An Improved Objective Function for Modal-Based Damage Identification Using Substructural Virtual Distortion Method

Abstract

Damage identification based on modal parameters is an important approach in structural health monitoring (SHM). Generally, traditional objective functions used for damage identification minimize the mismatch between measured modal parameters and the parameters obtained from the finite element (FE) model. However, during the optimization process, the repetitive calculation of structural modes is usually time-consuming and inefficient, especially for large-scale structures. In this paper, an improved objective function is proposed based on certain characteristics of the peaks of the frequency response function (FRF). Traditional objective functions contain terms that quantify modal shapes and/or natural frequencies. Here, it is proposed to replace them by the FRF of the FE model, which allows the repeated full modal analysis to be avoided and thus increases the computational efficiency. Moreover, the efficiency is further enhanced by employing the substructural virtual distortion method (SVDM), which allows the frequency response of the FE model of the damaged structure to be quickly computed without the costly re-analysis of the entire damaged structure. Finally, the effectiveness of the proposed method is verified using an eight-story frame structure model under several damage cases. The damage location and extent of each substructure can be identified accurately with 5% white Gaussian noise, and the optimization efficiency is greatly improved compared with the method using a traditional objective function.

Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses

“…First, the first three natural frequencies and mode shapes ( Figure 29) are identified from the responses. The damages are optimized using the objective function considered in [47] and shown in Equation (20), where φ is the number of the structural mode shapes and ω is the number of the natural frequencies, while and are the respective weighting coefficients:…”

Damage Identification Method Using Additional Virtual Mass Based on Damage Sparsity

“…With the rapid development of modern science and technology, there has been an increasing number of large and complex engineering structures [1,2]. When these structures become damaged, the consequences are catastrophic, leading to a significant loss of human lives and property [3,4]. Therefore, it is necessary to adopt effective health-monitoring methods for such structures [5], and damage identification is a crucial aspect of structural health monitoring (SHM) [6,7].…”

Structural Damage Detection and Health Monitoring

“…[36][37][38][39][40][41]. A large number of investigators focus on damage detection [42][43][44][45][46], in which sensing technologies are used to characterize (e.g., location, size, depth, etc.) damage at a shorter time frame than typical monitoring techniques.…”