Performance Evaluation of Damping Systems in Civil Engineering Structures Via Minimal Sensor

TL;DR

This paper presents a unified framework for evaluating damping system performance in civil structures using minimal sensors, leveraging observability and Lie symmetries analysis combined with Kalman filtering for accurate system identification.

Contribution

It introduces a novel unified approach for analyzing observability and symmetries, guiding minimal sensor placement for damping system performance evaluation.

Findings

The framework effectively determines minimal sensor configurations.

Kalman filter accurately estimates structural responses.

Successful case study on seismic damping performance.

Abstract

To control structural responses under various actions, the growing use of supplementary damping systems in modern civil engineering structures necessitates inspecting and evaluating their operational performance postinstallation. However, due to the dispersed placement and complex nonlinearities of these devices, difficulties arise in determining minimal sensor configuration. This is inherently connected to a pivotal challenge: establishing a reliable input-output mapping, which comprises both the mathematical model and sensor arrangements. Prior work indicates this can be achieved through theoretical observability analysis or Lie symmetries analysis, both of which provide different perspectives on the existence of a way to access the solutions of a system identification problem uniquely (at least locally). The present study introduces a unified framework, enhanced by algorithm realization as an application guide, for analyzing the observability and Lie symmetries of a given input-output mapping. We demonstrate its implementation via examples of a building structure with various damping systems under different conditions such as seismic loads, wind loads, and operational vibrations. Finally, we present a case study for an isolation building with an inerter damper and minimal sensor arrangement under seismic action. The results demonstrate that the unscented Kalman filter, a system identification method, can precisely estimate structural responses and assess damping device performance once a reliable input-output mapping is established.