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The University of Southampton

SESG6035 Advanced Sensors and Condition Monitoring

Module Overview

This module covers advanced sensors and signal processing techniques for machinery condition monitoring. It discusses the condition monitoring strategies, introduces leading edge sensing methods and advanced signal processing techniques and provide introduction to condition monitoring procedures and system integration.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • the principles of instrumentation and measurement systems
  • the transducers typically encountered in engineering applications
  • condition monitoring approaches, sensor types, sensor placement, data analysis
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • better communicate ideas and understand instrumentation systems
  • determine the condition of a system from performance data and establish if repair or maintenance is necessary
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • communication skills through project work
  • These skills demonstrate a knowledge and understanding of the commercial and economic context of engineering and system processes.
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • design Instrumentation Systems
  • apply signal-processing methods
  • perform practical analysis on actual machines and systems
  • develop a maintenance strategy based on system response
  • understand the advantages and limitations of a variety of techniques for condition monitoring
  • understand the practical aspects of sensor use and type
  • understand the environmental benefits of condition monitoring techniques


Lectures 1-4 Introduction to condition monitoring: - Maintenance philosophies: time based versus condition based Intelligent fault detection - Non destructive testing vs condition monitoring - Condition monitoring procedure and system integration Lectures 5-10 Thick Film sensing and system design: - The role of thick film devices, and comparison to other technologies - Design and manufacture of thick film devices Lectures 11-16 MEMS devices: - Common microfabrication techniques - Applications of MEMS in sensing systems, including pressure sensors, accelerometers, gyroscopes and strain gauges - Overview of microfluidics Energy harvesting and wireless networks Lectures 17-22 Ultrasonic Sensing systems: - Fundamental principles of ultrasonic systems - Applications of ultrasonic sensors including distance and position measurement, flow velocity measurement, non destructive testing Lectures 23-26 Advanced signal processing techniques: - Time domain analysis (Kurtosis, skewness, enveloping, shock pulse method) - Frequency domain analysis (Fourier transforms for spectral analysis, cepstrum) - Time-frequency analysis (STFT, Wavelet) - Artificial intelligence technologies - Lectures 27-32 Condition monitoring techniques - Vibration based techniques - Acoustic emission - Thermal techniques - Oil debris analysis - Strain sensing. Lectures 33-36 Project consultations: - Group based project consultations

Learning and Teaching

Teaching and learning methods

Teaching methods include • A series of lectures in which the emphasis is on the practical application of the techniques. Dedicated project classes. Learning activities include • Worked examples and group projects.

Independent Study111
Project supervision3
Total study time150

Resources & Reading list

Vibration-based condition monitoring: industrial, aerospace and automotive applications.

Comprehensive list of reading materials supplied to students in week 1.. 



MethodPercentage contribution
Continuous Assessment 30%
Final Assessment  70%


MethodPercentage contribution
Set Task 100%


MethodPercentage contribution
Set Task 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisite: SESM3030

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