scholarly journals A predator-prey optimization for structural health monitoring problems

2019 ◽  
Vol 281 ◽  
pp. 01004
Author(s):  
Christelle Geara ◽  
Rafic Faddoul ◽  
Alaa Chateauneuf ◽  
Wassim Raphaël
Keyword(s):  
Genetic Algorithm ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Mechanical Model ◽  
Structural Parameters ◽  
Bayesian Updating ◽  
Frame Structure ◽  
Structural Elements ◽  
Predator Prey ◽  
Concrete Frame

Monitoring a structure using permanent sensors has been one of the most interesting topics, especially with the increase of the number of aging structures. Such a technique requires the implementation of sensors on a structure to predict the condition states of the structural elements. However, due to the costs of sensors, one must judiciously install few sensors at some defined locations in order to maximize the probability of detecting potential damages. In this paper, we propose a methodology based on a genetic algorithm of type predator-prey with a Bayesian updating of the structural parameters, to optimize the number and location of the sensors to be placed. This methodology takes into consideration all uncertainties related to the degradation of the elements, the mechanical model and the accuracy of sensors. Starting with two initial populations representing the damages (prey) and the sensors (predator), the genetic algorithm evolves both populations in order to converge towards the optimal configuration of sensors, in terms of number and location. The proposed methodology is illustrated by a two-story concrete frame structure.

Structural Health Monitoring of a Concrete Frame Subjected to Shake Table Excitations Using Smart Aggregates

2014 ◽  
Author(s):  
Wei Chang ◽  
Juin-Fu Chai ◽  
Wen-I Liao
Keyword(s):  
Structural Health Monitoring ◽  
Earthquake Engineering ◽  
Health Monitoring ◽  
Health Condition ◽  
Frame Structure ◽  
Shake Table ◽  
Rc Structures ◽  
Engineering Research ◽  
Structural Health ◽  
Concrete Frame

Structural health monitoring of RC structures under seismic loads has recently attracted dramatic attention in the earthquake engineering research community. In this paper, a piezoceramic-based device called “smart aggregate” was used for the health monitoring of a two stories one bay RC frame structure under earthquake excitations. The RC moment frame instrumented with smart aggregates was tested using a shake table with different ground excitation intensities. The distributed piezoceramic-based smart aggregates embedded in the RC structure were used to monitor the health condition of the structure during the tests. The sensitiveness and effectiveness of the proposed piezoceramic-based approach were investigated and evaluated by analyzing the measured responses.

scholarly journals Bayesian updating for uncertain condition state using permanent monitoring and sequential inspections

2019 ◽  
Vol 261 ◽  
pp. 02005
Author(s):  
Christelle Geara ◽  
Rafic Faddoul ◽  
Alaa Chateauneuf ◽  
Wassim Raphaël
Keyword(s):  
Health Monitoring ◽  
Posterior Probability ◽  
Bayesian Updating ◽  
Frame Structure ◽  
Management Tool ◽  
Numerical Application ◽  
Optimal Sequence ◽  
Posterior Probability Distribution ◽  
Concrete Frame ◽  
Condition State

Structural Health Monitoring using permanent sensors has been a fast growing management tool during the last decade. However, till this date, the installation of sensors on every measurable feature of the structure stills prohibitory costly. In this paper, an approach is proposed for a Bayesian updating of the condition states, based on the output of the monitoring sensors. The posterior probability distribution describing the magnitude of the defect for each element is further updated by inspecting some elements in an optimal sequence. A numerical application of the proposed methodology is presented for a concrete frame structure.

scholarly journals Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7067
Author(s):  
Jia-Hao He ◽  
Ding-Peng Liu ◽  
Cheng-Hsien Chung ◽  
Hsin-Haou Huang
Keyword(s):  
Structural Health Monitoring ◽  
Infrared Thermography ◽  
Mode Shape ◽  
Health Monitoring ◽  
Large Scale ◽  
Frame Structure ◽  
Harsh Environments ◽  
Thermal Imager ◽  
Heat Sources ◽  
Structural Health

In this study, infrared thermography is used for vibration-based structural health monitoring (SHM). Heat sources are employed as sensors. An acrylic frame structure was experimentally investigated using the heat sources as structural marker points to record the vibration response. The effectiveness of the infrared thermography measurement system was verified by comparing the results obtained using an infrared thermal imager with those obtained using accelerometers. The average error in natural frequency was between only 0.64% and 3.84%. To guarantee the applicability of the system, this study employed the mode shape curvature method to locate damage on a structure under harsh environments, for instance, in dark, hindered, and hazy conditions. Moreover, we propose the mode shape recombination method (MSRM) to realize large-scale structural measurement. The partial mode shapes of the 3D frame structure are combined using the MSRM to obtain the entire mode shape with a satisfactory model assurance criterion. Experimental results confirmed the feasibility of using heat sources as sensors and indicated that the proposed methods are suitable for overcoming the numerous inherent limitations associated with SHM in harsh or remote environments as well as the limitations associated with the SHM of large-scale structures.

scholarly journals A Multiobjective Perspective to Optimal Sensor Placement by Using a Decomposition-Based Evolutionary Algorithm in Structural Health Monitoring

2020 ◽  
Vol 10 (21) ◽  
pp. 7710
Author(s):  
Tsung-Yueh Lin ◽  
Jin Tao ◽  
Hsin-Haou Huang
Keyword(s):  
Structural Health Monitoring ◽  
Evolutionary Algorithm ◽  
Health Monitoring ◽  
Sensor Placement ◽  
Frame Structure ◽  
Mode Shapes ◽  
Beam Model ◽  
Optimal Sensor Placement ◽  
Modal Assurance Criterion ◽  
Structural Health

The objective of optimal sensor placement in a dynamic system is to obtain a sensor layout that provides as much information as possible for structural health monitoring (SHM). Whereas most studies use only one modal assurance criterion for SHM, this work considers two additional metrics, signal redundancy and noise ratio, combining into three optimization objectives: Linear independence of mode shapes, dynamic information redundancy, and vibration response signal strength. A modified multiobjective evolutionary algorithm was combined with particle swarm optimization to explore the optimal solution sets. In the final determination, a multiobjective decision-making (MODM) strategy based on distance measurement was used to optimize the aforementioned objectives. We applied it to a reduced finite-element beam model of a reference building and compared it with other selection methods. The results indicated that MODM suitably balanced the objective functions and outperformed the compared methods. We further constructed a three-story frame structure for experimentally validating the effectiveness of the proposed algorithm. The results indicated that complete structural modal information can be effectively obtained by applying the MODM approach to identify sensor locations.

Optimal Accelerometer Locations for Structural Health Monitoring Using Time-Domain System Identification

2006 ◽  
Vol 321-323 ◽  
pp. 273-277 ◽  
Author(s):  
Soon Jung Kwon ◽  
Hae Sung Lee ◽  
Soo Bong Shin
Keyword(s):  
System Identification ◽  
Structural Health Monitoring ◽  
Fisher Information ◽  
Health Monitoring ◽  
Time Domain ◽  
Fisher Information Matrix ◽  
Structural Parameters ◽  
Hessian Matrix ◽  
Information Matrix ◽  
Structural Health

The paper presents two algorithms for determining optimal accelerometer locations for structural health monitoring when structural condition is assessed by a system identification scheme in time-domain. The accelerometer locations are determined by ranking the components of an effective independent distribution vector computed from a Fisher information matrix. One of the proposed algorithms formulates a Fisher information matrix by multiplying acceleration matrix with its transpose and the other as a Gauss-Newton Hessian matrix composed of acceleration sensitivities with respect to structural parameters. Since the structural parameters cannot be known exactly in an actual application, a statistical approach is proposed by setting an error bound between the actual and the baseline values. To examine the algorithm, simulation studies have been carried out on a two-span planar truss. The results using locations selected by the two algorithms were compared.

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