Digital acquisition and data processing

The main objective of the Digital Data Acquisition and Analysis course is to develop a systematic understanding of how physical quantities are converted into reliable, interpretable digital information through an integrated measurement system. Students are introduced to the roles and interrelationships among key components of digital acquisition systems, and to how sensor selection, signal conditioning, sampling, and data management affect the quality of results. Special emphasis is placed on the development of critical thinking and the practical application of modern tools, which allows students to acquire, generate, and process analog and digital signals. One of the key objectives is to develop the ability to design and configure digital acquisition systems for real-world applications, while ensuring accurate and reliable measurements. The course develops practical engineering skills through work with the LabVIEW development environment and modern acquisition hardware, preparing students to work in real-world, multidisciplinary environments (automotive, industrial, and IoT systems) and for roles in developing digital acquisition systems and in data processing using statistics and signal processing. The course also develops engineering judgment for data-driven decision-making through uncertainty assessment, noise identification, and an understanding of limitations in the digital-to-analog conversion process.

Upon successful completion of the course, students will be able to explain the architecture and components of a digital data acquisition system. They will be able to design and implement complete data acquisition systems, from sensor selection to data analysis (generating analog signals, working with digital input/output systems, using counters to measure frequency, generating pulses and counting events, as well as analyzing and processing signals and data. Students will be able to configure digital acquisition systems using tools such as LabVIEW and implement data processing flows using modern tools and programming environments. They will also be able to process and analyze the acquired signals using appropriate conditioning and interpretation methods. They will develop practical skills in integrating hardware and software components into functional systems, as well as the ability to select appropriate configurations for specific applications. Students will be able to diagnose problems in measurement systems and ensure the reliability of data.

The course covers the basic concepts and practical implementation of signal acquisition and conditioning systems. It begins with an overview of the architecture of digital acquisition systems, including sensors, signal types (analog and digital), and measurement principles. Students then study digital acquisition hardware components such as analog input/output, digital input/output, counters, and system interfaces. Key topics include sampling and signal protection and conditioning techniques for various types of measurements (temperature, pressure, strain, vibration, etc.). In addition, students are introduced to signal processing methods, including filtering and frequency domain analysis (FFT).

Introduction to Virtual Instrumentation (VI) and the LabVIEW programming environment; Data flow in VI; Troubleshooting and debugging virtual instruments; Implementing virtual instruments; File writing and reading techniques; File formats; Programming techniques in LabVIEW; Using acquisition hardware resources in LabVIEW; Synchronization techniques in LabVIEW; Event-driven programming; Error handling; User interface management; Methods for improving LabVIEW code; Introduction to sensors and complete measurement chains through practical examples and tasks; Implementation of an acquisition system and corresponding LabVIEW applications according to a given project (adapted to the needs of the student's home module); Practical exercises covering the implementation of applications for digital acquisition systems in LabVIEW, including acquisition, generation, analysis and processing of signals, and system integration.

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Script: Digital acquisition and data processing. Measurement and acquisition system: National Instruments PXI, National Instruments LabVIEW development environment. VS CODE and Arduino IDE development environment. Auxiliary platforms: Development platforms for simulation and acquisition of analog and digital signals (Atmega); Amplifier and conditioning circuits (instrumentation and operational amplifiers), AD converters, voltage and current references, oscilloscope.

Total assigned hours: 75

New material: 25
Elaboration and examples (recapitulation): 5

Auditory exercises: 10
Laboratory exercises: 2
Calculation tasks: 2
Seminar paper: 0
Project: 10
Consultations: 0
Discussion/workshop: 6
Research study work: 0

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 0
Review and grading of the project: 0
Test: 15
Test: 0
Final exam: 0

Activity during lectures: 0
Test/test: 50
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 0
Project: 10
Final exam: 40
Requirement for taking the exam (required number of points): 0

E. O. Doebelin, Measurement Systems: Application and Design. McGraw-Hill, 2004. ISBN–978-0-07-243886-4; J. P. Bentley, Principles of Measurement Systems. Pearson Prentice Hall, 2008. ISBN – 978-81-7808-134-2; A. Oppenheim, A. Willsky, and S. Nawab, Signals and Systems. Upper Saddle River, N.J: Pearson, 1997. ISBN – 978-0-13-814757-0; J. G. Proakis and D. G. Manolakis, Digital signal processing, 4th ed. Upper Saddle River, N.J.: Pearson Prentice Hall, 2007. ISBN–978-0-13-187374-2; J. P. Holman, Experimental Methods For Engineers. New York, NY: McGraw-Hill Higher Education, 2012. ISBN– 978-0-07-132648-3