scholarly journals A Comparative Study of Genetic and Firefly Algorithms for Sensor Placement in Structural Health Monitoring

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Guang-Dong Zhou ◽  
Ting-Hua Yi ◽  
Huan Zhang ◽  
Hong-Nan Li

Optimal sensor placement (OSP) is an important task during the implementation of sophisticated structural health monitoring (SHM) systems for large-scale structures. In this paper, a comparative study between the genetic algorithm (GA) and the firefly algorithm (FA) in solving the OSP problem is conducted. To overcome the drawback related to the inapplicability of the FA in optimization problems with discrete variables, some improvements are proposed, including the one-dimensional binary coding system, the Hamming distance between any two fireflies, and the semioriented movement scheme; also, a simple discrete firefly algorithm (SDFA) is developed. The capabilities of the SDFA and the GA in finding the optimal sensor locations are evaluated using two disparate objective functions in a numerical example with a long-span benchmark cable-stayed bridge. The results show that the developed SDFA can find the optimal sensor configuration with high reliability. The comparative study indicates that the SDFA outperforms the GA in terms of algorithm complexity, computational efficiency, and result quality. The optimization mechanism of the FA has the potential to be extended to a wide range of optimization problems.

2020 ◽  
Vol 10 (21) ◽  
pp. 7710
Author(s):  
Tsung-Yueh Lin ◽  
Jin Tao ◽  
Hsin-Haou Huang

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.


Author(s):  
Victor Giurgiutiu ◽  
Adrián E. Méndez Torres

Radioactive waste systems and structures (RWSS) are safety-critical facilities in need of monitoring over prolonged periods of time. Structural health monitoring (SHM) is an emerging technology that aims at monitoring the state of a structure through the use of networks of permanently mounted sensors. SHM technologies have been developed primarily within the aerospace and civil engineering communities. This paper addresses the issue of transitioning the SHM concept to the monitoring of RWSS and evaluates the opportunities and challenges associated with this process. Guided wave SHM technologies utilizing structurally-mounted piezoelectric wafer active sensors (PWAS) have a wide range of applications based on both propagating-wave and standing-wave methodologies. Hence, opportunities exist for transitioning these SHM technologies into RWSS monitoring. However, there exist certain special operational conditions specific to RWSS such as: radiation field, caustic environments, marine environments, and chemical, mechanical and thermal stressors. In order to address the high discharge of used nuclear fuel (UNF) and the limited space in the storage pools the U.S. the Department of Energy (DOE) has adopted a “Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste” (January 2013). This strategy endorses the key principles that underpin the Blue Ribbon Commission’s on America’s Nuclear Future recommendations to develop a sustainable program for deploying an integrated system capable of transporting, storing, and disposing of UNF and high-level radioactive waste from civilian nuclear power generation, defense, national security, and other activities. This will require research to develop monitoring, diagnosis, and prognosis tools that can aid to establish a strong technical basis for extended storage and transportation of UNF. Monitoring of such structures is critical for assuring the safety and security of the nation’s spent nuclear fuel until a national policy for closure of the nuclear fuel cycle is defined and implemented. In addition, such tools can provide invaluable and timely information for verification of the predicted mechanical performance of RWSS (e.g. concrete or steel barriers) during off-normal occurrence and accident events such as the tsunami and earthquake event that affected Fukushima Daiichi nuclear power plant. The ability to verify the conditions, health, and degradation behavior of RWSS over time by applying nondestructive testing (NDT) as well as development of nondestructive evaluation (NDE) tools for new degradation processes will become challenging. The paper discusses some of the challenges associated to verification and diagnosis for RWSS and identifies SHM technologies which are more readily available for transitioning into RWSS applications. Fundamental research objectives that should be considered for the transition of SHM technologies (e.g., radiation hardened piezoelectric materials) for RWSS applications are discussed. The paper ends with summary, conclusions, and suggestions for further work.


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