UWA Handbook 2024

Unit Overview

Description

This unit covers concepts relating to measurement and noise, enabling students to understand the issues required to achieve high-quality measurements. Topics include accuracy, precision, repeatability, calibration, uncertainty and signal noise. Measurements from a range of sensors (mechanical, optical, electrical) are introduced and subsequent signal conditioning (operational amplifiers, instrumentation amplifiers) are addressed with the aim of maximising signal quality. Statistical methods are discussed to better understand noise processes and how signal noise can be minimised. Methods to improve signal quality (signal to noise ratio) are discussed. Measurement signal and noise are analysed in both the time and frequency domain to better understand the connection between two domains and the importance of measurement bandwidth. Sampling is reviewed to understand the impact of moving from continuous-time (CT) and discrete-time (DT), including discussion of the Nyquist rate and aliasing. The conversion between the analogue to digital domains including CT-DT, system transfer functions, spectral analysis (discrete Fourier transform, discrete-time Fourier transform) and the construction of finite and infinite impulse response filters to reduce noise is discussed.

Credit

6 points

Offering
(see Timetable)

Availability	Location	Mode
Semester 2	UWA (Perth)	Face to face

Details for undergraduate courses

• Level 3 core unit in the Automation and Robotics Engineering; Biomedical Engineering; Mechanical Engineering major sequences

Outcomes

Students are able to (1) explain measurement concepts; (2) use information from instrumentation specifications to design experiments; (3) achieve high-quality measurements using appropriate collection and data manipulation methods; (4) present data numerically and in graphical form in a manner that is clear and concise and includes the uncertainty associated with the measurement; (5) move between the time and frequency domains to interpret measurements and minimise signal noise; (6) assess instrumentation characteristics that affect data collection and measurement; and (7) analyse data in a manner that includes the uncertainty associated with the measurement.

Assessment

Indicative assessments in this unit are as follows: (1) laboratories; (2) quizzes; and (3) final examination. Further information is available in the unit outline.

Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Unit Coordinator(s)

Associate Professor Adrian Keating

Unit rules

Prerequisites

CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation (ID 343)

and ENSC2004 Engineering Mechanics (ID 7437) and

MATH1012 Mathematical Theory and Methods (ID 6013)
or MATX1012 Mathematical Theory and Methods

and GENG2000 Engineering Practice 2
and Enrolment in

Bachelor of Engineering (Honours) or an associated Combined Degree

Incompatibility

MECH4424 Measurement and Noise (ID 2625)

Contact hours

lectures/information sessions: 3 hours per week
practical classes: 1 hour per week
labs: 2 hours per week

Note

It is recommended that students are familiar with the Microsoft Excel spreadsheet program as Excel will be used to perform calculations in assessments/labs.