Study-unit
| Course name | Electronic engineering for the internet-of-things |
|---|---|
| Study-unit Code | A003189 |
| Curriculum | Industrial iot |
| Lecturer | Antonio Moschitta |
| Lecturers |
|
| Hours |
|
| CFU | 9 |
| Course Regulation | Coorte 2022 |
| Supplied | 2023/24 |
| Supplied other course regulation | |
| Learning activities | Caratterizzante |
| Area | Ingegneria elettronica |
| Sector | ING-INF/07 |
| Type of study-unit | Obbligatorio (Required) |
| Type of learning activities | Attività formativa monodisciplinare |
| Language of instruction | Italian |
| Contents | The contents of the module concern monitoring and management activities, referring both to the relevant electrical quantities in the industrial environment and to the management of measurement systems and related processes. The course is therefore divided into three teaching units. The first one deals with the measurement of electrical quantities in the industrial field, identifying the measured quantities, the measurement methods, and the instrumentation used. The second unit illustrates the architecture of an industrial monitoring system, both with respect to the measurement chain and with respect to the methods of interconnection of the constituent elements. The third teaching unit deals with instrumentation and data management methodologies, focusing on reliability, maintenance, and related reference documents. |
| Reference texts | • Dispense e slide a cura del docente. • Fausto Galetto, Affidabilità, volume primo - teoria e metodi di calcolo, Ed. CLEUP • Fausto Galetto, affidabilità, volume secondo - prove di affidabilità, Ed. CLEUP • Antonio Zanini, elementi di Affidabilità, Ed. Progetto Leonardo • M. Norgia, R. Ottoboni, A. Pesatori, C. Svelto, Misure - Dai fondamenti alla strumentazione, Società Editrice Esculapio. • M. Savino. Fondamenti di Scienza delle Misure. Ed. La Nuova Italia Scientifica. • G. Zingales. Misure Elettriche: Metodi e Strumenti. Ed. UTET. |
| Educational objectives | The course aims to provide advanced concepts and skills in the field of electrical measurements in the industrial field, useful to: • identify critical quantities and the related measurement chain to effectively monitor an industrial process; • select the most appropriate instrumentation, and its interfacing in a modern integrated system for monitoring and process control; • select and design strategies for instrumentation management; • evaluate the reliability of a complex and distributed data acquisition system; • select and design strategies for the acquisition and management of measurement data; |
| Prerequisites | It is recommended to have acquired the contents of the course of Electronic Measurements with Laboratory, degree course in Computer Science and Electronic Engineering |
| Teaching methods | Lectures, practical exercises |
| Other information | The teaching material produced by the teacher can be found on the e-learning platform http://www.unistudium.unipg.it |
| Learning verification modality | Written exam, oral exam |
| Extended program | Introduction to the course, presentation of teaching units and examination methods Teaching Unit 1. Measurement of electrical quantities in the industrial field. Measurements on power systems. Measurements on three-phase systems. Measuring transformers. Architecture of a digital output sensor for non-electrical quantities. Teaching Unit 2. Instrumentation for industrial measurements, performance parameters. Characteristics of a distributed measuring system for industrial applications. Main interconnection standards: fieldbus, wired and wireless realizations. Teaching Unit 3. Reliability and maintenance of measuring chains and complex measuring systems. Typical definitions and metrics. Statistical, probabilistic, and system aspects. FMEA, FMECA, HAZOP. Measures for statistical process control. Reference standard. Notes on the maintenance of systems and processes and on the applicable legislation. |
| Obiettivi Agenda 2030 per lo sviluppo sostenibile | The contents of the course and the skills provided help to increase the efficiency and resilience of production systems, as they support monitoring and management activities. |