Application of advanced statistical methods for extracting long-term trends in static monitoring data from an arch dam

Abstract

The objective of this article is to develop methods for extracting trends from long-term structural health monitoring data and try to set an early warning threshold level based on the results of analyses. The long-term monitoring data in this study is the continuous monitoring of the dam static deformation. Two different approaches were applied to extract features of the long-term structural health monitoring data of the static deformation of the Fei-Tsui Arch Dam (Taiwan). The methods include the singular spectrum analysis with auto regressive model (SSA-AR) and the nonlinear principal component analysis (NPCA) using auto-associative neural network method (AANN). The singular spectrum analysis is a novel nonparametric technique based on principles of multi-variance statistics. An AR model is optimized for each of the principal components obtained from SSA, and the multi step predicted values are recombined to make the time series. Different from SSA method the NPCA-AANN method is also used to extract the underlying features of static deformation of the dam. By using these two different methods, the residual deformation between the estimated and the recorded data was generated, through statistical analysis, the threshold level of the dam static deformation can be determined. Discussion on the two proposed methods to the static deformation monitoring data of Fei-Tsui Arch Dam (Taiwan) is discussed.

Controle estatístico multivariado de instrumentos de monitoramento de barragens

“…A análise de componentes principais tem sido empregada para reduzir a análise em dados de instrumentos de barragens em gráficos de controle multivariados, criar variáveis não correlacionadas e construir distribuições não paramétricas para os resíduos do gráfico T 2 por [2], [6] e [10]. No Brasil, [5] limitou-se ao caso normal univariado.…”

Data-Based Models for the Prediction of Dam Behaviour: A Review and Some Methodological Considerations

“…If the dependency is non-linear, it may lead to misinterpretation of the results. Non-linear principal component analysis (NPCA) can be an alternative, as showed by Loh et al [52] and Kao and Loh [42], who applied it by means of auto-associative neural networks (AANN) to predict radial displacements in an arch dam.…”

Parameter Variations of Identified Model for Static Deformation Analysis of Arch Dam

“…The data were not recorded during dam maintenance time, so the data were unavailable for these days. for static deformation measurement) [6]. The abscissa of Fig.…”

“…Since this dam is located in a very active seismic zone of Taiwan, both dynamic and static monitoring systems of the dam are deployed in this structure [6]. [6].…”

“…However, visual inspections have some shortcomings such as significant labor demands and inaccessible critical locations. The problems of visual inspections can be addressed with field tests, which are conducted to monitor the dynamic and static characteristics of structures [4][5][6]. For a large dam, it is a challenging task to excite structural vibration.…”