Abstract

The paper focuses on real-time damage detection based on vibration studies carried out by the Central Building Research Institute (CBRI) structural health monitoring team. The experiment was performed on a 1:3 scaled model of a six- story reinforced concrete (RC) frame with masonry infill in the building dynamics laboratory of CBRI. The forward problem is attended by inducing step-by-step damage in infill to investigate the changes in dynamic response as a result of changes in the physical properties of the structure. Recorded time histories are processed for frequency response spectra (FRS) with fast fourier transform (FFT) and mode shapes are obtained. Changes in natural frequency and modal curvature for each of the five damage cases are analysed for damage detection and location in the structure. An algorithm for damage identification viz. curvature damage factor (CDF) approach is presented.

Highlights

  • A major portion of existing infrastructure worldwide continues to be at potential risk of failure on account of aging, corrosion and overloading, principally during earthquakes

  • The promising domain of Structural health monitoring (SHM) monitors the condition of structures in view of natural hazards like earthquakes and man-made disasters like terrorist attacks, vibrations from generators, air-conditioners, enabling well managed repair, rehabilitation and refurbishment facilities to minimise the impact of the disaster

  • Changes in natural frequency and modal curvature for each of the five damage cases are analysed for damage detection and location in the structure

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Summary

Introduction

A major portion of existing infrastructure worldwide continues to be at potential risk of failure on account of aging, corrosion and overloading, principally during earthquakes. The recurrent check-ups, as well as the improbable failures, which cannot be entirely eliminated, increase maintenance costs, operating expenses and vehicle down-time This necessitates in-service checks for strength and durability of structures allowing early detection and diagnosis of damage. SHM encapsulates the technology and algorithms for sensing the condition of a structure, diagnosing the current state, conducting a prognosis of probable future performance and imparting information for its maintenance, safety and emergency actions This enhances the serviceability and integrity of structures resulting in their reduced life cycle cost. The promising domain of SHM monitors the condition of structures in view of natural hazards like earthquakes and man-made disasters like terrorist attacks, vibrations from generators, air-conditioners, enabling well managed repair, rehabilitation and refurbishment facilities to minimise the impact of the disaster. An algorithm for damage identification viz. the curvature damage factor (CDF) approach is presented

CSIR-CBRI Studied Model
Experimental Investigation
Damage Assessment of RC Building
Damage Detection
Results and Conclusions
Methods
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