DETECTION OF DAMAGE FOR STRUCTURAL HEALTH MONITORING APPLICATIONS

Abstract

In modern world, the importance of civil engineering structures cannot be denied. With increasing population, the demand of different types of structures is on peak. No doubt, this demand is being fulfilled by using modern construction techniques but their Health monitoring is still an emerging field. Damage Detection is one of the most important technique in context of Structural Health Monitoring and is of great significance for Civil Engineers. In Non-Destructive Evaluation like GPR, Ultrasonic Testing, the method of Vibration based Damage Detection(VBDD) have significance over Traditional Methods as they give a worldwide reaction and are feasible to work for huge structures. While working under Damage Detection techniques, an examination between two frameworks is required, which expresses the pattern or 'sound state’ and includes the underlying modular parameters and Damage Detection. System Identification and then damage detection is done on a Pedestrian Bridge, estimating the dynamic reaction utilizing six Micro Electro Mechanical System (MEMS) triaxial accelerometers. An output only method for modular examination, Frequency Domain Decomposition(FDD) calculation is utilized to acquire the modular properties, for example, normal frequencies and mode shapes. FDD calculations were done on MATLAB and afterward checked and approved by using lab scale beam by doing experiments under various conditions. The Damage is detected by validating results under damaged and undamaged conditions of the beam. After analyzing their frequencies and mode shapes a great correlation was discovered between the changes in frequencies and mode shapes. Last year a comparison was made by analyzing analytical and experimental mode shapes of pedestrian bridge for system identification. After one year, we did testing on the same pedestrian bridge for damage detection by comparing experimental mode shapes and frequencies. But, we found no damage. Keywords: Vibration Based Damage Detection, System Identification, Damage Detection, MEMS accelerometers, Mode shapes, Frequency Domain Decomposition.