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This paper demonstrates how to use the Random Decrement (RD) technique for identification of linear structures subjected to ambient excitation. The theory behind the technique will be presented and guidelines how to choose the different variables will be given. This is done by introducing a new concept: Quality Assessment. The identification process and quality assessment is illustrated by an analysis of the ambient response of a two-span concrete bridge.

The Random Decrement (RD) technique is a simple and fast method for estimating the correlation functions of Gaussian processes. The RD functions are estimated as an averaging process in the time domain, which makes the technique simple and fast. If the RD technique is applied to stationary zero mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach is not dependent on neither the physical system nor the actual formulation of the RD technique.

The Random Decrement (RD) technique is a simple and fast method for estimating the correlation functions of Gaussian processes. The RD functions are estimated as an averaging process in the time domain, which makes the technique simple and fast. If the RD technique is applied to stationary zero mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach is not dependent on neither the physical system nor the actual formulation of the RD technique.

The problem of estimating frequency response functions and extracting modal parameters is the topic of this paper. A new method based on the Random Decrement technique combined with Fourier transformation and the traditionalpure Fourier transformation based approach is compared with regard to speed and quality. The basis of the new method is the Fourier transformation of the Random Decrement functions which can be used to estimate the frequency response functions. The investigations are based on load and response measurements of a laboratory model of a 3 span bridge. By applying both methods to these measurements the estimation time of the frequency response functions can be compared. The modal parameters estimated by the methods are compared. It is expected that the Random Decrement technique is faster than the traditional method based on pure Fourier Transformations. This is due to the fact that the Random Decrement technique is based on a simple controlled averaging of time segments of the load and response processes. Furthermore, the Random Decrement technique is expected to produce reliable results. The Random Decrement technique will reduce leakage, since the Fourier transformation will be applied to the Random Decrement functions, which has a natura1 decay.