Name: DANIEL SCOPEL PAVIOTTI
Publication date: 27/01/2023
Advisor:
Name |
Role |
|---|---|
| WELLINGTON BETENCURTE DA SILVA | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| JULIO CESAR SAMPAIO DUTRA | Co advisor * |
| MARCELO CAMARGO SEVERO DE MACÊDO | Internal Examiner * |
| WELLINGTON BETENCURTE DA SILVA | Advisor * |
Summary: Welding process, widely used in industry, use a large amount of heat to make the union of parts by melting materials. Immediately after the melting process, begins the cooling of the parts, so that the study of the temperature field is very important to understand the materials behavior. The present work shows the efficiency of the particle filter named Sampling Importance Resampling filter (SIR) when solved an inverse problem for estimation of temperature of the weld bead after the process, as well as it is possible to minimized the error through the Approximation Error Model (AEM). Using a simplified model and comparing the results with the direct model was possible to observe the performance of the particle filter through the Root Mean Square (RMS) and the Relative Error (REL) of the monitored measurements. The computational cost is also a data to be observed showing that, as the number of particles is increased the time to compute the results also change. Another important parameter to be monitored, was the torch speed during the process, since it directly influences in temperature field. The results found with the filter was satisfying and are according available literature. The application of AEM to improve the results also is satisfying since this method applied with the chosen filter is not so common for this kind of problem.
Key words: Inverse problem, Particle filter, SIR, AEM, welding
