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Technical state assessment of charge exchange system of self-ignition engine, based on the exhaust gas composition testing

100%

Rudnicki J. , Zadrag R.

tom 24

nr Special Issue S1

This paper presents possible use of results of exhaust gas composition testing of self - ignition engine for technical state assessment of its charge exchange system under assumption that there is strong correlation between considered structure parameters and output signals in the form of concentration of toxic compounds (ZT) as well as unambiguous character of their changes. Concentration of the analyzed ZT may be hence considered to be symptoms of engine technical state. At given values of the signals and their estimates it is also possible to determine values of residues which may indicate a type of failure. Available tool programs aimed at analysis of experimental data commonly make use of multiple regression model which allows to investigate effects and interaction between model input quantities and one output variable. Application of multi-equation models provides great freedom during analysis of measurement data as it makes it possible to simultaneously analyze effects and interaction of many output variables. It may be also implemented as a tool for preparation of experimental material for other advanced diagnostic tools such as neural networks which , in contrast to multi-equation models, make it possible to recognize a state at multistate classification and - in consequence – to do diagnostic inference. Here , these authors present merits of application of the above mentioned analytical tools on the example of tests conducted on an experimental engine test stand

Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states

100%

Rudnicki J. , Zadrag R.

2014

tom 21

nr 4

Contemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous analysis of effects and interactions between many output variables. They can also be used as a tool in preparing experimental material for other advanced diagnostic tools, such as the models making use of neural networks which, when properly prepared, enable also analysing measurement results recorded during dynamic processes. The article presents advantages of the use of the abovementioned analytical tools and a sample application of the neural model developed based on the results of examination carried out on the engine research rig

Relationship between the replicative age and cell volume in Saccharomyces cerevisiae

80%

Zadrag R. , Kwolek-Mirek M. , Bartosz G. , Bilinski T.

nr 4

Oxygen-dependent and oxygen-independent effects of superoxide dismutase deficiency in yeast

61%

Bilinski T. , Wawryn J. , Krzepilko A. , Swiecilo A. , Zadrag R. , Zyracka E.

nr Supplement 1