the professor; For some topics indications on specific references will be given, e.g.: 1. E. Doebelin, Strumenti e metodi di misura, ed. Mc Graw Hill, 2004.
2. Primers e Technical review disponibili sul sito: www.bksv.com
3. L. Furlanetto, Manuale di manutenzione degli impianti industriali e dei servizi, ed. Franco Angeli, 1998.
4. J.L. Semmlow, Biosignal and Biomedical Image Processing - MATLAB-Based Applications, ed. CRC Press, 2004.
- Ingegneria Meccanica (Corso di Laurea Magistrale (DM 270/04))