Application of self-oscillating system for stress measurement in metal

Within the article the applicability of the Self-oscillating Acoustical System (SAS) in order to continuously monitor changes in strain was examined. The essence of SAS is to use a vibration exciter and vibration receiver placed in a distance, which is coupled by an amplifier operating in a positive feedback loop. Changing the speed of wave propagation, which is associated with the change of frequency in the system, can be measure of deformation of the material. The study confirmed the existence of the phenomenon of self-oscillating which can be used to assess the state of metal frame deformation

Human endoprosthesis design using finite element method and rapid prototyping

The paper presents the application of the Finite Element Method (FEM) in the analysis of the stress state in artificial hip prosthesis. A virtual model of hip prosthesis was made using computer aided design systems (CAD). A better construction of this component was developed in combination with numerical analysis. Virtual model allows manufacturing the real workpiece using Rapid Prototyping technology. The article describes also the hardware and softwareaspects of the RP technology

Tailoring the physical properties of non-isocyanate polyurethanes by introducing secondary amino groups along their main chain

A series of linear non-isocyanate polyhydroxyurethanes (NIPUs) were synthesized by aminolysis of a PPO bis-cyclic carbonate with two diamines, one of which (triethylenetetramine, TETA) contains non-reacting secondary amino groups. Thus, varying the composition of the diamine component modulates the density of proton donors. Fourier Transform Infrared Spectroscopy (FTIR) showed that with increasing TETA content in the amine components (20–100 wt%) carbonyl groups tend to form progressively more double hydrogen bonds (HBs). Interestingly, the system without this amine deviates from the trend. In the whole composition range, a higher amount of double HBs correlates monotonously with reduced molecular mobility as observed by differential scanning calorimetry (DSC), dielectric relaxation spectroscopy (DRS), and dynamic mechanical analysis (DMA). It also correlates with the mechanical properties of studied NIPUs which range at room temperature from a viscous liquid to a dimensionally stable, flexible, and durable elastomer, depending on the density of double hydrogen-bonded carbonyls. Hence, the herein proposed approach allows for tailoring thermomechanical properties of NIPUs by modulating density of double hydrogen-bonded carbonyls

Biodegradable, conductive and flexible substrates for opto-electronic devices

Dokonano analizy porównawczej wpływu zawartości poszczególnych składników na wybrane właściwości warstw hybrydowych dwu- i trójskładnikowych na bazie trzech polimerów biodegradowalnych z domieszką jednościennych nanorurek węglowych (SWCN) i ciekłego kryształu 5CB. Pokazano, że najlepsze właściwości dla zastosowań w opto-elektronice jako biodegradowalna elektroda wykazuje kompozyt L,DPLA:5CB:SWCN (10:1:0,5) o dużej elastyczności oraz dobrej stabilności termicznej.A comparative analysis of the impact of the content of individual components on selected properties of two- and three-component hybrid layers based on three biodegradable polymers with an admixture of single-walled carbon nanotubes (SWCN) and 5CB liquid crystal was carried out. The best one for applications in opto-electronics as a biodegradable electrode turned out to be the L,D-PLA:5CB:SWCN (10:1:0,5) composite with high flexibility and good thermal stability. (Biodegradable, conductive and flexible substrates for opto-electronic devices)

Ocena transferu wiedzy i powiązań sfery B+R oraz instytucji otoczenia biznesu z przedsiębiorstwami w województwie małopolskim w 2009 roku. Raport końcowy

The report focuses on the regional system of innovation in małopolskie voivodeship (southern Poland). It presents the results of two empirical stages. The first stage was conducted using computer assisted telephone interviews (CATI) on the sample of 465 enterprises and 51 business support centres. The second stage was conducted as in-depth interview (IDI) on the sample of 20 enterprises and 10 centres. The results are the base for the recommendations for regional policy makes. The reserach was conudcted by the order of Regional Authorities of the Małopolskie Voivodeship

Ocena transferu wiedzy i powiązań sfery B+R oraz instytucji otoczenia biznesu z przedsiębiorstwami w województwie małopolskim w 2009 roku. Raport końcowy

The report focuses on the regional system of innovation in małopolskie voivodeship (southern Poland). It presents the results of two empirical stages. The first stage was conducted using computer assisted telephone interviews (CATI) on the sample of 465 enterprises and 51 business support centres. The second stage was conducted as in-depth interview (IDI) on the sample of 20 enterprises and 10 centres. The results are the base for the recommendations for regional policy makes. The reserach was conudcted by the order of Regional Authorities of the Małopolskie Voivodeship

Impact of the Coulomb field on charged-pion spectra in few-GeV heavy-ion collisions

In nuclear collisions the incident protons generate a Coulomb field which acts on produced charged particles. The impact of these interactions on charged-pion transverse-mass and rapidity spectra, as well as on pion–pion momentum correlations is investigated in Au + Au collisions at $\sqrt{^{S}NN}$ = 2.4 GeV. We show that the low-m$_{t}$ region (m$_{t}$ < 0.2 GeV / c$^{2}$) can be well described with a Coulomb-modified Boltzmann distribution that also takes changes of the Coulomb field during the expansion of the fireball into account. The observed centrality dependence of the fitted mean Coulomb potential energy deviates strongly from a $A_{part}^{2/3}$ scaling, indicating that, next to the fireball, the non-interacting charged spectators have to be taken into account. For the most central collisions, the Coulomb modifications of the HBT source radii are found to be consistent with the potential extracted from the single-pion transverse-mass distributions. This finding suggests that the region of homogeneity obtained from two-pion correlations coincides with the region in which the pions freeze-out. Using the inferred mean-square radius of the charge distribution at freeze-out, we have deduced a baryon density, in fair agreement with values obtained from statistical hadronization model fits to the particle yields

Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles

The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly improve the overall effectiveness and efficiency of systems designed for wear analysis and detection of vibrations that can indicate changes in the physical structure of the industrial components such as bearings, motor shafts, and housing, as well as other parts involved in rotary movement. Recently this concept was also adapted to the field of renewable energy and the automotive industry. The core of the presented prototype is an innovative interface interconnected with augmented reality (AR). The proposed integration of AR goggles allowed for constructing a platform that could acquire data used in rotary components technical evaluation and that could enable direct interaction with the user. The presented platform allows for the utilization of artificial intelligence to analyze vibrations generated by the rotary drive system to determine the technical condition of a wind turbine model monitored by an image processing system that measures frequencies generated by the machine

Self-Powered Wireless Sensor Matrix for Air Pollution Detection with a Neural Predictor

Predicting the status of particulate air pollution is extremely important in terms of preventing possible vascular and lung diseases, improving people&rsquo;s quality of life and, of course, actively counteracting pollution magnification. Hence, there is great interest in developing methods for pollution prediction. In recent years, the importance of methods based on classical and more advanced neural networks is increasing. However, it is not so simple to determine a good and universal method due to the complexity and multiplicity of measurement data. This paper presents an approach based on Deep Learning networks, which does not use Bayesian sub-predictors. These sub-predictors are used to marginalize the importance of some data part from multisensory platforms. In other words&mdash;to filter out noise and mismeasurements before the actual processing with neural networks. The presented results shows the applied data feature extraction method, which is embedded in the proposed algorithm, allows for such feature clustering. It allows for more effective prediction of future air pollution levels (accuracy&mdash;92.13%). The prediction results shows that, besides using standard measurements of temperature, humidity, wind parameters and illumination, it is possible to improve the performance of the predictor by including the measurement of traffic noise (Accuracy&mdash;94.61%)

A Real-Time Distance Measurement System for a Digital Twin Using Mixed Reality Goggles

This paper presents a new system architecture for controlling industrial devices using Mixed Reality (MR) applications and a new method based upon them for measuring the distance between real and virtual points. The research has been carried out using a physical robot and its Digital Twin (DT). The possibility of controlling them using gestures recognized by Mixed Reality goggles has been presented. The extension of the robot&rsquo;s environment with a 3D model capable of following its movements and positions was also analyzed. The system was supervised by an industrial Programmable Logic Controller (PLC) serving as an end point for the data sent by the goggles and controlling the movements of the real robot by activating the corresponding control. The results of the preliminary measurements presented here concerned the responsiveness of the system and showing the influence of system parameters in the accuracy of distance estimation between measured points