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Structural modal identification has become increasingly important in health monitoring, fault diagnosis, vibration control, and dynamic analysis of engineering structures in recent years. Based on an analysis of traditional optimization algorithms, this paper proposes a novel sensor optimization criterion that combines the effective independence (E...
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... Among the evolutionary algorithms utilized in engineering problems, the genetic algorithm has gained significant popularity (Ostachowicz et al. 2019;Zamani et al. 2023). The application of GAs in optimal sensor placement problems has been widespread, with studies employing both the original GAs (Liu et al. 2008;Markmiller and Chang 2010;Chow et al. 2011;Soman et al. 2014;Elsersy et al. 2016;Huang et al. 2016;Thiene et al. 2016;Chisari et al. 2017;Yang et al. 2018) and its enhanced versions (Yi et al. 2012;He et al. 2013;Han et al. 2014;Zhou et al. 2014;Zhu et al. 2016;Downey et al. 2018;An et al. 2022;Yang and Xia 2022). The use of genetic algorithms for optimal sensor placement has traditionally involved binary coding, where each gene in the chromosome represents a binary value. ...
Optimal sensor placement (OSP) is a challenging combinatorial problem commonly addressed using Genetic algorithms (GAs), which are well suited to discrete problems. However, coding the problem can be difficult and often requires manual modifications during optimization. On the other hand, applying optimization methods designed for continuous problems to OSP is problematic due to its discrete nature. In this study, we propose a novel triple-structure coding approach that transforms OSP into a permutation and then a continuous optimization problem. This solves gene duplication in GAs and enables direct employment of all suitable methods for continuous problems in sensor placement optimization without any manual intervention. We evaluated the proposed method by implementing the encoding scheme with GA and mutated particle swarm optimization (MPSO) algorithms, two of the most renowned evolutionary algorithms. Additionally, we integrate modal identification within the optimization process for addressing the practicality of mode shape identification in a high-rise structure and a steel dome truss. The proposed coding reduces the cost of GA by 7 to 10 percent and MPSO by 25 to 54 percent, showcasing advancements in cost reduction within the context of sensor placement optimization. Moreover, the percentage of shared nodes in placements obtained from analytical and modal identification dropped to 34% in certain scenarios for the high-rise structure and 26% for the steel dome truss. This emphasizes the substantial distinctions in placements resulting from modal identification using structural responses compared to those obtained exclusively from analytical mode shapes.
... The GA operates through stages of initialization of chromosome sets, fitness evaluation based on predefined criteria, chromosome ranking and culling by fitness, and generation of new chromosomes via crossover and mutation [121], as demonstrated in Figures 6 and 7, where '0' and '1' represented the absence or presence of sensors at specific locations. Due to challenges in this method during crossover and mutation [122], alternative encodings like integer [123], floating-point [124], decimal two-dimensional array [125], quantum probability vectors [126], and dual-structure coding [127] were developed to improve computational efficiency and stability in GA operations. ...
Structural health monitoring (SHM) is critical to maintaining safe and reliable civil infrastructure, but the optimal design of an SHM sensing system, i.e., optimal sensor placement (OSP), remains a complex challenge. Based on the existing literature, this paper presents a comprehensive review of OSP strategies for SHM. It covers the key steps in OSP, from evaluation criteria to efficient optimization algorithms. The evaluation criteria are classified into six groups, while the optimization algorithms are roughly categorized into three classes. The advantages and disadvantages of each group of methods have been summarized, aiming to benefit the OSP strategy selection in future projects. Then, the real-world implementation of OSP on bridges, high-rise buildings, and other engineering structures, is presented. Based on the current progress, the challenges of OSP are recognized; its future development directions are recommended. This study equips researchers/practitioners with an integrated perspective on state-of-the-art OSP. By highlighting key developments, persistent challenges, and prospects, it is expected to bridge the gap between theory and practice.
... Zhu et al. [7] used the quantum genetic algorithm to determine the optimal location of sensors on a concrete dam. Their primary objective was to ascertain the structural modal parameters. ...
Determining the optimal location of sensors in order to identify modal parameters in large structures such as dams is one of the most important and widely used topics in damage detection and health monitoring of structures. In this research, the modal parameters including the natural frequency and mode shape of two arched concrete dams have been calculated using the finite element method for healthy and damaged dams. The reduction of the elastic modulus of concrete in different parts and percentages has been used as the degree of damage. Then, using the modal confidence criterion (MAC) method, the optimal location of the sensors is determined, then the results of this method are compared with the new method. The results show that in both dams, the new method matches the MAC method with 90% accuracy. This new method is a fast and suitable measure to determine the optimal location of sensors in arched concrete dams.
... In 2016, zhai and his colleagues conducted a study to optimize the characteristics of piezoelectric actuators using GA [7]. Also, Genetic algorithms are widely used to determine the proper location of actuators and sensors [8,9]. In this regard, many researches were conducted to find suitable locations of sensors and actuators so that the required energy is minimized. ...
Active control method by improving specification of well-known intelligent numerical search method i.e. genetic algorithm is developed here. This method reduces displacement of the structure by optimizing the control forces at each time step. The efficiency of the genetic algorithm as a part of nature-inspired metaheuristic methods is highly dependent on the constrained objective function. The constrained objective function is achieved by combining the constraints of the optimization problem. There are several methods to numerically combine these constraints. Using appropriate weighting factors to generate this function has been suggested by many researchers. In previous studies, the selection of these factors has been based on experimental or try and error methods and were constant throughout the control period. Proper selection of weighting factors increases the efficiency of the control method. Presenting a new genetic algorithm method in a way selecting weighting factors dynamically over the structural control period is the aim of this paper. Here, weighting factors are non-static in nature and are dynamically selected at each time step according to the memory of the previous step. Numerical results clearly prove the accuracy and efficiency of the proposed control process in comparison with Constant weighting factors methods.
... Genetic algorithms based on the minimisation of Bayes risk as an objective function were employed by Flynn and Todd to optimise the location of piezoelectric sensors and actuators for ultrasonics in a plate (Flynn and Todd, 2010a). The optimal placement of accelerometer sensors have been thoroughly investigated for SHM of small and large scale structures using genetic algorithms based on the maximisation of the probability of crack detection (Markmiller and Chang, 2010), off-diagonal element of modal assurance criterion matrix (He et al., 2013;Zhou et al., 2015;Zhu et al., 2016) and mean square deviation of natural frequencies as fitness functions (Mehrjoo, Khaji and Ghafory-Ashtiany, 2013;Mehrjoo, Khaji and Ghafory-Ashtiany, 2013). Similarly, the optimal placement of piezoelectric sensors and actuators using genetic algorithms bonded on beams (Zhang et al., 2000;Kumar and Narayanan, 2008), plates (Sadri, Wright and Wynne, 1999;Han and Lee, 1999;Ramesh Kumar and Narayanan, 2007;Daraji and Hale, 2012;Daraji and Hale, 2014) and proposed placement method using Ansys package (Daraji, Hale and Ye, 2018) are thoroughly investigated for active vibration control, but there is a lack of study for active structure health monitoring. ...
This paper concerns optimal placement and number of discrete piezoelectric macro fibre composite (MFC) sensors to optimise SHM systems. Its novelty lies in a two-stage placement methodology for discrete piezoelectric transducers, with fitness and objective functions to optimise the location and number of discrete piezoelectric sensors in order to reduce the cost and complexity of data processing and increase the effectiveness in damage detection. The maximisation of sensor voltage amplitude at multiple modes of vibration and the average of sensor normal damage index [Formula: see text] measured for several plates artificially cracked at different positions and orientations are proposed as objective functions to optimise the locations and the number of efficient piezoelectric sensors. A non-normalised root-mean-square deviation [Formula: see text] is introduced in this study in place of the conventional normalised [Formula: see text] to assess the degree of damage and sensor effectiveness. Furthermore, normal damage indices [Formula: see text] and [Formula: see text] normalised to 100% are proposed as the fitness functions. The placement methodology is utilised and verified for stiffened and unstiffened plates; stiffeners are used to break the dynamic symmetry and increase plate complexity. The performance of the placement methodology is tested for a healthy and 12 damaged plates to optimise SHM system based on the maximisation of sensor voltage and average normal damage index [Formula: see text] as objective functions. The results show that the placement methodology is efficient in determining the optimum number and placement of piezoelectric sensors at a low computational effort. The optimum placement of two piezoelectric sensors can efficiently monitor the crack’s initiation at different positions and multiple modes of vibration. The optimal placement and number of sensors have a positive impact on the cost, data acquisition and processing of the active SHM system
... The mutation probability and the crossover probability determine the system's global and local search capabilities. When they are larger, the recombined individuals will have a high probability of appearing and converge quickly; but at the same time, the replacement of the old and the new is too fast, making some superior individuals may be eliminated prematurely [38][39][40]. ...
This paper proposes a dynamic high-type control (DHTC) method based on an interval type-2 fuzzy logic controller (IT2FLC), which is used in the photoelectric tracking system to improve the steady-state accuracy and response speed. Adding integrators to the traditional multi-loop feedback control loop can increase the system type, thereby speeding up the response speed and improving the steady-state accuracy, but there is a risk of integral saturation. Switching the type dynamically according to the system state can avoid integral saturation while retaining the advantages of the high-type. Fuzzy logic control (FLC) can dynamically change the output value according to the input change and has the advantages of fast response speed and strong ability to handle uncertainties. Therefore, in this paper, the FLC is introduced into the high-type control system, and the output of the FLC is used as the gain of the integrator to control the on-off to achieve the goal of dynamic switching type, which is successfully verified in the experiment. IT2FLC introduces a three-dimensional membership function, which further improves the FLC’s ability to handle uncertainties. From the experimental results, compared with T1FLC, IT2FLC’s ability to handle uncertainties is significantly improved. In addition, in order to speed up the calculation speed of IT2FLC, this paper proposes an improved type-reduction algorithm, which is called weighted-trapezoidal Nie-Tan (WTNT). Compared with the traditional type-reduction algorithm, WTNT has faster calculation speed and better steady-state accuracy, and has been successfully applied to real-time control systems, which has good engineering application value. Finally, in order to reduce the interference of human factors and improve the automation level of the system, a multi-population genetic algorithm (MPGA) is used to iteratively optimize the parameters of the FLC, which improves the output accuracy. On the experimental platform of the flexible fast steering mirror (FFSM), the control effects of the traditional controller, T1FLC and IT2FLC are compared, which proves that the IT2FLC-DHTC system has a faster response performance, higher steady-state accuracy, and stronger ability to handle uncertainties.
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Dams are among the most important and largest engineering structures used to supply potable and agricultural water and hydro-power as well as prevent seasonal floods. Human experience has shown that when damage occurs in these megastructures, there are irreversible financial, environmental, and fatal losses. Therefore, the issue of safety and proper performance of dams is of vital importance both in terms of designing new structures or health monitoring of the old structures. This subject is of more particular importance in the case of concrete arch dams, since in the absence of identification of small and minor damages, with the growth and spread of structural damages, a general failure may occur in these infrastructures with considerable human and financial losses. Nevertheless, concrete arch dams have been less broadly considered in the investigation, and most of the researches have included simple structures with a low-degree-of-freedom. Therefore, the main objective of this paper is to study the effects of structural damages (including the intensity and location) on the modal properties of these engineering systems. For this purpose, the modal characteristics of the structure, such as the natural frequencies and the shape-modes, are initially computed using finite element model on a concrete arch dam. Considering different scenarios for damage including, nine different locations (on different vertical and horizontal locations) are chosen. The modal characteristics of the system would be then determined before and after the occurrence of damage. In the presented research, the effects of damages at three levels of arch dam body on the modal parameters of the system are investigated. The comparison of the structural modal parameters of the intact and damaged states shows that first, the natural frequencies of the system have lower sensitivity than mode-shapes of the system, and also the damages to the top and middle are more effective than the corner zones on the modal features of the arc-dam body.
... QGA has been proved to be efficient in solving various kind of problems such as combinatorial and functional optimization problems, engineering optimization problems, image processing and identification, and many others. A few example application can be found in [14,[17][18][19][20][21][22][23][24] and many more. ...
This paper presents a Two-Dimensional Quantum Genetic Algorithm (2D-QGA), which is a new variety of QGA. This variety will allow the user to take the advantages of quantum computation while solving the problems which are suitable for two-dimensional (2D) representation or can be represented in tabular form. The performance of 2D-QGA is compared to two-dimensional GA (2D-GA), which is used to solve two-dimensional problems as well. The comparison study is performed by applying both the algorithm to the task allocation problem. The performance of 2D-QGA is better than 2D-GA while comparing execution time, convergence iteration, minimum cost generated, and population size.
... Moreover, multi-level intelligence [12] and combinations of optimization methods for sensor placement have been studied, e.g. employing multi-agent technology [13] or quantum genetic algorithms [14]. Nature has also been an inspiration for sensor design. ...
Since the dawn of humanity, nature has been a source of inspiration for developing engineering systems, referred to as “nature-inspired systems”. With respect to smart structures instrumented with smart structural health monitoring (SHM) systems, nature-inspired systems may provide promising advancements, for example, by executing self-healing or self-diagnosing processes. However, for developing optimum strategies towards deploying nature-inspired systems to smart structures, the plenitude of nature-inspired systems in SHM need to be classified. This paper aims at reviewing the potential of nature-inspired systems to advance the performance of smart structures. Upon a brief introduction to smart structures and nature-inspired systems, a state-of-the-art review of nature-inspired systems that exhibit potential to advance smart structures is presented, providing decision support on how to advantageously apply the benefits of nature-inspired systems to smart structures.
... Also, it is possible to use the GA for determining sensor and actuator locations (Hale and Daraji, 2012;Zhu et al., and structural displacements are calculated. By substituting these displacements in the objective function and fitting the data, control forces are evaluated. ...
This study focuses on a new active control method by improving specification of well-known intelligent numerical search method i.e. Genetic algorithm. The proposed scheme modifies the specifications of the common Genetic algorithm (CGA) by utilizing two strategies. First, a new constrained objective function is proposed. Then, a procedure is designed for evaluating and reducing time delay in control process. These procedures lead to a new generation of Genetic algorithm (PGA), which is more reliable. For verifying the efficiency of the proposed method, vibrations of several structures are controlled and results are compared with other well-known methods such as CGA, linear quadratic regulator and equivalent critical damping. Numerical results clearly prove the accuracy and efficiency of the proposed control process in comparison with other methods.
