MACHINE CONDITION MONITORING (CCE)

SHE Level 4
SCQF Credit Points 10.00
ECTS Credit Points 5.00
Module Code MHH324873
Module Leader Martin MacDonald
School School of Computing, Engineering and Built Environment
Subject SCEBE - School Office
Trimesters
  • A (September start)
  • 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.

Syllabus

The teaching syllabus will cover the following areas: Measurable 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 including light emission (photo multipliers, fiber optic techniques, etc.), heat emissions (IR, cameras, direct temperature measurement, etc.), electrical charges (tan d, electrical particle 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. Identify the basic principles common to all condition monitoring systems (AM1).2. Apply mechanical condition monitoring techniques such as vibration analysis, orbital analysis, etc. to obtain reliable data representing plant condition (AM2, AM4).3. Apply electrical condition monitoring techniques such as current monitoring, flux linkage, etc. to obtain reliable data representing plant condition (AM5, AM6).4. Select the appropriate commercial software and hardware available for data collection and analysis (AM1, AM6).5. Describe the fundamental data analysis techniques used in electrical and mechanical condition monitoring such as trend analysis, kurtosis analysis, FFT (AM1, AM6).6. Identify potential fault conditions in electrical and mechanical plant by analyzing the processed data (AM1, AM6).

Teaching / Learning Strategy

The module will be taught using lectures and case studies. Tutorials will be used to reinforce the module material discussed during lecture sessions. Tutorials also serve as a platform of technical discussions to clarify any queries that arise from directed studies.

Indicative Reading

Relevant topics from the following books: -360 1. Donald E. Bently and Charles T. Hatch (2002), Fundamentals of Rotating Machinery Diagnostics , Bently Pressurized Bearing Press . 2. B.K.N. Rao (1996), Handbook of Condition Monitoring . 3. Victor Wowk (1991) Machinery Vibration, Measurement and Analysis , Mc Craw Hill. 4. C. Scheffer and P. Girdhar (2004) , Practical machinery Vibration Analysis & Predictive Maintenance , , IDC technologies. 5. John S. Mitchell (1003), Introduction to Machinery Analysis and Monitoring , PennWell Books. Lihui Wang, Robert X. Gao (2006), Condition Monitoring and control for Intelligent manufacturing , Springer series in advance manufacturing.

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
Assessment (FT) 8.00
Independent Learning (FT) 50.00
Tutorials (FT) 14.00
Lectures (FT) 28.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 1 n/a 30.00 n/a Lab report of 1500 words
Exam (School) 1.50 20.00 n/a Mid-term Test - 20% (Unseen written – 1 ½ Hours)
Exam (Exams Office) 2.00 50.00 45% Final Examination - Final Examination (Unseen written – 2 Hours)