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Jožef Stefan
International
Postgraduate School

Jamova 39
SI-1000 Ljubljana
Slovenia

Phone: +386 1 477 31 00
Fax: +386 1 477 31 10
Email: info@mps.si

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Course Description

Sensor Networks for Condition Monitoring of Industrial Assets

Program

Sensor Technologies
Information and Communication Technologies, third-level study programme

Lecturers:

prof. dr. Đani Juričić

Goals:

Course objectives:
• understanding the taxonomy of sensor networks in the area of condition monitoring,
• becoming familiar with basic concepts of condition monitoring,
• getting acquainted with basic signal processing algorithms in sensor networks,
• making students familiar with practical problems.

Competences:
• ability to perform requirements analysis for condition monitoring systems,
• ability to configure a sensor network for system diagnostics and prognostics,
• ability to design algorithms for sensor fusion,
• ability to make use of MIMOSA database.

Content:

• The role of condition monitoring in the maintenance of industrial assets.
• The taxonomy of asset condition monitoring and prognostics of the remaining useful life.
• Components of the industrial sensor networks, sensors and micro-sensors, smart nodes, systems on chip, gateways and protocol converters.
• Feature extraction, Fourier and wavelet transforms, high-order spectra, spectral kurtosis, entropy indices.
• Model based approaches: residuals, (non-linear) Kalman filter.
• Trend change detection, feature fusion,
• Prognostics: statistical approaches based on historical records.
• Data acqusition, storage and display in sensor networks, integration with existing information systems, MIMOSA OSA EAI standard.
• Industrial case studies.
• Individual study of a real case from student’s research work.

Course literature:

Books:
• R. B. Randall. Vibration-based Condition Monitoring. Wiley, 2011.
• S. Mallat. A Wavelet Tour of Signal Processing. Academic Press, Burlington, MA, 3rd edition, 2008.

Periodicals:
• Mechanical Systems and Signal Processing.
• Sensors.
• Journal of Intelligent Manufacturing.

Significant publications and references:

Bibliography:
• 46 original scientific articles,
• 7 invited lectures,
• 145 conference contributions,
• 1 patent,
• 1 patent application,
• 8 other completed works,
• > 230 pure citations,
• h-index: 8.

Reprezentativne reference za področje predmeta:
• S. Strmčnik, Đ. Juričić (Eds.) Case Studies in Control: Putting Theory to Work. Springer, 2013.
• Đ. Juričić, P. Boškoski, M. Gašperin, “Diagnostics and prognostics of rotational machines in non-stationary conditions : how much do details matter?”, CM 2012/MFPT 2012, The 9th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, 12-14 June 2012, London. (Invited semi-plenary)
• P. Boškoski, Đ. Juričić. Fault detection of mechanical drives under variable operating conditions based on wavelet packet Rényi entropy signatures. Mech. Syst. Signal Process.. 2012, vol. 31, pp. 369-381.
• Nosilec več kot 20 raziskovalnih projektov, med drugim programa " Sistemi in vodenje" , in 10 projektov za industrijo.

Examination:

Seminar work with presentation and defence of the solution for the selected problem from student’s research work (60%)
Oral exam (40%)

Students obligations:

Seminar work with presentation and defence of the solution for the selected problem from student’s research work.
Oral exam.

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