Data Acquisition Systems
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.
- Basic concepts of data acquisition systems
- Architectures for Data Acquisition Systems (SAD)
- Signal conditioning and D/A – A/D converters
- Interfaces for data acquisition
- Design of data acquisition systems
- Development of solutions in different operational contexts
- 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
Filipe de Carvalho Moutinho, Ricardo Luís Rosa Jardim Gonçalves
Weekly - 7
Total - 70
Practical Data Acquisition for Instrumentation and Control Systems; John Park, Steve Mackay; 2003; Newnes
Data Acquisition Techniques Using PCs; Howard Austerlitz, 2003; Academic Press
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.
Theoretical evaluation component (CT), with evaluation of the Seminar type, has a weight of 50% in the final grade and minimum classification of 9.5 values. This component has the following evaluation elements:
- Evaluation element “individual work/report” (to be delivered in PDF/DOC) and the associated justification (to be delivered in video and to be visualized by the teacher) – this evaluation element (CTRJ) weights 60% of the theoretical evaluation component;
- Evaluation element “presentation of the individual work/report” (to be delivered in video and to be presented in class) – this evaluation element (CTAP) weights 20% of the theoretical evaluation component;
- Evaluation element "evaluation of a colleague''s work” (to be delivered in PDF/DOC) – this evaluation element (CTAV) weights 20% of the theoretical evaluation component.
There may be individual discussion (in person or remote), on any of the elements of theoretical evaluation component, until the last day of the semester''s exam period.
Additionally, questions will be asked during the theoretical-practical classes. The answers to these questions may produce a bonus of up to 2 values in the grade of the theoretical evaluation component (maximum between 2 and 0 values, for grades between 7.5 and 20 values proportionately) - see formula below.
Practical evaluation component (CP), with evaluation of Laboratory or Project type, carried out in groups of 3 students (max. and recommended), has a weight of 50% in the final grade and minimum rating of 9.5 values. This component has the following evaluation elements:
- Evaluation element "1st evaluation work" (CP1, 50% of the practical component), to be discussed in person (if possible) on a date to be agreed;
- Evaluation element "2nd evaluation work" (CP2, 50% of the practical component), to be discussed in person (if possible) on a date to be agreed.
Works will be delivered in digital format through the course page in Moodle.
The classification obtained, in the previous two years, is valid for the theoretical evaluation component or for the practical evaluation component, if it has a score higher than 9.5.
All evaluation components and evaluation elements are rounded to two decimal places.
- CTwithoutBonus = CTRJx0,6 + CTAPx0,2 + CTAVx0,2
- CT = CTwithoutBonus if CTwithoutBonus < 7,5
- CT = CTwithoutBonus + (((20 - CTwithoutBonus) / 12.5) x 2) if CTwithoutBonus >= 7.5
- CP = CP1x0.5 + CP2x0.5
- FinalGrade = CTx0.50 + CPx0.50
- 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.
- Analysis of use cases.
Programs where the course is taught: