Multivariate analysis applied to concrete dam monitoring data
Sheila Regina Oro1; Anselmo Chaves Neto2; Suellen Ribeiro Pardo Garcia1; Claudio Neumann Júnior3
1 UTFPR; 2 UFPR; 3 ITAIPU BINACIONAL
doi:10.20906/CPS/CILAMCE2017-0348
Resumo
This work is focused on the monitoring of the responses of the concrete structures of the buttresses blocks of Sector D of the Itaipu dam, through the analysis of series of monitoring sensors of structural displacement and foundations of two blocks of the dam and the time series of environmental conditions in the dam surroundings. Multivariate analysis techniques have been used to study the relationship between displacement and environmental conditions, defined by the surface temperature of the concrete, ambient temperature and reservoir water level. The canonical correlation analysis was used to evaluate the influence of environmental variables on the displacement of structures and dam foundations. The application of factor analysis intended to identify the sources of variability in data and the ordering of the sensors according to the action of factors. The dates of the measurements were grouped according to the similarities present in the observations, by applying cluster analysis. Thereafter, the discriminant analysis was used to evaluate the groups as to their homogeneity. The results indicated that the techniques used allow the distinguish of the dam responses and identification of the effects of variations in environmental conditions on the displacements of structures and dam foundations. Then, using these results as input data, the Joint Monitoring Index Blocks Responses (JMIBR) of dam, considering the action of temperature and water level of the reservoir was created in order to contribute to the diagnosis of changes in the dam's structural behavior pattern. The values obtained for JMIBR indicated that the monitored process was under control, stable and, thus, the dam responses were predictable. Updated data were used for method validation.
Palavras-chave: Joint Monitoring Index; Displacements; Environmental Conditions; Factor Analysis