Hierarchical Redundancy-Based Monitoring and Robust Seismic Control Systems

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

9909247 Yang A redundancy-based monitoring system for civil structures such as bridges, towers, chimneys, dams and buildings with uncertain dynamic properties located in regions that are susceptible to nature disasters is investigated. This Hierarchial Intelligent Monitoring System is projected as an integrated entity consisting of three principal software components which interact seamlessly with each other in real time and are interfaced with the physical structure. These components have data processing and decision-making capabilities organized into a hierarchy of shielded layers, with each layer employing a decentralized topology of information processing units. The shielding of the layers provides data abstraction and the decentralized topology in each layer creates a mechanism of redundancy. In turn, these factors improve the overall performance and reliability of the monitoring system. The elements of the monitoring system are referred to as the Multilayer Expert Module (MEM), the Multilayer Identification Module (MIM), and the Multilayer Control Module (MCM). The Multilayer Expert Module assists in structural health monitoring (both in 'normal' time and also during earthquakes) and employs advanced damage detection and assessment using neuro-fuzzy logic techniques. The Multilayer Identification Module is primarily responsible for maintaining an active database of system models, which are updated appropriately. The control signals developed in the Multilayer Control Module are implemented by the control system hardware on the actual structure, using devices such as active tendons, active variable stiffness systems, active mass dampers, active base isolators, etc., or combinations of these. Model selection in the MIM and control algorithm selection in the MCM are achieved via fuzzy logic based decision support. The main objectives of this project are to develop a sophisticated expert system which can monitor structural health, and which can detect and accommodate failures needing corrective action despite inaccurate sensory data and to build a reliable identification system which interfaces with the physical structure and which can synthesize accurate structural models in real time, despite the presence of structural uncertainties. The investigation addresses several key aspects of structural monitoring practice and will contribute to the development of safer and more reliable infrastructures.