PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

Elenco notifiche



Digital twins for mechanical systems prognostics

01OHJQD, 01OHJNE

A.A. 2024/25

Course Language

Inglese

Degree programme(s)

Master of science-level of the Bologna process in Ingegneria Meccanica (Mechanical Engineering) - Torino
Master of science-level of the Bologna process in Ingegneria Meccanica - Torino

Course structure
Teaching Hours
Lezioni 21
Esercitazioni in aula 10,5
Esercitazioni in laboratorio 28,5
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Mauro Stefano Professore Ordinario IIND-02/A 12 0 0 0 1
Co-lectures
Espandi

Context
SSD CFU Activities Area context
ING-IND/13 6 D - A scelta dello studente A scelta dello studente
2024/25
The course aims to provide the necessary skills to understand the potential of using digital twins of mechanical systems to develop algorithms for fault condition identification (diagnostics) and for predicting the system's evolution in response to the presence of faults (prognostics). It provides the tools for developing digital twins and mechanical systems, interfacing them with the corresponding physical system, and developing diagnostics and prognostics algorithms. The course includes practical laboratory exercises, which account for about half of the total hours.
The subject aims to provide the necessary skills to understand the potential of using digital twins of mechanical systems to develop algorithms for fault condition identification (diagnostics) and for predicting the system's evolution in response to the presence of faults (prognostics). It provides the tools for developing digital twins and mechanical systems, interfacing them with the corresponding physical system, and developing diagnostics and prognostics algorithms. The course includes practical laboratory exercises, which account for about half of the total hours.
At the end of the course, students will have acquired the necessary skills for developing digital twins of mechanical systems. They will know the techniques underlying the development of algorithms for the prognostics of mechanical systems, which can be developed using their digital twins. Additionally, they will become able to interface mechanical systems with their digital twins using sensors and data acquisition boards. They will have experienced the development of digital twins in some practical examples.
At the end of the subject, students will have acquired the necessary skills for developing digital twins of mechanical systems. They will know the techniques underlying the development of algorithms for the prognostics of mechanical systems, which can be developed using their digital twins. Additionally, they will become able to interface mechanical systems with their digital twins using sensors and data acquisition boards. They will have experienced the development of digital twins in some practical examples.
Applied mechanics
Applied mechanics
Different types of digital twins and the numerical models on which they are based will be analyzed, with a particular focus on applications of lumped parameter functional models. The course then proceeds with an illustration of possible prognostic algorithms, which will also be demonstrated with practical examples. The basic elements for developing numerical models that underpin digital twins will be taught using Matlab, Simulink, and the multibody environment with the Simscape tool. The methods of interfacing numerical models with physical systems will be illustrated, also with practical examples, with particular attention to sensors and data acquisition and conversion chains. Finally, several practical cases in different contexts will be presented, considering robotics, motion transmission, and a fluid system, with practical exercises involving the use of experimental equipment available at the Department of Mechanical and Aerospace Engineering laboratories. The course includes 21 hours of classroom lectures and 39 hours of laboratory exercises. • Possible types of DT; use of DT; application examples; difference between DT and models (3 hours) • Characteristics of functional DTs used for the prognostics of mechanical systems; real-time and off-line DTs; modeling defects in mechanical systems (3 hours) • Principles of prognostics for mechanical systems (6 hours) • Tools for developing models underlying DTs: Modeling in Simulink environment (3 hours); Multibody modeling (9 hours) • HW and SW tools for DT implementation: sensors; data acquisition boards; real-time operating systems (6 hours) Examples of DTs: • Screw drive (9 hours) • Mobile robot (7.5 hours) • Fluid system (7.5 hours) • Harmonic drive reducer (6 hours)
Different types of digital twins and the numerical models on which they are based will be analyzed, with a particular focus on applications of lumped parameter functional models. The course then proceeds with an illustration of possible prognostic algorithms, which will also be demonstrated with practical examples. The basic elements for developing numerical models that underpin digital twins will be taught using Matlab, Simulink, and the multibody environment with the Simscape tool. The methods of interfacing numerical models with physical systems will be illustrated, also with practical examples, with particular attention to sensors and data acquisition and conversion chains. Finally, several practical cases in different contexts will be presented, considering robotics, motion transmission, and a fluid system, with practical exercises involving the use of experimental equipment available at the Department of Mechanical and Aerospace Engineering laboratories. The course includes 21 hours of classroom lectures and 39 hours of laboratory exercises. • Possible types of DT; use of DT; application examples; difference between DT and models (3 hours) • Characteristics of functional DTs used for the prognostics of mechanical systems; real-time and off-line DTs; modeling defects in mechanical systems (3 hours) • Principles of prognostics for mechanical systems (6 hours) • Tools for developing models underlying DTs: Modeling in Simulink environment (3 hours); Multibody modeling (9 hours) • HW and SW tools for DT implementation: sensors; data acquisition boards; real-time operating systems (6 hours) Examples of DTs: • Screw drive (9 hours) • Mobile robot (7.5 hours) • Fluid system (7.5 hours) • Harmonic drive reducer (6 hours)
The course will be carried out with the cooperation of researchers who worked on the development of the digital twins showed as use case in the laboratory exercise
The subject will be carried out with the cooperation of researchers who worked on the development of the digital twins showed as use case in the laboratory exercise.
The course includes a substantial practical component where students will develop digital twins of systems available in the laboratory and verify their validity using experimental data acquired during the exercises. The experimental activities will specifically involve a robot, a fluid system, and a transmission system with a screw and nut. Students will prepare four short reports about the four laboratory exercise. The report can be produced as an individual or a group report, according to the choice of each student
The subject includes a substantial practical component where students will develop digital twins of systems available in the laboratory and verify their validity using experimental data acquired during the exercises. The experimental activities will specifically involve a robot, a fluid system, and a transmission system with a screw and nut. Students will prepare four short reports about the four laboratory exercise. The report can be produced as an individual or a group report, according to the choice of each student.
Slide provided during the course Selected scientific papers
Slides provided during the semester. Selected scientific papers.
Slides;
Lecture slides;
Modalità di esame: Prova orale obbligatoria;
Exam: Compulsory oral exam;
... Oral examination will consider tall the topic of the course and it with discussion of reports related to the experimental activities conducted during the exercises. The final score will consider the knowledge of the topics of the course and the quality and understanding of the short reports about exercise
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam: Compulsory oral exam;
Oral examination will consider all the topics of the subject and incluses the discussion of reports related to the experimental activities conducted during the exercises. The final score will consider the knowledge of the topics of the subject and the quality and understanding of the short reports about exercises.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
Esporta Word