Course Catalog 2014-2015

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Course Catalog 2014-2015

MOL-82096 Machinery Diagnostics, 5 cr

Person responsible

Juha Miettinen


Study type P1 P2 P3 P4 Summer Implementations Lecture times and places
Laboratory work


 2 h/week
 1 h/week

+2 h/week
+1 h/week
 6 h/per

MOL-82096 2014-01 Wednesday 14 - 16 , K4242


Accepted examination and exercises. Hyväksytyt tentti ja harjoitukset.
Completion parts must belong to the same implementation

Learning Outcomes

When passing the course the student knows operation monitoring, condition monitoring and machinery diagnostics processes. He knows the fundamentals of machinery vibration and he can identify normal running state and fault states from measurement result. Student can carry out analysis, diagnosis and conclusion of the running state of common industrial machinery by using measurement results and fault finding carts and diagnostics standards. He can implement special signal feature extraction procedures and simulate fault phenomena by using graphical programming soft ware. Student gets familiarize with multi parameter diagnostics and automated machinery diagnostics carried out by neural network and expert systems as well as safe running time prognostics methods.


Content Core content Complementary knowledge Specialist knowledge
1. Operation monitoring and condition monitoring. Monitoring, analysis, diagnostics and prognostics procedure.   Fault mode simulation with LabView software.  Neural networks in data mining and diagnostics of machinery. 
2. Fundamentals of machine vibration. Torsional vibration.   Instrumentation for measurements and analysis.  Theory of lateral and torsional vibration of rotating rotor.  
3. Vibration signal analysis methods. Beating and modulation. High frequency vibration diagnostics. Acoustic emission.  Trouble-Shooting case studies.  Barring vibration of rotating rolls in contact. 
4. Rolling and sliding bearing diagnostics. Gear transmission diagnostics. Universal shaft and shaft alignment disgnostics. Centrifugal pump diagnostics.      
5. Oil monitoring methods. Rainflow analysis of designs. Fault finding charts and standards.     

Instructions for students on how to achieve the learning outcomes

Accepted examination and exercises. Exercises are compulsory and they form a part of the final score of the cource.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Study material

Type Name Author ISBN URL Edition, availability, ... Examination material Language
Book   Fundamentals of rotating machinery diagnostics   Bently, D.E., Hatch, C.T., Grissom, B   ISBN 0-9714081-0-6     Bently pressurised beraing company. 2002. Minden, NV, USA   No    English  
Book   Introduction to Machinery Analysis and Monitoring, second edition   Mitchell, J.S.   0-87814-401-3     PennWell Publishing Co. 1993. Tusla, USA   No    English  
Book   Rotating machinery vibration. From analysis to troubleshooting   Maurice L. Adams, JR   978-1-4398-0717-0     CRC Press Taylor & Francis Group. 2010. Boca Raton, New York, USA   Yes    English  
Lecture slides   Machinery diagnostics   Juha Miettinen       Lecture slides and text material   Yes    English  

Prerequisite relations (Requires logging in to POP)

Correspondence of content

Course Corresponds course  Description 
MOL-82096 Machinery Diagnostics, 5 cr EDE-33156 Machinery Diagnostics, 5 cr  

More precise information per implementation

Implementation Description Methods of instruction Implementation
MOL-82096 2014-01 When passing the source the student knows principles of most common condition monitoring methods and principles of determining the running situation and principles of fault diagnostics. The student can identify normal and abnormal phenomena of different machines based on measurement results. He can choose suitable vibration monitoring method for typical industrial machinery and he can analyse measurement results. The student can combine different measurement data and machine data for defining the running state of a machine or carry out fault diagnosis.   Lectures
Laboratory assignments
Contact teaching: 80 %
Distance learning: 5 %
Self-directed learning: 15 %  


MOL-82096 Machinery Diagnostics_14-15.pdf

Last modified12.01.2015