Browsing by Author "Coelho, J."
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Analisador paramétrico de transístores com controlo de temperaturaPublication . Campos, F.; Coelho, J.; Gomes, M.; Pinto, A.; Ramos, H.Neste documento é descrito um analisador de características estáticas de transístores de junção bipolar cuja temperatura da cápsula do transístor em teste pode ser controlada, constituindo assim um dos parâmetros de análise. O analisador foi desenvolvido para suprir a necessidade de demonstração em aulas laboratoriais da dependência com a temperatura de algumas características estáticas dos transístores bipolares, tendo portanto um cariz eminentemente pedagógico.
- Statistical classification of road pavements using near field vehicle rolling noise measurementsPublication . Preto Paulo, Joel; Coelho, J.; Figueiredo, MárioLow noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.