The aging of civil infrastructure and aerospace structures has led to an increased need to monitor the overall structural health. If growing damage not identified on time, it may has serious consequences, both safety related and economic. However, the complexity of large structures and the difficulty in accessing them makes the use of commonly existing conventional Non Destructive Evaluation (NDE) methods such as visual inspection and instrumental evaluation methods, impractical. An effective alternative in Structural Health Monitoring (SHM) is the use of methods that depend on Vibration-Based Damage Identification (VBDI) techniques. These methods use limited instrumentation to detect the changes in the measured modal characteristics of the structure, that is, its frequencies and mode shapes. These characteristics change with the physical properties of the structure (stiffness, mass and damping matrices) and can be used to help find the location and extent of damage. Optimal matrix update method is one of the VBDI algorithms that depends on finite element modelling (FEM) of the structure and is therefore referred to as model-based damage identification algorithm. The FRF differences method is also one of the VBDI techniques that depends on the directly measured frequency response functions data and is therefore referred to as non model-based or modal-based damage identification algorithm. However, VBDI algorithms still faces a number of challenges that have not been fully resolved. Some of these challenges are highlighted through modal tests designed to provide estimates of damage in a 3D eight-bay free-free frame. Details of tests on a healthy structure as well as on a structure in which predetermined damage has been introduced are presented. A proposed algorithm combining the aforementioned model-based and non-model based methods is introduced to improve the reliability of damage detection. The algorithm is first tested through numerical simulation to predicting damage on the basis of modal test data and the predictions are compared with the known damage.
The regular structural integrity monitoring of major engineering structures such as space structures, orbiting spacecrafts, and civil infrastructures have become an urgent necessity to prevent potential catastrophic failures. The evolution of Vibration Based Damage Identification methods (VBDI) introduced an alternative techniques to the conventional methods. These methods relate changes in the vibration signature (natural frequencies and mode shapes) to changes in structural physical parameters (mass and stiffness) and thus is used to identify damage. The present research focus on developing a combined algorithm includes a model-based method (optimal matrix update) and a Non model-based method (frequency response functions difference), to enhance the reliability of the VBDI techniques. The algorithm presented robust sequential scheme of VBDI techniques and has proven a reasonable success when tested through numerical simulation on a large complex space frame. Since, the FEM of the monitored structure considered as a major constitute of the identification procedure, in the present paper, the ability of the proposed combined algorithm to identify damage in plate-like structure is investigated. A numerical simulation is carried out by introducing several damage scenarios to steel plate and predictions were compared to the known damage. Regardless the assumptions made in the FEM and the introduced simulated random errors introduced at different steps in the algorithm procedures, the algorithm is found to be reliable in identifying damage in plate-like structures. KEYWORDS Vibration-based damage detection, structural health monitoring, identification of damage in plate-like structures, frequency response function, optimal matrix update, optimization.
A system of continuous structural health monitoring would be desirable for early warning of distress in major engineering systems such as space structures and orbiting spacecrafts since they are susceptible to the impact of meteoroids and orbital debris. However, the complexity of some large space structures makes the use of the traditional non-destructive evaluation (NDE), such as visual inspection and instrumental evaluation methods, impractical. A recent development in structural health monitoring systems (SHM) is the use of vibration-based damage identification (VBDI) methods. These methods use limited instrumentation to detect the changes in the measured modal characteristics of the structure, that is, its frequencies and mode shapes. These characteristics change with the physical properties of the structure (stiffness, mass and damping matrices) and can be used to help find the location and extent of damage. Optimal matrix update method is one of the VBDI algorithms that depend on finite element modeling (FEM) of the structure. The FRF differences method is also one of the VBDI techniques that depends on the directly measured frequency response functions data and is therefore referred to as non model-based damage identification algorithm. A proposed two stage algorithm combining the aforementioned model-based and non-model based methods introduced to improve the reliability of damage detection. The algorithm presented a simple robust sequential scheme of VBDI techniques and has proven an acceptable level of success when tested through numerical simulation in the presence of simulated random errors. The present paper focuses on the experimental verifications through the implementation of the algorithm to evaluate its efficiency in identifying damage in real large-scale space structures. The experimental verifications are highlighted through modal tests designed to provide estimates of damage in a 3D eight-bay freefree frame representing part of the International Space Station ISS. Details of tests on a healthy structure as well as on a damaged structure in which predetermined damage has been introduced are presented. This combination allowed identifying different levels of damage for real monitoring of structures using minimum modal data base even when the structure is somewhat complex.
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