Electrocardiography (ECG) is a diagnostic method that allows sensing and record the electric activity of heart [. The measurement of electrical activity is used as a standard twelve-point system. At each of these leads to measure the useful signal and interference was measured. The intensity of interference depends on the artefacts (electrical lines, brum, motion artefacts, muscle, interference from the environment, etc.). For correct evaluation of measured signal there is a need to processing the measured signal to suitable form. At present, the use of electrocardiograms with sensors with contact scanning are difficult to set a time so we decided to use the principle of non-contact sensing. Such a device to measure the ECG was constructed under the project. The disadvantage of such devices is a problem with a high level of noise, which degrades a useful signal. The aim of this article is to pre-process the signals obtained from non-contact sensing. The contactless devices are powered from the network and battery. The electrodes were connected by way of Eithoven bipolar leads. Signals were pre-treated with suitable filters so that they are also appropriate for their subsequent analysis. In the filtration ECG signals was used as a method of linear (low pass filter, high pass, IIR (Infinite Impulse Response) peak, notch filter. The results of many signals clearly demonstrate removing noise in the ECG signals to the point that is also suitable for their analysis.

The aim of the article is to propose a methodology for implementing a model-driven safety analysis of dynamical technology systems. The safety analysis is performed in the process of control system development, especially aiming at safety-critical processes of system operation. The methodology was divided into six basic steps. The individual steps of the methodology are carried out in a hierarchical sequence. Further, roles of individual methodology steps are detailed. In the next part of the article, the principle of safety-critical process monitoring based on models is described.

The content of this article is the proposal of process of the safety analysis for complex dynamic systems. The safety analysis is carried out in process of the proposal of control system for safety-critical processes. In preliminary hazard analysis is done the identifying all possible risks by PHI method. The PHA method is used to analyze these risks. The method of safety analysis depends on various safety-critical states of system which are system are controlled by models. We propose to use the method SQMD for modeling these states. This method combines qualitative and quantitative methods of modeling states and takes advantage of both methods. The model of the proposal is shown in the diagram. The article includes detailed description of the tasks for each step of analysis.

Turbocharger is a device used for compression of gases of different features. I tis a conversion of kinetic energy or mechanical energy into pressure. Compressed media can be vary from pure gases such as hydrogen, oxygen, noble gases to the gas mixtures such as air, a mixture, of hydrogen and others. Gas composition is very important because of its physical and chemical properties depends on many parameters of compressor design [. The basis of modelling surge dynamics of centrifugal compressors is Greitzerov nonlinear model. This article is getting the gear characteristics of the mass flow and pressure increase passing compression system. Another challenge is getting the throttle characteristic mass flow and pressure drop on the throttling valve. These characteristics are necessary for modelling the dynamic model of a centrifugal compressor according Greitzer (1976). For getting these characteristics, it is necessary to know the data of the measurements. Data can be extracted from a manufacturer. One of the most important graphs is compressor characteristic, known as the compressor map.

Surge is a type of instability, that dramatically affects the operation and life of the turbocharger. There were analyzed the options for the control of surge of which were control designed for surge avoidance (method of minimizing the flow through the control valve). This algorithm is based on the logic of closure control valve at a constant speed regardless of the error. Besides of control were designed surge and control curves. To verify the solution was modeled and implemented nonlinear parametric model with downstream with control valve (Fink model) in Matlab. The simulation models are needed for physical systems, and develop good management strategy. Derivation of the compressor characteristic is presented. Dynamic model also includes two characteristics of valves describing mass flow.