EE3901/EE5901 Sensor Technologies
Please refer to the JCU timetable for the schedule. Attendance at all classes is mandatory.
Start here: Subject details
|1||Introduction to sensors|
|3||Sensor fusion and the Kalman filter💻|
|4||Kalman filters for non-linear systems💻||Start Assignment 1|
|5||Resistive sensors||Prac 1: assignment help|
|6||Signal conditioning circuits for resistive sensors||Prac 2: strain gauges|
|7||Capacitive sensors and their signal conditioning circuits||Assignment 1 due (Friday 5pm)|
|8||Design of capacitive sensors💻||Prac 3: capacitive sensors||Start Assignment 2|
|9||Inductive and magnetic sensors|
|10||Self-generating sensors: thermocouples and photodiodes|
|11||Light sensors and applications to NIR spectroscopy💻||Prac 4: eddy current sensors [Moved from week 10]||Assignment 2 due (Friday 5pm)|
|12||Piezoelectric sensors and accelerometers||Prac 5: NIR spectroscopy|
|13||Revision and exam preparation||Prac 6: accelerometers|
💻 Weeks indicated with this symbol have software exercises, typically in Matlab. Please bring a laptop to class if you have one.
|Practicals||Binary mark (1 or 0) for each assessed practical||10%||Report due one week after each assessed practical|
|Assignment 1||Marked on the basis of your submitted report and data||20%||Week 7, Friday 5pm|
|Assignment 2||Marked on the basis of your submitted report||20%||Week 11, Friday 5pm|
|Exam||2 hour theory exam. Similar to tutorial questions||50%||During official university exam period|
Start here. This page describes administrative details about how the subject is organised and how it will run.
Week 1 — Introduction to sensors
This week introduces the concepts of sensors and sensing. Key topics include the vocabulary that we will use to discuss sensor systems in the remainder of the course, for example: the transfer function, sensitivity, resolution, accuracy, precision, noise, bandwidth, and more.
Week 2 — Measurement uncertainty
We review and expand on your knowledge of probability and statistics, and apply this to the problem of measurement. We discuss how to propagate measurement error through calculations. We also briefly introduce calibration.
Week 3 — Sensor fusion and the Kalman filter
Sensor fusion is the process of combining information from multiple sensors to determine the state of a system. This week we will study the Kalman filter, which is one of the most famous and important sensor fusion algorithms.
Week 4 — Kalman filters for non-linear systems
The basic Kalman filter discussed last week is limited to linear systems. This week we investigate two methods to extend the Kalman filter to arbitrary, non-linear systems. Specifically we study the Extended Kalman Filter and the Unscented Kalman Filter.
Week 5 — Resistive sensors
This week we survey some common resistive sensors and study their properties.
Week 6 — Signal conditioning circuits for resistive sensors
This week we study the circuit designs used to interface with resistive sensors.
Week 7 — Capacitive sensors and signal conditioning circuits for reactive sensors
Capacitance is a common mechanism of sensing. This week we study capacitive sensors and capacitive interface circuits.
Week 8 — Design of capacitive sensors with arbitrary geometries
Last week we considered capacitive sensors for plane parallel geometries. However, how would go about analysing capacitors of different geometries? In general, there is no simple formula to calculate the capacitance, and we must turn to numerical simulation on a computer.
Week 9 — Inductive and magnetic sensors
Previously we studied resistive and capacitive sensors. The remaining fundamental circuit element to address is the inductor. Our topics for this week are inductive and magnetic sensors.
Week 10 — Self-generating sensors: thermocouples and photodiodes
This week we study sensors that generate a voltage or current by transforming some other type of energy into electricity.
Week 11 — Light sensors and applications to NIR spectroscopy
This week we study additional aspects of light sensing, and consider an important application in near infrared spectroscopy.
Assignment 1 — Implementing an extended Kalman filter
This task requires you to implement an extended Kalman filter for the scenario of ground vehicle navigation.
Assignment 2 — Designing a capacitive sensor to measure water level
This task requires you to design, build, and test a capacitive sensor to measure the water level in a glass beaker.
Practical 1 — Assignment help
This week we will use the practical session for help with Assignment 1. There is no assessment this week.
Practical 2 — Strain gauges and instrumentation amplifiers
This practical requires you to design and test an interface circuit for strain gauge measurement.
Practical 3 — Capacitive sensors
In this practical, you will experiment with capacitive sensors and sources of interference in capacitive sensing.
Practical 4 — Eddy current sensors
In this practical you will use an eddy current sensor to measure the thickness of various non-conductive plastic sheets.
Practical 5 — Near-infrared spectroscopy
In this practical you will gain experience in analysing hyperspectral images.