Beam Deflection Monitoring Based on a Genetic Algorithm Using Lidar Data

Abstract

The Light Detection And Ranging (LiDAR) system has become a prominent tool in structural health monitoring. Among such systems, Terrestrial Laser Scanning (TLS) is a potential technology for the acquisition of three-dimensional (3D) information to assess structural health conditions. This paper enhances the application of TLS to damage detection and shape change analysis for structural element specimens. Specifically, estimating the deflection of a structural element with the aid of a Lidar system is introduced in this study. The proposed approach was validated by an indoor experiment by inducing artificial deflection on a simply supported beam. A robust genetic algorithm method is utilized to enhance the accuracy level of measuring deflection using lidar data. The proposed research primarily covers robust optimization of a genetic algorithm control parameter using the Taguchi experiment design. Once the acquired data is defined in terms of plane, which has minimum error, using a genetic algorithm and the deflection of the specimen can be extracted from the shape change analysis.

Numerical Study of the Environmental and Economic System through the Computational Heuristic Based on Artificial Neural Networks

“…GA is typically used to control the results of the precise population for solving various steep/complicated models based on optimal training. In recent years, GA is implemented in the shotgun metabolomics [ 29 ], wellhead back pressure control system [ 30 ], bearing fault diagnosis of induction motors [ 31 ], energy efficient clustered wireless sensor networks [ 32 ], beam deflection monitoring systems [ 33 ], adjustment problem of sensor acquisition frequency [ 34 ], image processing optimization tasks [ 35 ], and torque adjustment for the ankle push-off in the walking bipedal robots [ 36 ]. The optimization performance in terms of efficiency, accuracy, and viability of GAs is further enhanced by introducing the concept of hybridization with efficient local search.…”

LiDAR-Based Structural Health Monitoring: Applications in Civil Infrastructure Systems

“…By comparing the fitted objects from test specimens and test-bed bridges with the acquired point clouds, defects were located and quantified. An algorithm presented by [142] used TLS for measuring structural deflection and damage. The TLS data was acquired for the loading and unloading scenarios, and the plane was fitted for the point cloud using a robust genetic algorithm.…”

Performance Degradation Assessment of Concrete Beams Based on Acoustic Emission Burst Features and Mahalanobis—Taguchi System

“…It was effective to estimate the severity of structural damage. Some other works based on inverse problem, optimization techniques, and ANN in the field of fracture and damaged identification were carried out by [37][38][39][40][41][42].…”