Registry

Module Specifications

Current Academic Year 2012 - 2013
Please note that this information is subject to change.

Module Title	Labview, Data Acquisition, Analysis & Control
Module Code	MM600
School	School of Mechanical and Manufacturing Engineering
Online Module Resources
Module Teacher	Dermot Brabazon
NFQ level	8	Credit Rating	7.5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Description

The objectives of this module are to enable participants to acquire, analyse and simulate data, and use this data input for real time system control. By the end of this module participants should be able to program in LabVIEW for data acquisition, analysis and control applications. Product development research design of experiments examples will be analysed. Participants will understand the software and hardware specifications required for specific applications. The emphasis will be on rapid development of data acquisition, analysis, system control, simulation and visualisation.

Learning Outcomes

1. Create programs/ Virtual Instruments (VIs) in LabVIEW and integrate sub-VIs (modular code/sub-routines/sub-programmes) for system control
2. Perform data analysis including advanced statistical, spectrum, and topology analysis
3. Implement system simulation techniques of optimisation and Artificial Neural Networks
4. Perform integrated data acquisition, analysis and real time control
5. Create remote instruments and executables which can run independently of operating system
6. Alter VI appearance, documentation, integratability for Object Oriented Programming
7. Interpret capabilities of add-on software and hardware

Workload	Full-time hours per semester
*Type*	*Hours*	*Description*
Lecture	32	According to indicative content and learning outcomes
Lab	40	Integrated data acquisition and anlysis
On-line learning	58	Reading and using module preparatory resources
Independent learning	58	Study of module content prior to exam
Total Workload: 188

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Indicative content.
Dataflow-based graphical programming, program commenting/documenting and scalability. Data acquisition and control. Web-based data monitoring and control of remote instruments. Implementation of M-script code and signal processing routines. Data analytical techniques including spectral frequency and time domain analysis (Bode plots, polar plots, …), transforms, digital filters, convolution and correlation, windowing, signal generation, statistics (including covariance, correlation, mean square error, histogram, Pareto charts, Kurtosis, skewness). Simulation techniques of optimisation and Artificial Neural Networks. Real-time data acquisition and analysis to enable point of control in digital and analogue hardware with NIELVIS, PLC and FPGA (field programmable gate array) embedded controllers in FieldPoint and CompactRio systems. Usage of add on software: Real Time, Motion, Vision, DIAdem, PID control, and Design and Simulation..

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Course Work Breakdown
Type	Description	% of total	Assessment Date
In Class Test	MCQ test	50%	Once per semester

Reassessment Requirement
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 1

Indicative Reading List

Peter A. Blume: 2007, The LabVIEW style book, Prentice Hall, Upper Saddle River, NJ, 0131458353
Rick Bitter, Taqi Mohiuddin, Matt Nawrocki: 2001, LabVIEW advanced programming techniques, CRC Press, Boca Raton, FL, 0849320496
Gary W. Johnson, Richard Jennings: 2001, LabVIEW graphical programming, 3, McGraw-Hill, New York, 0071370013
John Essick: 1998, Advanced LabVIEW Labs, 1st Ed, Prentice Hall, 013833949X
Jeffrey Travis, Jim Kring: 2006, LabVIEW for everyone, Prentice Hall, Upper Saddle River, N.J., 0131856723
Bruce Mihura: 2001, LabVIEW for data acquisition, Prentice Hall PTR, Upper Saddle River, N.J., 0130153621
Hall T. Martin, Meg L. Martin: 2000, Labview for Automotive, Telecommunications, Semiconductor, Biomedical, and Other Applications, 1st Edition, Prentice Hall, 013019963X
Andrew L. McDonough: 2001, LabVIEW: Data Acquisition & Analysis for Movement Sciences, Prentice Hall, Upper Saddle River, NJ, 0130128473
Eric Rosow and Jon B. Olansen,: 2002, Virtual bio-instrumentation: Biomedical, Clinical and Healthcare Applications in LabVIEW, 1, Prentice Hall, Upper Saddle River, NJ, 0130652164
Jon Conway and Steve Watts: 2003, A Software Engineering Approach to LabVIEW, Prentice Hall, 0130093653
Kenneth L. Ashley: 2002, Analog electronics with LabVIEW, Prentice Hall PTR, Upper Saddle River, New Jersey, 0130470651
Christopher G. Relf: 2003, Image acquisition and processing with LabVIEW, CRC Press, 0849314801
Nesimi Ertugrul: 2002, LabVIEW for electric circuits, machines, drives, and laboratories, Prentice Hall, Upper Saddle River, NJ, 0130618861
Thomas Klinger: 2003, Image Processing with LabVIEW and IMAQ Vision, Prentice Hall, 0130474150
Sanjay Gupta & Joseph John: 2005, Image Processing with LabVIEW and IMAQ Vision, Tata McGraw Hill, 0070590990
Steven Chapra, Raymond Canale,: 2010, Numerical Methods for Engineers, 6, McGraw-Hill, 0073401064
Douglas C. Montgomery: 2001, Design and analysis of experiments, 5, John Wiley, New York, 0471316490
Ernest O. Doebelin: 1995, Engineering experimentation, McGraw-Hill, New York, 0070173397
Chris Chatfield: 1983, Statistics for technology, Chapman & Hall, London, 0412253402