Long-term Dynamic Monitoring of a Concrete Block of the Itaipu Hydroelectric Dam
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Data
2021
Autores
Ardila Ardila, Yeny Victoria
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Resumo
Dams are structures that offer multiple benefits: water for irrigation, energy, flood control,
among others. The structural integrity of these structures can be affected over time by agerelated
deterioration, flooding, earthquakes and other factors, representing a potential risk to
the population and neighboring ecosystems. Therefore, it is necessary to implement monitoring
systems that allow the assessment of the structural integrity of these structures by obtaining
and observing the evolution of the main static and dynamic properties. Dynamic monitoring
involves measuring the structural response in the form of acceleration due to ambient excitations
and then identifying modal parameters: natural frequencies, damping ratios and mode shapes.
As these dynamic characteristics depend on physical properties such as mass or stiffness, the
detection of significant changes in the modal parameters indicates the presence of structural
anomalies. However, many studies have shown that environmental and operational conditions
can induce changes in modal parameters to the same degree as the damage. Therefore, dynamic
monitoring should include the normalization of information to separate the changes in modal
parameters produced by these environmental and operational variables from those produced by
damage. In this work, continuous monitoring of the modal parameters (natural frequencies and
damping ratios) of a hollow-gravity concrete block of the Itaipu Hydroelectric Dam is performed
for three years of operation (January/2018 - December/2020). This block is instrumented with
two triaxial sensors that permanently record acceleration data with a sampling frequency of
200 [Hz]. For this application, a methodology was configured to estimate modal properties
automatically. The procedure starts from the identification results using the SSI-COV algorithm
to 30-minute long accelerations time series. Subsequently, the obtained stability diagram goes
through a cleaning phase, where the spurious modes are discarded, a grouping phase, where
the modes with similar modal characteristics are clustered, and a selection phase, where the
identified physical modes are extracted. These modes are compared with reference modes,
allowing automatic tracking of natural frequencies and damping ratios. The process is repeated
for each set of 30-minute long time series, producing a new set of modal parameters in each
analysis. Once the identification and tracking process is completed, the effect of ambient
temperature and reservoir water level on the temporal evolution of the identified parameters is
analyzed. Autoregressive moving average models with exogenous inputs (ARMAX) are fitted
to separate the effects of environmental variables from the modal parameters. As a result, nine
modes were identified and tracked during the three years of operation. Correlation analysis
between the identified modal parameters and temperature and reservoir water level showed
that these environmental variables influence natural frequencies. ARMAX models were able to
mitigate these effects and reduce the variability in natural frequencies by more than 10 [%] for
the modes associated with the frequencies most influenced by these environmental conditions.
Descrição
Dissertação apresentada ao Programa de Pós-Graduação em Engenharia Civil da Universidade Federal da Integração Latino-Americana, como parte integrante dos requisitos para obtenção do título de Mestre em Engenharia Civil.
Palavras-chave
Modal parameters, Ambient vibrations, Concrete block, Dam, Temperature, Reservoir Level, Cluster, Identification