SHE Level 4
SCQF Credit Points 10.00
ECTS Credit Points 5.00
Module Code MHH624718
Module Leader Chengke Zhou
School School of Computing, Engineering and Built Environment
Subject SCEBE - School Office
  • B (January start)

Summary of Content

The aim of this half module is to develop in the student the ability to evaluate, in a given situation the most appropriate condition monitoring strategy to assess the condition of electrical and mechanical machinery.


The teaching syllabus will cover the following areas: Meaurable phenomena from different Plant Items: Measurable phenomena associated with degradation from a range of plant items including motors/generators, transformers, cables, bushings, connectors, capacitors and circuit breakers. Fault diagnosis of Rotational Machines: Unbalance, shaft and coupling misalignments, bent shafts, gear and bearing wear, oil whirls and shaft eccentricity. Measurement Strategies and Techniques: A wide range of strategies and associated technologies will be discussed inlcuding light emission (photo mulitpliers, fibre optic techniques,etc.), heat emissions (IR, cameras, direct temperature measurement, etc.), electrical charges (tan 'd', electrical partial discharge, etc.), force, power and vibration. Data Processing and Analysis: For each of the approaches, options with respect to data processing and analysis will be discussed including digital signal processing and computational techniques. Close attention will be paid through examples of the cost benefits and the reliability which can be placed on data with respect to formulating a view on the condition of a give item of plant.

Learning Outcomes

On completion of this module the student should be able to:1. Understand the basic principles common to all condition monitoring systems.2. Apply mechanical condition monitoring techniques such as vibration analysis, orbital analysis, etc. to obtain reliable data representing plant condition.3. Apply electrical condition monitoring techniques such as partial discharge monitoring, etc. to obtain reliable data representing plant condition.4. Appreciate the commercial software and hardware available for data collection and analysis.5. Understand fundamental data analysis techniques used in electrical and mechanical condition monitoring such as trend analysis, kurtosis analysis, FFT.

Teaching / Learning Strategy

The module will be taught using lectures, laboratory demonstrations, and case studies.

Indicative Reading

Relevant topics from the following books: Diagnostics for Machines and Structures, M Dimentburg, et al, J Wiley (1991) Instrumentation for Engineers, J D Turner, Macmillan (1988) Cost Effective Maintenance, W T File, Butterworth (1991) Methodology for Risk Based Inspection (API-RP500) Heavily based on current journals and conference publications.

Transferrable Skills

Analysis and evaluation of journals and publications, increasing analytical skills and research capability. Group skills and interpersonal skills developed by seminars.

Module Structure

Activity Total Hours
Practicals (FT) 12.00
Tutorials (PT) 3.00
Practicals (PT) 6.00
Tutorials (FT) 6.00
Assessment (PT) 12.00
Independent Learning (PT) 67.00
Lectures (PT) 12.00
Assessment (FT) 12.00
Lectures (FT) 12.00
Independent Learning (FT) 58.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 0.00 18.00 n/a Lab exercise report (18%) ( word count 2000 words ) is the course work and Assignment to be made formative.
Exam (Exams Office) 1.50 70.00 35% Final Examination - Unseen written examination-1½Hours
Exam (School) 1.50 12.00 n/a Mid Term Test - Unseen written examination-1½ Hours