BEng Mechanical Engineering with Management

Year of entry: 2022

Course unit details:
Data Acquisition & Experimental Methods (Mech)

Unit code MACE21342
Credit rating 10
Unit level Level 2
Teaching period(s) Semester 2
Offered by Department of Mechanical, Aerospace & Civil Engineering
Available as a free choice unit? No

Overview

The course has two distinct elements the theory of data acquisition and its experimental application utilising LabVIEW software and National Instrument’s hardware. The module will be delivered through a combination of ‘hands on’ LabVIEW programming sessions, lectures, resource based learning exercises and a small group project.

This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.  Please see Blackboard / course unit related emails for any further updates

Aims

This unit aims to develop students understanding of theoretical concepts and practical implementation of data acquisition and equip them with the fundamental experimental skills required in mechanical and aerospace disciplines to conceive, design, implement and operate systems in engineering applications.

Syllabus

Lectures
Implementing a LabVIEW Virtual Instrument – Front Panel Design, LabVIEW Data Types, Documenting Code, While Loops, For Loops, Timing a VI, Iterative Data Transfer, Plotting Data.
Data Acquisition Systems – Hardware, Analogue to Digital conversion, Digital to Analogue conversion,
Overview of the I/O process, General purpose I/O card, Considerations for I/O cards, Application software.
Basic Concepts of Measurement – An Experimental approach, Experimental errors, Accuracy, Precision, Calibration, Bias error, Random error, Measurement error, Sensitivity, Range, Resolution, Offset, Linearity, Hysteresis, Response time, Noise.
LabVIEW troubleshooting and Debugging – Help Utilities, Correcting Broken Vis, Debugging Techniques
Undefined or Unexpected Data, Error Checking and Error Handling, Plotting data, Case structures.
Arrays – Creating arrays, 2D Arrays, Initializing, Creating constants, Auto indexing, Creating 2D Arrays
Clusters – Background, Arrays vs clusters, Creating, Cluster constants, Order, Assembling a cluster, Modifying a cluster, Error clusters
Common Design Techniques - sequential programming, state programming, State transition diagrams
State machines: (1) Infrastructure, (2) Default transition, (3), Transition between 2 states, (4) Case structure transition, (5) Transition array transition.
Signal conditioning – Introduction, Sensors & transducers, Amplification, Attenuation, Isolation,
Linearization, Filtering, Multiplexing, Digital signal conditioning.
Sensors – Introduction, Why do we need to know about sensors?, Categorization of sensors, Choosing a sensor, Specific types of sensor, Strain sensing, Resistive sensors, Infra red sensors, Incremental, optical encoders, Ultrasonic sensors, Inertial sensors, Gyroscopes, Accelerometers
Using Variables – Parallelism, Variables, Functional Global Variables, Race Conditions
Developing Modular Applications - Understanding modularity, Sub Vis, Sub Vis…why use them, Example code without subVIs, Icon and connector pane, Using subVIs
Filtering - Filter classification, Filter characteristics, Low pass, High pass, Band pass, Filtering – examples
, Butterworth

‘Hands on’ Cluster Sessions
Hands on computer session 1 - Data Acquisition & Implementing a .vi
Hands on computer session 2 - Arrays, Clusters, Common Design Techniques
Hands on computer session 3 - Arrays, Clusters, Common Design Techniques
Hands on computer session 4 - Analogue/Digital Signals and Sensors
Hands on computer session 5 – Group project drop in session

Group Project
Title: Design a LabVIEW program that autonomously controls a DANI robot to avoid an object placed in its path and navigate back to its starting position

The Aim of this project is to develop your skills in experimental methods and to apply your LabVIEW programming skills to developing a state machine architecture to control a robot. You will work in a group of 4 people to achieve this task.

Assessment methods

Method Weight
Written exam 50%
Practical skills assessment 40%
Set exercise 10%

Feedback methods

Exam - Solutions to examination and examination released the same day

In class test - Model solutions released the same day with marking scheme. Individual feedback within 2 weeks. 

Practical demonstration - Race performance mark given at end of lab. Feedback on group project given within 2 weeks.

 

Study hours

Scheduled activity hours
Lectures 12
Practical classes & workshops 6
Project supervision 16
Tutorials 18
Independent study hours
Independent study 48

Teaching staff

Staff member Role
Andrew Weightman Unit coordinator

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