Module Title
Level
Reference No.
(showing level)
Credit Value
Student Study Hours
Pre-requisite learning
Co-requisites
Excluded combinations
Module co-ordinator
Faculty/Department
Short Description
Aims
Learning Outcomes
Advanced Instrumentation and Control
7
EEB_7_XXX
20
Contact hours:
52
Student-managed learning hours: 148
None
None
Steve Alty
ESBE/EED
This module develops advanced techniques in data acquisition and
manipulation required for instrumentation and control applications.
Including structures of virtual instrumentation, data acquisition tools
and wizards. Signal conditioning and suitable pre-processing prior to
digitisation is also covered. The theory behind modern control systems
is explored including proportional, differential and integral control,
state-space analysis, bode plots and stability. Further, it consolidates
lectures with experimental computer-based assignments using industry
standard hardware and software (NI DAQ and LabView). Specifically,
the NI Elvis platform is used along with its data acquisition facilities to
perform a closed-loop control task, such as temperature control. The
hardware assignment will be the basis of a group project in the latter
half of the module.
The aim of this module is to develop knowledge and experience in data
acquisition and virtual instrumentation used in Industry for
instrumentation and control purposes.
At the end of the module, students will be able to undertake the
actions described in each of the four areas below.
Knowledge and Understanding
To understand the process of data acquisition and digitisation.
To show an appreciation of sampling theory and preparation of data for
acquisition according to context.
To be able to use software programming techniques to develop virtual
instrumentation to perform standard processing, instrumentation and
control tasks.
Intellectual Skills
To be able to synthesise specialised virtual instrumentation tools for
specific tasks.
To know which processing technique to select in which context.
To acquire a high-level of software programming skills.
Practical Skills
To be able to utilise computer methods to build practical solutions to
instrumentation and control problems.
To be able to systematically select and apply appropriate control
algorithms using NI LabView.
To evaluate the performance of a given system and its behaviour.
Employability
Teaching and learning
pattern
Indicative content
Assessment
Elements & weightings
Indicative Sources
(Reading lists)
Transferable Skills
To effectively communicate and critically evaluate observed results in a
technical format.
To competently maintain a logbook.
To analyse data using complex mathematical techniques.
This module will provide students with a sound knowledge of virtual
instrumentation and control techniques commonly used in industry.
National Instruments LabView environment is widely used throughout
the electrical and electronic engineering industry and experience will
enable students to gain employment therein.
26 hours of Lectures
26 hours of Labs
Lectures
 Data flow programming in LabView
 Structures of Virtual Instrumentation
 Data structures
 Sub-VIs
 Data acquisition tools and DAQ wizards
 Sampling Theorem and Anti-Aliasing Filtering
 Closed loop control systems
Computer Labs
 NI Elvis platform
 Signal pre-processing
 Data acquisition
 VI creation
 Group project: PID temperature control (6-weeks)
Exam (2 hrs)
50%
(Testing Knowledge, Understanding and Intellectual Skills)
Course work and formal assignments
50%
(Testing Practical Skills and Transferable Skills)
1 hour phase test in Week 8 to test knowledge acquired during previous
weeks’ lecture material (worth 10%)
Labs; students hand in a logbook, a formal report and software
assignment in week 13 (worth 40%). The assignment will test students’
ability to develop a NI LabView virtual instrument to perform data
acquisition and solve a control theory problem.
All courseworks are summative, formal reports will contain formative
feedback. Formal reports should be no more than 3000 words.
Core reading:
1. King, R., Introduction to Data Acquisition with LabView, McGrawHill, 2nd Edition, 2012.
2. Dorf and Bishop, Modern Control Systems, Pearson, 12th Edition,
2012
Background reading:
3. Essick, J., Hands-On Introduction to LabVIEW for Scientists and
Engineers, OUP, 2nd Edition, 2012