Health monitoring and vibration control of steel space structures

Abstract

This thesis pursues the understanding of structural behaviour of steel space structures under various types of external loads including atmospheric and stress corrosion, the development of innovative yet practical algorithm for structural damage detection, the combination of health monitoring with vibration control towards a smart steel space structure, and the formation of integrated structural health monitoring and vibration control systems for the best protection of steel space structures. Steel space structures exposed to the open air are inevitably subjected to atmospheric corrosion. This thesis first presents a framework for evaluation of potential damage due to atmospheric corrosion to steel space structures through an integration of knowledge in material science and structural analysis. An empirical model for estimating corrosion of steel material is presented based on long-term experimental data available. Equations relating the sensitivity of structural natural frequencies to the thickness of structural members are derived in consideration of both inner and outer surface corrosions of structural members. A nonlinear static analysis is conducted to evaluate effects of atmospheric corrosion on the stresses of structural members and the safety of steel space structures. By taking a large steel space structure and a reticulated steel shell as two examples, the feasibility of the proposed approach is examined and the potential damage caused by atmospheric corrosion to the structures is assessed. The results demonstrate that the atmospheric corrosion does not obviously affect the natural frequencies of the structures but it does create stress redistribution and cause large stress changes in some of the structural members. The research work on atmospheric corrosion of steel space structures is then extended by involving stress corrosion cracking to estimate corrosion damage to steel space structures in a more realistic way. An evaluation method for coupled atmospheric corrosion and stress corrosion cracking of steel space structures is presented in consideration of different locations and shapes of initial cracks as well as different periods of atmospheric corrosion. The proposed method is applied to the large steel space structure to evaluate its potential corrosion damage. Based on the analytical results of atmospheric corrosion and stress corrosion cracking and the sensory technology, a corrosion monitoring system is conceptually designed to monitor the large steel space structure in corrosive environment and to update the proposed evaluation model, which will also form a sub-system of the integrated health monitoring and vibration control system for the reticulated steel shell in the last phase of this study. The corrosion-induced fracture or local instability of a steel space structure may cause sudden stiffness reductions of some structural members, which will induce the discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. An instantaneous damage index is proposed to detect the damage time instant, location, and severity of structures due to a sudden change of structural stiffness. The proposed damage index is suitable for online structural health monitoring. It can also be used in conjunction with the empirical mode decomposition for damage detection without using intermittency check. A shear building and the reticulated shell are respectively selected to numerically assess the effectiveness and reliability of the proposed damage index with different types of excitation and different levels of damage being considered. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also examined. The results demonstrate that the damage index and damage detection approach proposed can accurately identify the damage time instant and location in the structures due to a sudden loss of stiffness if measurement noise is below a certain level. The relation between the damage severity and the proposed damage index is linear. In most of previous investigations, structural health monitoring and structural vibration control have been treated separately. This study presents an integrated procedure for health monitoring and vibration control of structures using semi-active friction dampers towards a smart structure. The concept of integrated health monitoring and vibration control systems using semi-active friction dampers is introduced by means of a shear building subject to earthquake excitation. It is then applied to the reticulated steel shell with some adjustments in control algorithm and system identification procedure. In such an integrated approach, a model updating scheme based on adding known stiffness by using semi-active friction dampers is first presented to update the structural stiffness and mass matrices and to identify its structural parameters using measured modal information. Based on the updated system matrices, the control performance of semi-active friction dampers with a given control algorithm is then investigated for either the building or the shell against earthquakes. By assuming that the building or the shell suffers certain damage after an extreme event or long-term service and by using the previously identified original structural parameters, a damage detection scheme based on adding known stiffness using semi-active friction dampers is proposed and used for damage detection. The feasibility and effectiveness of the proposed integrated procedure are demonstrated through detailed numerical investigation on the shear building and the reticulated shell. For control devices which cannot provide the required two states of additional stiffness to a structure like the semi-active friction dampers, the parameter identification and damage detection of the controlled structure can be performed in the time domain as long as the control forces can be measured. The equation of motion of the controlled structure is first converted to the parametric identification equation when the inertia forces, damping forces, and restoring forces are linear functions of structural parameters. By taking control forces as known external forces together with measured structural responses, the least-squares method together with an amplitude-selective filter is then used to solve the parametric identification equation, from which the structural parameters can be identified. The same procedure is applied to the controlled structure with damage to identify another set of structural parameters. By comparing the two sets of structural parameters identified, the structural damage can finally be detected and quantified. This proposed procedure is applied to the shear building and the reticulated steel shell with control devices for parametric identification and damage detection with and without measurement noise. The numerical results demonstrate the feasibility and effectiveness of the procedure when the measurement noise is small. The conceptual design of an integrated health monitoring and vibration control system is finally performed in this thesis by taking the reticulated steel shell as an example with the aim of updating analytical models, identifying structural parameters, assessing structural safety, guiding maintenance and repairing work, and activating control devices to protect the structure against extreme loading. In this regard, the structural behaviour, stability and safety of the reticulated steel shell under dead load, wind load, earthquake load, temperature, fire and corrosion are investigated or summarised. Based on these understandings, various types of sensors are selected to measure climate change, atmospheric contamination, material corrosion, wind, earthquake, structural responses, and control forces among others. The numbers and locations of the sensors and control devices are also specified. Two databases are established to collect the information from the sensors and the inspection respectively. The main objectives of installing the integrated system are demonstrated based on the information collected and the layout of the integrated system is illustrated in detail.