|Semester 1, 2021 Online|
|Short Description:||Meas Science & Instrn Eng|
|Faculty or Section :||Faculty of Health, Engineering and Sciences|
|School or Department :||School of Mechanical and Electrical Engineering|
|Student contribution band :||Band 2|
|ASCED code :||031399 - Electrical, Electronic Enginee|
|Grading basis :||Graded|
Examiner: Andrew Maxwell
An instrument is an Information processing machine involving: sensing (usually analogue); signal processing (analogue and digital); reference to a scale of measurement or a standard; and, display or actuation. Although modern instruments are mostly implemented using electronic technology, their functionality is determined largely by embedded software. The physics of the sensing interface remains fundamental. Design of an optimal instrument (or instrumentation system) to meet a new measurement requirement involves the formal design methodology of measurement science: it is not adequate to rely on experience alone and an "off-the-shelf" solution will usually not be available. This course will prepare students for rigorous design of measurement systems, required in industrial and processing situations, and is the logical successor to ELE3506, with a more philosophical basis.
This course does NOT present a traditional catalogue of standard measurement techniques. In consequence this is a design-oriented course which seeks to develop cross-disciplinary skills in fundamental areas including the use of the Measurement Process Algorithm; the physics, classification and selection of sensors and transducers; theory of scales and standards; signals, systems and modelling techniques; evaluation of available technologies; manufacturing; economic and management implications. Advanced topics will be drawn from: fibre optic and silicon sensors; distributed sensing; rule based and fuzzy sensing; multisensor systems and sensor fusion; intelligence and mechatronics in instruments; and tactile sensing. This course is appropriate for students with a range of backgrounds in the senior or honours years of an engineering or science degree with an appropriate electronics background.
The course objectives define the student learning outcomes for a course. On completion of this course, students should be able to:
- analyse general measurement problems in terms of referents and measurands by means of the Measurement Process Algorithm;
- analyse and model instrumentation systems in terms of information flow;
- define and explain common instrument performance parameters including static and dynamic response;
- analyse and model transducer performance;
- evaluate alternative technologies that might be applied in the realisation of an instrument;
- select and implement major signal recovery methods and strategies for signal-to-noise improvement;
- draw up specifications and plans for the development and management of an instrumentation system;
- choose appropriate transducers and instrumentation system components in the broad areas of temperature measurement and flow measurement;
- evaluate current developments and potential future directions in sensing techniques and measurement system design.
Instruments as Information Machines
1.1. The scope of measurement science and instrumentation engineering.
1.2. Measurement system architecture.
1.3. The differing roles of measurement - knowledge/calibration/control.
Identification of the Measurement Requirement
2.1. The Measurement Process Algorithm - attributes, referents and measurands.
Overview of Sensors and Transducers
3.1. Energy conversion, impedances
3.2. The information machine versus the energy machine.
3.3. Multi- sensitivity, influence variables.
3.4. "Latent Information".
3.5. Sensor individuality.
3.6. Sensor classification - self-generating and modulating.
3.7. Energy domains.
3.8. 2D, 3D and 4D sensor space.
4.1. Reasons for modelling and types of model.
4.2. Energy flow modelling and terminal relations.
4.3. Overview of mathematical techniques, FDM, FEM, applications and examples.
4.4. Models as functional parts of instruments
Design of Measurement Systems
5.1. Philosophy, approaches, engineering design versus industrial design.
5.2. Specifications, the CAD and CAE of instruments.
6.4. Radiative/acoustic/ optical.
Signal Recovery Techniques
7.1. Noise in measurement systems, white, 1/f, drift, offset.
7.2. Theory of averaging, the Boxcar, the Multipoint Averager.
7.3. Autocorrelation and crosscorrelation in instruments.
7.4. Modulation-based techniques, synchronous detection and "lock-in" techniques.
8.1. Temperature and flow measurement
|9.||Management of Instrument Systems||5.00|
Current and Future Directions
10.1. Distributed measurement systems, field bus options.
10.2. Smart sensors, concepts, examples.
10.3. Fibre optic sensing, fibre optic fundamentals, sensing capabilities, options, examples.
10.4. Sensing for robotics, requirements, tactile sensing and imaging.
10.5. Distributed sensing; sensor fusion, concepts and requirements, introduction to fuzzy processing, robotic applications
Text and materials required to be purchased or accessed
ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (https://omnia.usq.edu.au/textbooks/?year=2021&sem=01&subject1=ELE4109)
Please contact us for alternative purchase options from USQ Bookshop. (https://omnia.usq.edu.au/info/contact/)
Student workload expectations
|Description||Marks out of||Wtg (%)||Due Date||Objectives Assessed||Notes|
|PRELIMINARY DESIGN||100||10||31 Mar 2021||1,2,5|
|FINAL DESIGN||300||30||19 May 2021||1,2,4,6,7,8|
|OPEN EXAMINATION - ONLINE||600||60||End S1||1,2,3,4,5,6,7,8,9||(see note 1)|
- This will be an online exam. Students will be provided further instruction regarding the exam by their course examiner via StudyDesk. The examination date will be available via UConnect when the Alternate Assessment Schedule has been released.
Important assessment information
There are no attendance requirements for this course. However, it is the students' responsibility to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.
Requirements for students to complete each assessment item satisfactorily:
Requirements for students to complete each assessment item satisfactorily:
To satisfactorily complete an assessment item a student must achieve at least 50% of the marks or a grade of at least C-. Students do not have to satisfactorily complete each assessment item to be awarded a passing grade in this course. Refer to Statement 4 below for the requirements to receive a passing grade in this course.
Penalties for late submission of required work:
Students should refer to the Assessment Procedure http://policy.usq.edu.au/documents.php?id=14749PL (point 4.2.4)
Requirements for student to be awarded a passing grade in the course:
To be assured of receiving a passing grade a student must obtain at least 50% of the total weighted marks available for the course.
Method used to combine assessment results to attain final grade:
The final grades for students will be assigned on the basis of the weighted aggregate of the marks (or grades) obtained for each of the summative assessment items in the course.
An Open Examination is one in which candidates may have access to any printed or written material and a calculator during the Examination.
Examination period when Deferred/Supplementary examinations will be held:
Normally Deferred and Supplementary Examinations are held in the next Examination period. In S1 2021 selected courses will pilot an early Deferred and Supplementary Examination period held within 30 business days of results release. The list of courses involved can be found at https://cmsauth.usq.edu.au/current-students/academic/exams/supplementary-and-deferred-assessment.
University Student Policies:
Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at http://policy.usq.edu.au.
Students must familiarise themselves with the USQ Assessment Procedures (http://policy.usq.edu.au/documents.php?id=14749PL).
IEEE is the referencing system required in this course. Students should use IEEE style in their assignments to format details of the information sources they have cited in their work. For further information on this referencing style, refer to the below website:
Evaluation and benchmarking
In meeting the University's aims to establish quality learning and teaching for all programs, this course monitors and ensures quality assurance and improvements in at least two ways. This course: 1. Conforms to the USQ Policy on Evaluation of Teaching, Courses and Programs to ensure ongoing monitoring and systematic improvement. 2. Forms part of the Bachelor of Engineering and/or Bachelor of Engineering Technology program and is benchmarked against the: - USQ accreditation/reaccreditation processes which include (i) stringent standards in the independent accreditation of its academic programs, (ii) close integration between business and academic planning, and (iii) regular and rigorous review; and - professional accreditation standards of Engineers Australia.