Application of model reduction technique and structural subsection technique on optimal sensor placement of truss structures

Abstract

Abstract. An optimal sensor placement (OSP) method based on structural subsection technique (SST) and model reduction technique was proposed for modal identification of truss structures, which was conducted using genetic algorithm (GA). The constraints of GA variables were determined by SST in advance. Subsequently, according to model reduction technique, the optimal group of master degrees of freedom and the optimal objective function value were obtained using GA in a case of the given number of sensors. Correspondingly, the optimal number of sensors was determined according to optimal objective function values in cases of the different number of sensors. The proposed method was applied on a scaled jacket offshore platform to get its optimal number of sensors and the corresponding optimal sensor layout. Then modal kinetic energy and modal assurance criterion were adopted to evaluate vibration energy and mode independence property. The experiment was also conducted to verify the effectiveness of the selected optimal sensor layout. The results showed that experimental modes agreed reasonably well with numerical results. Moreover the influence of the proposed method using different optimal algorithms and model reduction technique on optimal results was also compared. The results showed that the influence was very little.

A two-stage optimal sensor placement method for multi-type structural response reconstruction

“…The greater the redundancy in the information collected by the two sensors, the more similar their corresponding information matrices are. To quantify that, Euclidean distance is introduced in this study to evaluate the redundancy level of any two measurement points as shown in equation (17):…”

“…The main idea behind it is to achieve an unbiased estimate of modal coordinates by maximizing the determinant of the Fisher information matrix (FIM). In addition to the classical approaches, novel evolutionary optimization algorithms, such as the genetic algorithm [13][14][15][16][17], monkey algorithm [18,19], firefly algorithm [20,21], and particle swarm optimization algorithm [22], were also utilized to address some of the complex problems arising during the OSP process. All of these evolutionary algorithms have shown promising results in addressing the OSP problem for different large-scale structures, such as suspension bridges [21], dams [23], and high-rise buildings [24].…”

Optimal sensor placement for damage detection of bridges subject to ship collision

“…In comparison with those devoted to modal identification, the OSP methods aiming at damage detection are far from maturing . In this context, OSP methods based on modal and residual sensitivity have been proposed, and model reduction techniques have been introduced to facilitate solution to the OSP problem . Advanced computing techniques, such as neural network, genetic, simulated annealing, and monkey algorithms have been applied for OSP .…”