DATA ACQUISITION AND ANALYSIS

SHE Level 5
SCQF Credit Points 15.00
ECTS Credit Points 7.50
Module Code MMH120619
Module Leader Peter Wallace
School School of Computing, Engineering and Built Environment
Subject Instrumentation and Control
Trimesters
  • A (September start)
  • B (January start)
  • C (May start)

Pre-Requisite Knowledge

A knowledge of; (i) Signals and Noise, (ii) Transducers. Both at a level equivalent to that covered in Measurement Theory and Devices.

Summary of Content

This module aims to develop in the student the ability to evaluate, in a given situation, the most approrpriate strategy for acquiring data and to understand the merits of this strategy with respect to other approaches. A range of modern time and frequency domain analysis techniques will be discussed as well as advanced applications such as data fusion.

Syllabus

Data Acquisition: Signal conditioning and processing techniques including: buffer amplifier, voltage attenuator, current-to-voltage converters, amplification, filters and analalue-to-digital converters. Sampling, A/D conversation, Practical implementation of DAQ systems. Development of LabVIEW acquisition and display systems. Data Analysis: Statistical properties of signals, time and frequency domain, convolution and correlation, curve fitting and data modelling, interpolation and extrapolation, FFT, digital filtering Development of LabVIEW analysis systems. The syllabus consists of a list of topics normally covered within the module. Each topic may not be dealt with in the same detail.

Learning Outcomes

On completion of this module the student should have:1. Knowledge of LabVIEW and its application to data acquisition and analysis.2. The ability to critically appraise the range of techniques applicable to a specific measurement tasks.3. The ability to design and implement a data acquisition solution for a particular application.4. The ability to apply a range of time and frequency domain analysis techniques to acquired data.

Teaching / Learning Strategy

Full Time Students The first week of the 3 week cycle will consist of lecture material together with a practical introduction to LabVIEW programming. Further practical work on data acquisition and analysis, using real signals, will be undertaken over the next two weeks. The module content will be supported by a combination of notes, tutorials and student-centred work. Materials will be available via GCU Learn. In addition, the students will be directed to the resources available on the National Instruments web site. Distance Learning Students Students will be provided with a study pack which will cover the syllabus material. The module content will be delivered through a combination of notes, tutorials and practical exercises. In addition the students will be provided with a self-contained practical introductionto LabVIEW programming. This will permit them to run simulations illustrating course concepts as well as to tackle data acquisition and analysis tasks using real data. In order to achieve this, the students will be provided with a USB signal interfacing/data acquisition device as well as sensors, such as temperature ICs and termocouples. Tutors will be available for consultation via GCU Learn, e-mail and telephone. In addition, the students will be directed to the resources available on the National Instruments web site. Materials, including AV versions of lectures and tutorials, will be available via GCULearn

Indicative Reading

Principles of Measurement Systems, J.P. Bentley, 2005, 4th Edition, Longman. Measurment Systems - Application and Design, E.O. Doebelin, 2003, 5th Edition, McGraw Hill International. Online tutorials and white papers located in the National Instruments Developer Zone: http://zone.ni.com/zone/jsp/zone.jsp Introduction to Instrumentation and Measurements, Third Edition Robert B. Northrop, University of Connecticut, Storrs, USA June 2014: 254 x 178: 927pp Hb: 978-1-4665-9677-1: Measurement Systems and Sensors (2nd Ed pending), Waldemar Nawrocki, Artech House

Transferrable Skills

Critical thinking and problem solving through the development of data acquisition systems and data analysis strategies. Development of higher level cognitive skills including analysing and synthesising skills. Independent working via lab based courseworks. Numeracy skills in all aspects of the module. Information retrieval skills via access of online resources. IT skills via lab work and report presentation.

Module Structure

Activity Total Hours
Tutorials (FDL) 6.00
Tutorials (FT) 6.00
Practicals (FDL) 26.00
Independent Learning (FDL) 94.00
Assessment (FDL) 24.00
Practicals (FT) 26.00
Assessment (FT) 24.00
Independent Learning (FT) 82.00
Lectures (FT) 12.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 2 n/a 50.00 45% Data acquisition exercise (including programming) (Learning Outcomes 1, 2 and 3)
Coursework 1 n/a 50.00 45% Analysis of Data (Learning Outcomes 1, 2 and 4)