Joint Laboratory of System Reliability

This Laboratory forms an integral part of the ICET, FTS CTU, Prague. In cooperates als tightly wit the Institute of Computer Science of the Czech Academy of Sciences.

The Joint Laboratory of System Reliability (JLSR) was founded in summer 1996 in the range of the program of university research enhancement of the Ministry of Education of the Czech Republic. The main research activity of this Laboratory was that time concerned to the research program “Signals, Processes and Factors of Reliability in Complicated Systems, especially in Transportation”.

This was a 5 year program started in 1996 and extended to the year 2000. The dominant goals of this project were:

To create a new laboratory (JLSR) as a specialized research institution of the Faculty of Transportation, which will be oriented to problems of control, monitoring and operation automation of transportation systems, with special regard to their reliability and life-time.
To develop the suitable theoretical, methodical and program basis of predictive diagnostics as a general applicable tool for reliability improvement of large and complicated systems especially in transportation, industrial, economic and medical area.
To create a research team with necessary interdisciplinary character, formed not only from killed researcher and professors, but also from young postgraduate and graduate students.
To prepare projects in which the obtained theoretical and methodical results can be projected in real practical problems.
To present both theoretical and practical results on relevant scientific conferences, symposiums and seminars and their publications in scientific journals and books.
 
System reliability and safety as the research field represents one of the most important criterion of all existing systems. Its significance had increased very high in recent years, when in all the areas of human activity much more complex and complicated systems are used. The problems of system reliability is in the focus of interest for many years and much in this area was already done. However, all three main up to now used approaches to system reliability improvement, i.e.

• the improvement of technological quality ode system components,

• the duplication and often multiplication of important system parts and nodes,

• the optimization of the system structure with respect to minimal sensitivity of its function to system parameter changes

does not allow to satisfy the still increasing requirements.

This was the reason why since the late eighties an alternative approach was developed. This is based on application of the knowledge both from the theory of system tolerances and from modern information technologies. These are combined in the so called predictive diagnostics, which represents a methodical tool, by the use of which:

the boundaries of the regions of acceptability (the regions in system parameter space where the system properties are acceptable) of the system under consideration are determined and

the trajectories of the system parameter vector in this space (system life-curve) are investigated when some important independent variable change (the time before all) and the expected further life-curve shape is predicted.

For this purpose the progressive time-series prediction methods (before all based on artificial neural networks) are used;
the optimal correction and restoration of the system parameters is investigated so that one can either: minimize the losses caused by the system missfunction, prevent the eventual system failure or catastrophe.

In the Joint Laboratory of System Reliability (JLSR) works now on the research of predictive diagnostics and its applications about 30 people. The JLSR cooperates in this are also with many other universities and research institutes.

The JLSR has now at disposal the space in the main building of the Faculty of Transportation in the center of Prague and runs also the detached laboratiries in north-west rand of Prague. It has at disposal several adaprive car-driver simulators furnished with scenarios in virtual.