MEASUREMENT AND INSTRUCTION

EMS3001

2021

Credit points: 15

Subject outline

Data is essential to the design and operation of modern engineering systems. To appreciate the quality of the acquired data, and apply it effectively, it is essential that engineers have a thorough understanding of measurement processes and uncertainty. The subject firstly investigates analogue measurement techniques, and the inherent sources of error and noise. Secondly, the conversion to the digital environment is explored, including examination of the impact of error and noise on the resultant data product, and hence the reliability and applicability of its use in an engineering environment.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorAlex Stumpf

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 3 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesELE1IEL AND MAT1NLA AND MAT1CDE

Co-requisitesN/A

Incompatible subjectsELE3IES

Equivalent subjectsELE3MIN

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Learning resources

Fundamentals of Industrial Instrumentation and Process Control

Resource TypeBook

Resource RequirementPrescribed

AuthorDunn, W.

Year2005

Edition/VolumeN/A

PublisherMcGraw-Hill

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Principles of Measurement Systems

Resource TypeBook

Resource RequirementPrescribed

AuthorBentley J.

Year2005

Edition/VolumeN/A

PublisherPearson

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Analyse sources of error and noise in a measurement system and techniques which may be used to mitigate these errors.
02. Acquire analog data signals into a digital domain and evaluate relevant considerations including quantisation, sampling rate and linearity.
03. Construct and analyse simple amplifier circuits to ascertain and document their functionality through measurements.
04. Analyse the functionality and purpose of standard filter types.
05. Perform measurements with remote (wireless/wired data acquisition tools and evaluate sources of error related to data acquisition and transmission.

Subject options

Select to view your study options…

Start date between: and    Key dates

Bendigo, 2021, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorAlex Stumpf

Class requirements

Laboratory ClassWeek: 10 - 22
One 3.00 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
3 hours problem solving in laboratory

LectureWeek: 11 - 11
One 1.00 hour lecture other recurrence on weekdays during the day from week 11 to week 11 and delivered via face-to-face.
Face-to-face lecture only in week 1

LectureWeek: 10 - 22
Two 1.00 hour lecture per week on weekdays during the day from week 10 to week 22 and delivered via online.
Online lectures for the remainder of the subject

WorkShopWeek: 10 - 22
One 1.00 hour workshop other recurrence on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Problem solving

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*

2 hour written Exam (2,000-words equivalent)

N/ACentral examIndividualNo60 SILO1, SILO2, SILO4, SILO5

Laboratory design and analysis tasks (1,000-words equivalent)
Students demonstrate completed tasks to demonstrators across ten 2-hour laboratories.

N/AOtherIndividualNo20 SILO1, SILO2, SILO3, SILO4, SILO5

3 Written Assignments (750-words total)

N/AAssignmentIndividualNo10 SILO1, SILO2, SILO4, SILO5

Fortnightly online multiple choice quizzes (750-words equivalent total)These quizzes will help keep students on track with online lecture content and provide formative feedback about what they are learning

N/AQuizzesIndividualNo10 SILO1, SILO2, SILO4, SILO5

Melbourne (Bundoora), 2021, Semester 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorAlex Stumpf

Class requirements

Laboratory ClassWeek: 10 - 22
One 3.00 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
3 hours problem solving in laboratory

LectureWeek: 11 - 11
One 1.00 hour lecture other recurrence on weekdays during the day from week 11 to week 11 and delivered via face-to-face.
Face-to-face lecture only in week 1

LectureWeek: 10 - 22
Two 1.00 hour lecture per week on weekdays during the day from week 10 to week 22 and delivered via online.
Online lectures for the remainder of the subject

WorkShopWeek: 10 - 22
One 1.00 hour workshop other recurrence on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Problem solving

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*

2 hour written Exam (2,000-words equivalent)

N/ACentral examIndividualNo60 SILO1, SILO2, SILO4, SILO5

Laboratory design and analysis tasks (1,000-words equivalent)
Students demonstrate completed tasks to demonstrators across ten 2-hour laboratories.

N/AOtherIndividualNo20 SILO1, SILO2, SILO3, SILO4, SILO5

3 Written Assignments (750-words total)

N/AAssignmentIndividualNo10 SILO1, SILO2, SILO4, SILO5

Fortnightly online multiple choice quizzes (750-words equivalent total)These quizzes will help keep students on track with online lecture content and provide formative feedback about what they are learning

N/AQuizzesIndividualNo10 SILO1, SILO2, SILO4, SILO5