Monitoring of vulcanization process using measurement of electrical properties during linear increasing temperature

The article presents the possibilities of diagnostics of irreversible chemical reaction vulcanization in case of laboratory prepared rubber mixture based on styrene - butadiene (SBR) using measurements of selected physical parameters. Our work is focused on the measurement of current rheologic parameters (torque at defined shear deformation) and selected electrical parameters (DC conductivity) during linear increasing temperature. The individual steps of vulcanization are well identified by means of measurements of rheologic parameters, while significantly affecting the value of the electrical conductivity. The value of the electrical conductivity increases with the increasing of rate of the crossbridging reactions during vulcanization. The rate of the heating affects both types of measurements. When the rate of the heating is increasing the temperature of the beginning of networking step of reactions and also the rate of vulcanization grow. The sensitivity of the both types of measurements allows a good mathematical description of the temperature dependence of the torque and the electric conductivity during the vulcanization of rubber mixtures based on SBR

Determining of Maximum Stress in Circular and Circular Hollow Rod by Measurement of Strains

The contribution deals with determining of stress from measured values of strains. Gauge strains, which were linked in half-bridge, and the universal measurement system QuantumX MX840 were used to experimentally obtain the strains. Rods with circular section and hollow circular section serve as tests samples. Students within the educational process will have the opportunity to acquaint with the universal measuring system and see the interconnectedness of theory and practical application

The Relationship Between Mechanical and Electrical Properties During Vulcanisation of SBR Based Rubber

The aim of this paper is description of vulcanization process by monitoring of selected electrical and mechanical parameters. The experiments have shown that the vulcanization process can be qualitatively and quantitatively evaluated on the basis of measurements of mechanical (standard procedure in rubber industry) and also electrical parameters. The results obtained for model system SBR rubber mixture under conditions of linear heating are presented also

A monitoring of the kinetics thermally degradation selected rubber by electrical methods

The work presents the possibilities of diagnostics of irreversible chemical reaction - thermal degradation in case of industry prepared rubber mixture based on styrene - butadiene (SBR) using measurements of selected physical parameters. Our attention was focused on the measurement of electrical parameters (electrical conductivity). Procedure of the measurement of electrical properties was applied at the constant temperatures from the range 150 °C to 200 °C. The determination of electrical properties by means of the measurements of time dependencies of alternate conductivity (σAC=σ(t)), were performed in frequency range 20Hz - 100kHz. It is possible describe significant constants of the kinetics of degradation reaction (reaction rate coefficient) by the solution of differential equations and by mathematical approximation. The constants are exponentially dependent on the temperature of thermal degradation. In addition the approximation allows describe the thermal degradation in the temperature range outside of the monitoring interval. © 2019 Author(s).Slovak Science Foundation [VEGA 1/0235/18]; Research & Development Operational Programme - ERDF [ITMS: 26220120048

Aplikácia metodiky AEO pri registrácii silanizácie gumárenských zmesí

Existuje celá řada experimentálních metod zaměřených na zkoumání strukturálních transformaci (DTA , X - Ray , TSDC , .. ). Tyto metody se liší od sebe spektrem kvantitativních ukazatelů a jejich použití je omezeno povahou zkoumané struktury a procesu. V jistém smyslu, je také možné uvažovat o silanizaci pryžové směsi jako o strukturální transformaci. Je to proměna nezesítěné struktury na zesítěnou. Nicméně , specifičnost uvedené transformace je , že se vyskytuje postupně, formou chemické reakce . Experimentální sledování proměn neuspořádané pryžové směsi může být docela obtížné . Příspěvek se zabývá teoretickými principy experimentální metodiky , které jsme nazvali AER (analýza elektrické odozvy) . Uvedená metodika identifikaci pryžových směsí v průběhu silanizace . Pozornost je zaměřena na modelování možné elektrické odezvy na chemické reakce v systému, skládající se z několik součástí. Výsledky modelu jsou porovnány s experimentálními daty AER měřenými při silanizaci reakce zejména kaučukových směsí.There are a number of experimental methods aimed at the investigation of structural transformations (DTA, X-Ray, TSDC, ...). These methods differ from each other by a spectrum of quantitative indicators and their application is limited by the nature of investigated structures and processes. In a sense, it is also possible to consider the silanization of rubber mixtures as a structural transformation. This is a transformation from the unlinked to crosslinked structure. However, the specificity of mentioned transformation is, that it occurs gradually, by the form of a chemical reaction. Experimental observation of transformations of disordered rubber mixtures type structures can be quite difficult. The contribution deals with theoretical principles of experimental methodology, which we have called AER (Analysis of the Electrical Response). We analyze mentioned methodology just in connection with its application for the identification of rubber mixtures silanization. Our attention is focused on the modeling of a possible electrical response of a chemical reaction in system consisting of several components. Results of the model are compared with experimental data AER measured during silanization reaction in particular rubber mixtures.

Artificial neural network analysis of optical measurements of glasses based on Sb2O3

In the paper we present application of artificial neural network (ANN) on relation between glass composition versus optical transmittance of the chosen glass systems of Sb2O3 - PbCl2 and Sb2O3 – PbO – M2O, where M was Na, K and Li, respectively. The excellent prediction ability of special ANN program developed for this study demonstrates the possibility to influence the glass composition to obtain asked optical properties. The measurements of the temperature dependencies of the direct electric conductivity show the strong influence of the concentration of the individual glass compounds of systems Sb2O3 - PbCl2 and Sb2O3 – PbO – M2O (M is Na, K, Li) on their electric and dielectric properties. Glasses own the same mechanism of the electric conductivity with activation energy, which goes to the value 3.75 eV when temperature is higher than 250 C. Similarly optical transmittance T of systems Sb2O3 - PbCl2 and Sb2O3 – PbO – M2O strongly depends on the glass composition and the amount of defects, too. The glass 70Sb2O3 – 30PbCl2 reached the highest value of T. The minimal content of defects in its volume makes these glasses very perspective for next searching. The measurements of the complex modulus M of mentioned glasses showed their high sensitivity to the changes of glass structure connected with the creation of different sort and the amount of defects. The sensibility of the used methods is comparable with the usual exploited methods (X-ray analysis, optical microscopy) and makes possible to assess partially the quantitative occurrence of defects in the glass volume. A model of neural network for prediction of the optical transmittance was created. Model enables to predict the transmittance with sufficiently small error. After evaluation of results we can state that exploitation of neural networks is advantageous, if it is necessary to express complex mutual relations among sensor-based data. Neural networks are able to realize and appropriately express general properties of data and relations among them and on the contrary to suppress relationships which occur sporadically or they are not sufficiently reliable and strong. Their usage enables retrieval of relationships among parameters of the process which with use of common methods are not possible to trace for reason of their mutual interactions, big amount and dynamics. Use of a neural network seems to be suitable tool for estimating different important optical parameters.Web of Science183-424724