SHE Level 5
SCQF Credit Points 15.00
ECTS Credit Points 7.50
Module Code MMH623521
Module Leader Dejan Karadaglic
School School of Computing, Engineering and Built Environment
Subject Instrumentation and Control
  • A (September start)
  • B (January start)
  • C (May start)

Pre-Requisite Knowledge

A knowledge of measurement, devices and systems to a level equivalent to that covered in Measurement, Theory and Devices.

Summary of Content

With the foundation in measurement and instrumentation provided by Measurement Theory and Devices the student is now equipped to study in depth instrumentation in industrial processes. The module will cover aspects of designing sensor systems for industrial measurements, instrument control, system troubleshooting and optimisation in industrial applications.


Case studies of systems concentrating on selection, installation and performance. The following topics will be covered: 1. Prognostics and Health Management Prognostics and Health Management Terminology, Models for Prognostics and Health Management - dynamic models, (e.g. component vibration models, free and forced vibration response, wave propagation models), data-driven models (e.g. experimental time domain and frequency response models, parametric and nonparametric statistical methods), selection and performance of transducers for measuring variables in an industrial setting, analysis of system performance. 2. Fault Detection and Isolation (FDI) Review of common engineering constraints that hinder acquisition of plentiful data; and consequent motivation for using analytical techniques to infer the condition of systems. Introduction to model-based estimation of unknown states using Luenberger observers; stochastic estimation in the presence of measurement uncertainty using Kalman filters, or system identification. Introduction to fault detection and isolation, with particular emphasis on the use of model-based analytical redundancy using parity relations; and application of such a method to analyse simulated faults in a complex system. 3. Subsea Temperature Sensor Review of temperature sensors suitable for deployment subsea; description of sensor operation; instrumentation requirements; and challenges of sensing in the subsea environment. 4. Machine Condition Monitoring Introduction to condition based maintenance (CBM) and machine condition monitoring (CM). Overview of measurands of interest; displacement, velocity, vibration, temperature, acoustic emission, wear debris. Analysis of bearing and gear vibration. Instrumentation for vibration and analysis; accelerometers, signal conditioning, sampling and acquisition. Analysis of vibration signals; FFT, waterfall diagrams. Review of contact temperature sensors, introduction to radiation based temperature sensors; black-body spectrum, emissivity, sensor types, signal conditioning. Introduction to termography, sensor types, applications. 5. Sensors for Process Instrumentation Selection of transducers for an industrial process application, e.g. beer brewing, pharmaceutical, oil and gas etc. One industrial application will be studied in depth. Introduction to transducer selection for process instrumentation. Overview of Most Critical Measuring and Control Points of Temperature, Pressure, Level, Flow and pH. In depth analysis of sensor selection for: Pressure, Level, Flow, Temperature, pH, Conductivity. Introduction to Automatic Control Valves. Drives and Motors.

Learning Outcomes

On completion of this module the student should be able to:1. specify the instrumentation requirements for a given task;2. determine the likely performance of a system based on instrumentation specification and the application.

Teaching / Learning Strategy

Full-time This module will be taught through in depth case studies which will be presented by lectures, and supported by tutorials, practical laboratories, including some group work, and directed study material. Distance Learning As indicated above, the module is taught through in depth case studies. Students will be guided through the 'lecture material' (presented to the full-time students and included in the study pack) by a Study Guide which will make reference to: core material, background information, relevant published papers and web sites.

Indicative Reading

Course Notes Engineering Condition Monitoring - Practice, Methods and Applications Editor: Ron Barron, Pearson Education, ISBN 0-582-24656-3 Machinery Vibration Analysis & Predictive Maintenance. C Scheffer, P Girdhar Issues of fault diagnosis for dynamic systems. Editors: Ron. J. Patton, Paul M. Frank and Robert N. Clark. Springer 2000. ISBN: 3-540-19968-3 (print) ISBN: 978-1-4471-3644-6 (e-book) Modelling and estimation strategies for fault diagnosis of non-linear systems (Chapter 1: Analytical techniques-based FDI). Author: Marcin Witczak. Lecture notes in Control and Information Sciences series. Editors: M. Thoma and M. Morari. Springer 2007. ISBN: 3-540-71114-7. System Identification - Theory for the user, 2nd edition. Author: Lennart Ljung. Prentice Hall 1999. ISBN 9780136566953 Fiber Optic Sensors: An introduction for Engineers and Scientists, Eric Udd, William B. Spillman, Jr., John Wiley & Sons, 2011 Fiber Optic Sensors, Second Edition, Francis T.S. Yu, Shizhuo Yin, Paul B. Ruffin, CRC Press, 12 Dec 2010 Fiber Bragg Gratings, Raman Kashyap, 2009, ISBN: 978-0-12-372579-0 Michael G.Pecht, Prognostics and Health Management of Electronics, Wiley-Blackwell, 2008 Tony R. Kuphaldt: Lessons in Industrial Instrumentation (c) 2008-2016, under the terms and conditions of the Creative Commons Attribution 4.0 International License. http://www/

Transferrable Skills

The student should: further develop technical writing skills; further develop critical thinking and problem solving; further develop information retrieval skills; further develop independent learning;

Module Structure

Activity Total Hours
Tutorials (FDL) 6.00
Assessment (FDL) 24.00
Tutorials (FT) 6.00
Assessment (FT) 24.00
Practicals (FT) 18.00
Lectures (FT) 20.00
Independent Learning (FT) 82.00
Practicals (FDL) 18.00
Independent Learning (FDL) 102.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 2 n/a 50.00 45% Case study/Design exercise (Learning Outcomes 1 and 2)
Coursework 1 n/a 50.00 45% Case study/Design exercise Learning Outcomes 1 & 2