Enhancement of an Optimization-Based Damage Detection Technique

Abstract

Various structural health monitoring (SHM) techniques utilizing vibration signals have been developed for identification of damages in a structure. Many of these studies are based on sensitivity analysis, finite element model (FEM) updating, and optimization techniques. FEM updating technique is one of the major techniques that iteratively minimizes the difference between the modal parameters measured from the real structure and the corresponding analytical predictions. This method would be more beneficial for typical continuous systems such as beams, plates, and shells which cannot be reasonably discretized. One of the drawbacks of these techniques is the large number of unknowns to be estimated. These techniques in the literature that use FEM updating to estimate perturbed parameters for all elements in the model can be time-consuming and ill-conditioned, even for relatively simple structures. The technique also requires a full and accurate finite element model for each monitored structure. A new method to identify damages in a structure using embedded sensitivity functions and optimization algorithms is described and its performance is demonstrated in this paper. The perturbed frequency response function (FRF) is calculated using Taylor series expansion in terms of the baseline system and the embedded sensitivity functions. The optimization process minimizes the difference between the measured FRFs of the damaged structure and the perturbed FRFs calculated from the baseline structure. Structural damages are often characterized by changes in mechanical parameters such as stiffness, mass, and damping. Embedded sensitivity functions offer a means of determining the path that is followed from the baseline to the perturbed FRF of the structure. The robustness and efficiency of suggested structural health monitoring method are discussed in this paper. The accuracy of damage estimation is investigated with respect to various types and values of damages, objective functions, frequency ranges, scale factors, procedures, and noise levels. Precise measurement and monitoring of vibration signals are critical for accurate detection of the location, type, and level of damage. However, in most practical mechanical systems, vibration tests may result in noise on the input or output measurements. Noise on the measurement affects the accuracy of the FRFs and identification of damages in a structure. Based on the results of the study, several parameters and factors in the optimization process and structural dynamics are suggested to enhance the efficiency and robustness of damage identification process. It is shown that the iteration number of the optimization process is significantly reduced. Accurate estimate of damages can be obtained within the range of 2∼5% error with various enhancements applied to the technique.