**9. Conclusions**

This manuscript shows a methodology that uses some techniques of the field of Multivariate Analysis, which aim is to select, cluster and rank geotechnical-structural instruments of a Hydroelectric power plant, in our case, the Itaipu hydroelectric power plant, in order to maximize the efficiency and effectiveness of the analysis of the readings.

The methodology showed was applied to the instruments called extensometers, locates in different points of block F of the dam, a total of 30 extensometers that with one, two or three point rods totalized 72 measures of monthly displacement. This measures were stored over a period of 10 years, totalizing 120 readings (January/1995 to December/2004). It is important to remember that 24 measures out of the 72 were automated by the company. The ranking of the instruments would be a way to choose the instruments without any previous knowledge about its location, features, or other characteristics. In this way, it is possible to think in applying this methodology in further decision-making when it relates to the automation of additional new instruments.

Itaipu Hydroelectric Power Plant Structural Geotechnical Instrumentation

Temporal Data Under the Application of Multivariate Analysis – Grouping and Ranking Techniques 101

*Mathematics division, Western Paraná State University, Cascavel, Brasil* 

*PPGMNE, Federal University of Paraná, Curitiba, Brasil* 

resíduos líquidos industriais. Disponível em

Construction, v. 33, n. 12, 1999.

(NBR 8681), 2003.

 \*

Corresponding Author

Maria Teresinha Arns Steiner, Andrea Sell Dyminski and Anselmo Chaves Neto

The authors would like to thank Itaipu's Civil Engineering team for instrumentation data

[1] Icold - International Commission on Large Dams. http://www.icold-cigb.org, 2008. [2] CBGB - Comitê Brasileiro de Grandes Barragens. Diretrizes para a inspeção e avaliação

[3] Brasil. Projeto de Lei Nº 1.181/2003. Estabelece diretrizes para verificação da segurança de barragens de cursos de água para quaisquer fins e para aterros de contenção de

[4] Kalustyan, E. S. Assessment and role of risk in dam building. Hydrotechnical

[5] Yenigun, K.; Erkek, C. Reliability in dams and the effects of spillway dimensions on risk

[6] MenescaL, R. de A. Gestão da Segurança de Barragens no Brasil - Proposta de um Sistema Integrado, Descentralizado, Transparente e Participativo. 769 f. Tese (Doutorado em Engenharia Civil) - Departamento de Engenharia Hidráulica e

[7] ABNT – Associação Brasileira De Normas Técnicas. Ações e Segurança nas Estruturas

[8] Osako, C. I. A Manutenção dos Drenos nas Fundações de Barragens - O Caso da Usina Hidrelétrica de Itaipu. 126 f. Dissertação (Mestrado em Construção Civil). – Setor de

[9] FEMA – Federal Emergency Management Agency, Federal Guidelines For Dam Safety,

[10] Silveira, J. F. A. Instrumenatação e Comportamento de Fundações de Barragens de

[11] Matos, S. F. Avaliação de Instrumentos para Auscultação de Barragem de Concreto. Estudo de caso: Deformímetros e Tensômetros para Concreto na Barragem de Itaipu.

de segurança de barragens em operação. Rio de Janeiro, 1983. 26 p.

levels. Water Resources Management, v. 21, p. 747-760, 2007.

Ambiental, Universidade Federal do Ceará, Fortaleza, 2009.

Ciências Exatas, Universidade Federal do Paraná, Curitiba, 2002.

U. S. Department Of Homeland Security, USA, 2004.

Concreto. São Paulo: Oficina de Textos, 2003.

http://www.emtermos.com.br/ABMS/PL\_1181.pdf. Acessoem 19/06/2009.

**Author details** 

Rosangela Villwock \*

**Acknowledgement** 

**10. References** 

and technical contributions.

The methodology used to analyze the problem of the research was composed by the following form: Ward's method was applied in order to cluster 72 rods of extensometers; at the same time, the Factor Analysis was applied in order to rank the rods; latter, the Factor Analysis was applied within each cluster formed by Clustering Analysis.

In the Factor Analysis applied to the 72 rods, there was not need of investigation for any of the rods, once the communality was high for each of them. Observing the 25 rods of extensometers with the highest communality, 14 rods were identified among the ones that were automated by the team of engineers of Itaipu (the automated rods are the ones considered the most important), in other words, the proposed hierachization method (without previous clustering of the rods) identified 14 of the 24 automated rods.

The Clustering Analysis shows that it is possible to find technical justification for the formation of three clusters. The instruments were clustered according the relevant geological characteristics of the foundation mass, although they were not explicitly shown to the technicians.

By observing the clusters 1, 2, and 3, the factor analysis was applied within each cluster in order to perform the ranking of the rods of the extensometers. It was possible to notice that the rods of the automated extensometers are, most of the time, among the first ones of the ranking of each cluster.

In order to identify the 24 rods that are the most relevant, we decided to identify the 8 best ranked rods from each cluster. In this case, there would be 15 of the 24 automated rods. This number of rods coinciding with the automated ones in Itaipu would increase with the aid of a specialist for a better interpretation of the results. For instance, this specialist would detect that cluster 1is formed by rods that are extremely important for the monitoring of dams and that all rods from this cluster should be automated.

Approaches that are similar to this can be used in many other cases, since there are thousands of large construction works of Civil Engineering that use the system of instrumentation, of which the data can and must receive an appropriate treatment.

The approach of an important problem of engineer, the analysis of the instrumentation data of large construction works, clustering techniques and other techniques were applied, in the context of the Multivariate Statistical Analysis, aiming the identification of the instruments that are the most significant ones to the analysis of the behavior of dams.
