Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part.

Optimum Sensor Array for Passive Localization from Time Differences of Arrival

The problem how to improve the accuracy of passive localization from time differences of arrival received considerable interest. The localization performance of any unbiased estimator can be explicitly characterized by certain measures, for example, by the Cramer-Rao lower bound (CRLB) on the estimator variance. The lower the CRLB, the better localization performance. It is well known that the relative sensor-target geometry can significantly affect the performance of any particular localization algorithm. It demonstrates, when target is surrounded by the sensors, uniform angular array is the optimum sensor placement, in which the CRLB is minimized.

Optimal Sensor Placement Based on Damage Sensitivity of Modal Parameters

In this paper through to analyse the sensitivity of several modal parameters about the elastic modulus damage such as characteristic frequency, modal displacement, flexibility matrix and modal curvature , Combined with Fisher information matrix , got the sensitivity of modal parameters on different damage positions of bridge. Computational simulation of Jian Tiao bridge is implemented with this method to find Optimum sensor placement schemes of different parameters. And through the result of numerical analysis we know, flexibility matrix is the most sensitive parameter about damage of elastic modulus, modal sensitivity less than flexibility matrix, the third is frequency. Sensitivity of modal curvature is the dullest, its sensitivity only 1/300 than flexibility matrix. It have different sensor arrange schemes when use four different modal parameters, among them the sensitivity of flexibility matrix is highest.