prof. dr. Jožef Vižintin, Fakulteta za strojništvo, Univerza v Ljubljani
Odgovorni raziskovalec na odseku: prof. dr. Đani Juričić
1.5.2009 - 30.4.2012
Because of wear, material stress and environmental influences, mechanical drives are more
inclined to failures than any other item of equipment. Unexpected failures can result in partial or
total breakdown of a production line, destroyed equipment and even catastrophes. That is why
proper maintenance of such equipment is so important. However, it turns to be very costly, as
surveys over the last 20 years reveal that direct maintenance costs in European industry amount to
4% - 8% of the whole companies' income. In power generation sector these figures go even
higher, up to 11%. In addition, the indirect costs caused by degraded product quality, reduced
production efficiency, loss of customers etc. are at least of the same range of magnitude.
A way to reduce the figures above is to abandon the current maintenance paradigms (reactive and
preventive) and make room for cost-efficient condition-based (predictive) maintenance. Trends in
the world clearly follow this direction. For example, manufacturers of advanced process equipment
already provide a new generation of products with embedded diagnostic solutions for automatic
on-line condition monitoring.
However, an open problem in industry is that - according to the estimates about Slovenia - over
95% of installed drives belong to the older generation with no embedded diagnostic functionality.
This means that most of them are poorly monitored or even not monitored at all. As many of such
machines will still be operating for some time, an upgrade with low-cost intelligent condition
monitoring module would significantly improve surveillance, reduce maintenance costs, decrease
failure rates and increase equipment availability. Namely, timely localization of the root cause
would allow for more efficient pro-active maintenance as well as less costly and better planed fault
accommodation.
Intensive research in the area of fault diagnosis and prognosis has been running for several
decades. However, available commercial solutions are still mainly tailored for the particular classes
of drives and are usually limited to fault diagnosis (without prognosis). Some additional
weaknesses extend to: (a) high prices, (b) utilization of a restricted set of diagnostic techniques
(mainly analysis of vibrations or oil analysis) and (c) in some cases limited capability of fault
localization.
The aim of the project is to develop hardware and software prototype called Diagnostic and
Prognostic Processor (DPP, c.f. Fig. 1) for rotational machines and drives. Main innovative features of the
system are:
Economic price range will make the system affordable for a broad range of users in manufacturing, energy and transport sector, which are the most important for the Slovenian economy. The system will allow fusion of features from diverse sources like vibrations sensors, on-line oil analyzers, noise sensors, thermal sensors and motor current and voltage (Fig. 2). Feature extraction will rely on advanced signal processing methods. Clear relationships between signal processing and in-deep insight into the tribological processes will contribute notable added-value to the project. Fault localization and prognosis of the residual life span will be based on the probabilistic models derived from available experimental data. Operating version of the prototype will be built on a DSP platform, which guarantees high performance and cost-effective industrial solutions. System validation will be done on a laboratory benchmark rig.
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (L2-2110)
Domov |
Novice |
Kontakt |
Jezik |
Prijava
Predstavitev |
Ljudje |
R&R teme |
Projekti |
Izobraževanje |
Objave |
Aplikacije |
Partnerji |
Prosta mesta
Copyright © 2007-2024 IJS Vse pravice pridržane.