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Data Acquisition

Course Instructors: Adrian Surpateanu.

General notions about intelligent systems used for measurement and control. Hardware resources composing an intelligent data acquisition system, using constructive and functional points of view, as well as the most important parameters which characterize these resources. Main intelligent data acquisition systems architectures, making critical and objective comparison between them, as well as minimal criteria for choosing or designing such a system according to a specific application request. Main error sources in data acquisition systems and the calculus mode of total accuracy as a function of main resources parameters. Virtual instrumentation concepts and some specific aspects regarding machine-measurement and control process interfacing; dedicated virtual instrumentation software platforms and, some major examples of virtual instruments (multimeters, digital scopes, etc.). Basic notions detailed exemplification by theoretical and practical discussions about some intelligent data acquisition systems.

Syllabus:

  • Introductory elements regarding measurement and control systems using hardware-software intelligent platforms.
  • Data acquisition and data processing systems: general structure; main types of resources; interfacing techniques, microcontroller-based data acquisition systems.
  • Functional and structural analysis for signal processing and data acquisition circuitry.
  • Main architectures of data acquisition systems and comparative evaluation of their performances.
  • General considerations about virtual instrumentation; virtual instruments, machine-measurement and control process interfacing, dedicated virtual instrumentation software platforms and, some major examples of virtual instruments (multimeters, digital scopes, etc.); dedicated PC interfacing used for measurement equipments.
  • Specific measurement applications based on hardware-software intelligent data acquisition systems: designing an universal, modular data acquisition system based on structural analysis of the application domain, error estimation for the designed data acquisition system, software implementation for the acquired data analysis.