Data Acquisition Systems

Objectives

The discipline provides that students develop competencies in the domain of data acquisition systems, namely they learn and understand the basic concepts and know how to apply them in an engineering context in diversified application domains.

Objetives:
Knowledge:
- Basic concepts of data acquisition systems
- Architectures for Data Acquisition Systems (SAD)
- Signal conditioning and D/A – A/D converters
- Interfaces for data acquisition
Know-how:
- Design of data acquisition systems
- Development of solutions in different operational contexts
Soft-Skills:
- Analysis and formalization of problems’ specifications
- Learn how to behave in teamwork
- Learn how to present publically a proposal of work
- Learn how to manage time

General characterization

Code

7317

Credits

6.0

Responsible teacher

Filipe de Carvalho Moutinho, Ricardo Luís Rosa Jardim Gonçalves

Hours

Weekly - 5

Total - 70

Teaching language

Português

Prerequisites

Available soon

Bibliography

Practical Data Acquisition for Instrumentation and Control Systems; John Park, Steve Mackay; 2003; Newnes

Data Acquisition Techniques Using PCs; Howard Austerlitz, 2003; Academic Press

Several datasheets

Teaching method

Theoretical-practical classes, of two hours per week, where the program contents are exposed, exercises and presentations are made by students and discussions are encouraged.

Individual work, which includes the research on a theoretical topic, the preparation of a report and its presentation.

Practical classes in the laboratory, of three hours per week, where students perform, in groups of max. 3 students, a set of works/projects with emphasis on data acquisition are performed. Two reports and respective presentations/discussions are also performed.

Evaluation method

Theoretical evaluation component (CT), with evaluation of the Seminar type, has a weight of 45% in the final grade and minimum classification of 9.5 values:

  • Evaluation element "individual work / report on a topic" (CTR, 50% of the theoretical component), to be delivered until 2020/04/19
  • Evaluation element "presentation and discussion of individual work" (CTAP, 20% of the theoretical component), on a date to be agreed
  • Evaluation element "poster about individual work" (CTP, 10% of the theoretical component), to be delivered until 2020/04/26
  • Evaluation element "evaluation of a colleague''s work" (CTAV, 20% of the theoretical component), to be delivered until 2020/04/26

Component of practical evaluation (CP), with evaluation of the Laboratory or Project type, carried out in groups of 3 students (max. and recommended), has a weight of 45% in the final grade and minimum rating of 9.5 values:

  • Evaluation element "1st evaluation work" (CP1, 40% of the practical component), to be delivered until 2020/04/07 and discussed on a date to be agreed
  • Evaluation element "2nd evaluation work" (CP2, 60% of the practical component), to be delivered by 2020/05/31 and discussed on a date to be agreed

Summative evaluation component (CS, 10% in the final grade, without minimum classification):

  • Arithmetic average of small weekly questionnaires, carried out in Moodle (between Friday and Monday of the following week), about the theoretical-practical and practical classes

All works will be delivered only in digital format through Moodle.

The classification obtained, in the previous two years, is valid for the theoretical component or for the practical component of evaluation, if it has a score higher than 9.5.

All assessment components and assessment parts are rounded to two decimal places, the result being calculated based on the weighted average according to the indicated weights.

Formulas:

  • Final_ Note = CTx0.45 + CPx0.45 + CSx0.10
  • CT = CTRx0.5 + CTAPx0.2 + CTPx0.1 + CTAVx0.2
  • CP = CP1x0.4 + CP2x0.6
  • CS average questionnaire scores

Subject matter

- Architectures for Data Acquisition Systems (SAD), general characterization of SAD, identification of principal blocks, characterization of functions, methodologies for the development of dedicated systems.

- Signal conditioning: use of operational amplifiers, compensations and linear/non-linear corrections, conversions V/A/F, galvanic isolation, use cases and applications using different transducers.

- Digital-Analog Conversion: characterization, converters specification, direct and indirect methods, architectures.

- Analog-Digital Conversion: characterization, converters specification, asynchronous methods with direct and indirect controller, architectures.

- Solutions for the acquisition of data (centralized versus distributed); traditional instrumentation versus virtual instrumentation; remote systems; interfaces (RS-232, RS-485, IEEE-488, ...).

- Analysis of use cases.

Programs

Programs where the course is taught: