Trajectory Identification for Moving Loads by Multicriterial Optimization

Abstract

Moving load is a fundamental loading pattern for many civil engineering structures and machines. This paper proposes and experimentally verifies an approach for indirect identification of 2D trajectories of moving loads. In line with the “structure as a sensor” paradigm, the identification is performed indirectly, based on the measured mechanical response of the structure. However, trivial solutions that directly fit the mechanical response tend to be erratic due to measurement and modeling errors. To achieve physically meaningful results, these solutions need to be numerically regularized with respect to expected geometric characteristics of trajectories. This paper proposes a respective multicriterial optimization framework based on two groups of criteria of a very different nature: mechanical (to fit the measured response of the structure) and geometric (to account for the geometric regularity of typical trajectories). The state-of-the-art multiobjective genetic algorithm NSGA-II is used to find the Pareto front. The proposed approach is verified experimentally using a lab setup consisting of a plate instrumented with strain gauges and a line-follower robot. Three trajectories are tested, and in each case the determined Pareto front is found to properly balance between the mechanical response fit and the geometric regularity of the trajectory.

Least-Square-Method-Based Optimal Laser Spots Acquisition and Position in Cooperative Target Measurement

“…If the physical size of each pixel is obtained by the calibrated internal parameters as s x = 1/ dx , s y = 1/ dy , the dimensions of which are 1/mm, the conversion formula, as shown in Equation (3) [ 29 , 30 , 31 ], is able to facilitate the coordinate transformation from ICS to CCS: …”

“…If the physical size of each pixel is obtained by the calibrated internal parameters as sx = 1/dx, sy = 1/dy, the dimensions of which are 1/mm, the conversion formula, as shown in Equation (3) [29][30][31], is able to facilitate the coordinate transformation from ICS to CCS: The definition of each quantity expressed in Figure 4 is as follows: the coordinates of the target P under the WCS are set to be Pw (Xw, Yw, Zw), and the coordinates of its projection point under the ICS are Pu (Xu, Yu, Zu). θ is the angle between the connection line formed by the origin O and Pw under the CCS and the optical axis Z, which represents the attitude information.…”

Long-Exposure RGB Photography with a Fixed Stand for the Measurement of a Trajectory of a Dynamic Impact Device in Real Scale

“…For this purpose, in drop weight testers, which are available on the market, a drop height program was used, controlled by a motor drive with the automatic lifting of the drop weight with stepless adjustment [18]. The issues regarding a path identification of a moving load based on multiobjective optimization were discussed in a paper [19].…”