Research Of Wind Load Identification Of High-rise Buildings

For nearly one hundred years, there is much development in technology on high-rise buildings. The higher the buildings, the more flexible the structures. There has been reported discomfort for users due to great vibration amplitude now and then though there has been few case where wind-induced collapse of high-rise buildings. Wind load has been the control load in high rise building design, in terms of safety and serviceability. Information on wind mainly comes from meteorological department or military department, which investigate wind for purposes other than engineering application. This lead to the lack of wind load information for engineering uses. It is much more difficult to measure wind load directly than to investigate wind-induced responses. In recent years, a new method that investigates wind load through measurement of structure wind-induced response inversely has been developed and is discussed in this dissertation.In this dissertation, mean value of normalized load is applied. Under the assumption of correlation of dynamic wind, using the classic form of equation of state for dynamic systems and least squares criterion, the derivation of mean value of normalized wind load can lead to a method for instance analysis. It is then testified that this method converges.In practice, there are a few scenarios as: the difference between noisy conditions and non-noisy conditions, the influence of different noisy levels, effect of different assumption of correlation of dynamic loads. With different initiations, under non-noisy conditions, structure physical parameters are identified with errors not greater than 0.99%. Similarly the difference between the wind load identified inversely and true value is no greater than 1.25%, which proves that the accuracy of this method does not subject to the effect of the assumed initial rigidity, thus is satisfying. Structure rigidity identification and reversely identified wind load under 15% noise level and three scenarios where ?=4, 8, 12 are investigated. It turned out that different coefficient of correlation of dynamic wind has little impact on identification of rigidity and wind load, and that the result is better under condition where ? is no less than 4. In order to testify the anti-noise capability of this method, different levels of Gaussian white noises are applied into the calculation, proving that under low levels of noises(5% and 15%), the wind load can be better recognized reversely thus with more accuracy. The recognition error of wind load can be up to 9.3% when the noise level reaches to 30%. In general, theoretical and numerical analysis proved the effectiveness and practicability of the combined reverse method using normalized wind load.