Course Catalog 2007-2008

KSU-3266 MONITORING AND DIAGNOSTICS, 6 cr
Monitoring and Diagnostics

Courses persons responsible
Juha Miettinen

Lecturers
Juha Miettinen

Lecturetimes and places
Per I,II: Tuesday 10 - 12, K1308
Per II: Thursday 8 - 10, K1303

Implementations
  Period 1 Period 2 Period 3 Period 4 Period 5 Summer
Lecture 2 h/week 2 h/week - - - -
Exercise - 2 h/week - - - -
Exam  
(Timetable for academic year 2007-2008)

Objectives
The student will familiarize himself with features of some typical machines used in process industry and monitoring and diagnostic techniques for determining their operating state and running condition.

Content
Content Core content Complementary knowledge Specialist knowledge
1. Operation principles and features of machines for determining their behaviour.  Standards and neural networks in diagnostics.   Some special monitoring methods.  
2. Monitoring methods of rotaing machines. Recognising the phenomena from measurement signals.   Case studies of diagnostics.    
3. Diagnosis process of the operation state of machines. Prognosis.       

Requirements for completing the course
Accepted examination.

Evaluation criteria for the course

  • The score of the course is determined by the sum of points from examination and exercises.

  • Used assessment scale is numeric (1-5)

    • Study material
    Type Name Auhor ISBN URL Edition, availability... Exam material Language
    Book Introduction to Machinery Analysis and Monitoring Mitchell, John, S. 0-87814-401-3   Second edition, PennWell Publishing Company No  English 
    Lecture slides Diagnostics and monitoring Juha Miettinen     Dealt out in lectures. Yes  English 
    Book Handbook of condition monitoring Rao, B.K.N 1 85617 2341   First edition, Elsevier Sdvanced Technology No  English 

    Prerequisites
    Prequisite relations (Sign up to TUT Intranet required)

    Remarks

  • Partial passing of course must be in connection with the same round of implementation.

    • Distance learning

  • ITC utilized during the course

    • - In compiling exercise, group or laboratory work
    - In distributing and/or returning exercise work, material etc
    - In the visualization of objects and phenomena, e.g. animations, demonstrations, simulations, video clips

  • Estimate as a percentage of the implementation of the course

    • - Contact teaching: 60 %
    - Distance learning: 0 %
    - Proportion of a student's independent study: 40 %

    Scaling
    Methods of instructionHours
    Lectures 48
    Laboratory assignments 4
    Seminar reports 30
    Information and communication technology 12

    Study materials Hours
    Mitchell, J.S., Introduction to Machine Analysis and Monitoring 30
    Lecture slides, standards 10

    Other scaledHours
    New tools and study methods 4
    Preparation for exam 16
    Exam/midterm exam 3
    Total sum 157

    Last modified 08.06.2007
    Modified byJuha Miettinen