scholarly journals Damage identification in steel plate using FRF and inverse analysis

2021 ◽  
Vol 15 (58) ◽  
pp. 416-433
Author(s):  
Samir Khatir ◽  
Magd Abdel Wahab ◽  
Samir Tiachacht ◽  
Cuong Le Thanh ◽  
Roberto Capozucca ◽  
...  
Keyword(s):  
Inverse Analysis ◽  
Damage Identification ◽  
Metaheuristic Algorithms ◽  
Steel Plates ◽  
Exploration And Exploitation ◽  
Wild Horse ◽  
Damage Indicator ◽  
Engineering Problems ◽  
Damage Indicators ◽  
Engineering Projects

Metaheuristic algorithms have known vast development in recent years. And their applicability in engineering projects is constantly growing; however, their deferent exploration and exploitation techniques cause the engineering problems to favor some algorithms over others. This paper studies damage identification in steel plates using Frequency Response Function (FRF) damage indicator to detect and localize the healthy and damaged structure. The study is formulated as an inverse analysis, investigating the performance of three new metaheuristic algorithms of Wild Horse Optimizer (WHO), Harris Hawks Optimization (HHO), and Arithmetic Optimization Algorithm (AOA).  The objective function is based on measured and calculated FRF damage indicators. The results showed that the case of four damages with different damage severity levels presented a good challenge where the HWO algorithm was shown to have the best performance.  Both in convergence speed and CPU time.

Performance Comparison among Vibration Based Indicators in Damage Identification of Structures

2014 ◽  
Vol 592-594 ◽  
pp. 2081-2085 ◽  
Author(s):  
Bharadwaj Nanda ◽  
Aditi Majumdar ◽  
Damodar Maity ◽  
Dipak K. Maiti
Keyword(s):  
Inverse Problem ◽  
Damage Assessment ◽  
Natural Frequencies ◽  
Damage Identification ◽  
Performance Comparison ◽  
Vibration Data ◽  
Flexibility Matrix ◽  
Damage Indicator ◽  
Damage Indicators ◽  
Shape Data

A simple and robust methodology is presented to identify damages in a structure using changes in vibration data. A comparison is made among damage indicators such as natural frequencies, mode shape data, curvature damage factors and flexibility matrices to study their efficacy in damage assessment. Continuous ant colony optimization (ACOR) technique is used to solve the inverse problem related to damage identification. The outcome of the simulated results demonstrates that the flexibility matrix as a damage indicator provides better damage identification.

scholarly journals Roller Bearing Monitoring by New Subspace-Based Damage Indicator

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
G. Gautier ◽  
R. Serra ◽  
J.-M. Mencik
Keyword(s):  
Damage Identification ◽  
Roller Bearing ◽  
Simulated Data ◽  
Efficient Tool ◽  
Vibration Data ◽  
Damage Indicator ◽  
Bearing Defects ◽  
Damage Indicators ◽  
Bearing Characteristic ◽  
Bearing Monitoring

A frequency-band subspace-based damage identification method for fault diagnosis in roller bearings is presented. Subspace-based damage indicators are obtained by filtering the vibration data in the frequency range where damage is likely to occur, that is, around the bearing characteristic frequencies. The proposed method is validated by considering simulated data of a damaged bearing. Also, an experimental case is considered which focuses on collecting the vibration data issued from a run-to-failure test. It is shown that the proposed method can detect bearing defects and, as such, it appears to be an efficient tool for diagnosis purpose.

scholarly journals Enhanced Firefly Algorithm Using Fuzzy Parameter Tuner

2018 ◽  
Vol 11 (1) ◽  
pp. 26 ◽  
Author(s):  
Mahdi Bidar ◽  
Samira Sadaoui ◽  
Malek Mouhoub ◽  
Mohsen Bidar
Keyword(s):  
Firefly Algorithm ◽  
Optimization Problems ◽  
Metaheuristic Algorithms ◽  
Exploration And Exploitation ◽  
Improved Firefly Algorithm ◽  
Engineering Problems ◽  
Exploitation And Exploration ◽  
Low Dimensional ◽  
Fuzzy Parameter

Exploitation and exploration are two main search strategies of every metaheuristic algorithm. However, the ratio between exploitation and exploration has a significant impact on the performance of these algorithms when dealing with optimization problems. In this study, we introduce an entire fuzzy system to tune efficiently and dynamically the firefly algorithm parameters in order to keep the exploration and exploitation in balance in each of the searching steps. This will prevent the firefly algorithm from being stuck in local optimal, a challenge issue in metaheuristic algorithms. To evaluate the quality of the solution returned by the fuzzy-based firefly algorithm, we conduct extensive experiments on a set of high and low dimensional benchmark functions as well as two constrained engineering problems. In this regard, we compare the improved firefly algorithm with the standard one and other famous metaheuristic algorithms. The experimental results demonstrate the superiority of the fuzzy-based firefly algorithm to standard firefly and also its comparability to other metaheuristic algorithms.

scholarly journals Buyer Inspired Meta-Heuristic Optimization Algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 194-219 ◽  
Author(s):  
Sanjoy Debnath ◽  
Wasim Arif ◽  
Srimanta Baishya
Keyword(s):  
Optimization Algorithm ◽  
Optimization Technique ◽  
Statistical Test ◽  
Heuristic Optimization ◽  
Product Choice ◽  
Exploration And Exploitation ◽  
The Social ◽  
Engineering Problems ◽  
The Mean

AbstractNature inspired swarm based meta-heuristic optimization technique is getting considerable attention and established to be very competitive with evolution based and physical based algorithms. This paper proposes a novel Buyer Inspired Meta-heuristic optimization Algorithm (BIMA) inspired form the social behaviour of human being in searching and bargaining for products. In BIMA, exploration and exploitation are achieved through shop to shop hoping and bargaining for products to be purchased based on cost, quality of the product, choice and distance to the shop. Comprehensive simulations are performed on 23 standard mathematical and CEC2017 benchmark functions and 3 engineering problems. An exhaustive comparative analysis with other algorithms is done by performing 30 independent runs and comparing the mean, standard deviation as well as by performing statistical test. The results showed significant improvement in terms of optimum value, convergence speed, and is also statistically more significant in comparison to most of the reported popular algorithms.

Logistic Map and Exponential Scaling Factor based Differential Evolution

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Differential Evolution ◽  
Logistic Map ◽  
Differential Evolution Algorithm ◽  
Scaling Factor ◽  
Exploration And Exploitation ◽  
Engineering Problems ◽  
Evolutionary Technique ◽  
Evolution Algorithm ◽  
State Of Art ◽  
Modified Algorithm

Differential evolution (DE), an important evolutionary technique, enhances its parameters such as, initialization of population, mutation, crossover etc. to resolve realistic optimization issues. This work represents a modified differential evolution algorithm by using the idea of exponential scale factor and logistic map in order to address the slow convergence rate, and to keep a very good equilibrium linking exploration and exploitation. Modification is done in two ways: (i) Initialization of population and (ii) Scaling factor.The proposed algorithm is validated with the aid of a 13 different benchmark functions taking from the literature, also the outcomes are compared along with 7 different popular state of art algorithms. Further, performance of the modified algorithm is simulated on 3 realistic engineering problems. Also compared with 8 recent optimizer techniques. Again from number of function evaluations it is clear that the proposed algorithm converses more quickly than the other existing algorithms.

scholarly journals An Improved Moth-Flame Optimization Algorithm with Adaptation Mechanism to Solve Numerical and Mechanical Engineering Problems

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1637
Author(s):  
Mohammad H. Nadimi-Shahraki ◽  
Ali Fatahi ◽  
Hoda Zamani ◽  
Seyedali Mirjalili ◽  
Laith Abualigah
Keyword(s):  
Mechanical Engineering ◽  
Optimization Problems ◽  
Population Diversity ◽  
Local Optimum ◽  
Friedman Test ◽  
Exploration And Exploitation ◽  
Adaptation Mechanism ◽  
Local Optima ◽  
Engineering Problems ◽  
Moth Flame Optimization Algorithm

Moth-flame optimization (MFO) algorithm inspired by the transverse orientation of moths toward the light source is an effective approach to solve global optimization problems. However, the MFO algorithm suffers from issues such as premature convergence, low population diversity, local optima entrapment, and imbalance between exploration and exploitation. In this study, therefore, an improved moth-flame optimization (I-MFO) algorithm is proposed to cope with canonical MFO’s issues by locating trapped moths in local optimum via defining memory for each moth. The trapped moths tend to escape from the local optima by taking advantage of the adapted wandering around search (AWAS) strategy. The efficiency of the proposed I-MFO is evaluated by CEC 2018 benchmark functions and compared against other well-known metaheuristic algorithms. Moreover, the obtained results are statistically analyzed by the Friedman test on 30, 50, and 100 dimensions. Finally, the ability of the I-MFO algorithm to find the best optimal solutions for mechanical engineering problems is evaluated with three problems from the latest test-suite CEC 2020. The experimental and statistical results demonstrate that the proposed I-MFO is significantly superior to the contender algorithms and it successfully upgrades the shortcomings of the canonical MFO.

An efficient technique for extraction of nonlinear dynamic features in a model-based feature extraction scheme for machine learning–based structural health monitoring

2020 ◽  
pp. 107754632093374
Author(s):  
Mehdi Fathalizadeh Najib ◽  
Ali Salehzadeh Nobari
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Damage Identification ◽  
Element Model ◽  
Model Based ◽  
Damage Indicators ◽  
Input Model ◽  
Harmonic Components ◽  
Nonlinear Autoregressive ◽  
The Finite Element Model

Super-harmonic components in response to the harmonic excitation are sensitive indicators of damages such as breathing cracks in beams or kissing bonds in adhesive joints. In a model-based damage identification process using pattern recognition, these damage indicators can be extracted from the finite element model for all probable damage cases using stepped-sine simulation that necessitates nonlinear transient dynamic analysis with high computational costs. In this study, a procedure based on nonlinear autoregressive with exogenous input model is introduced as an alternative shortcut method for extraction of the damage indicators. As a case study, the finite element model of a beam connected to a rigid support via a flexible adhesive layer was used to investigate the efficiency of the proposed method. Kissing bond was introduced to the model as the source of nonlinearity via contact elements. The results prove that the super-harmonic components of orders up to 3, extracted from the nonlinear autoregressive with exogenous input model, agreed well with those extracted directly from the finite element model, whereas the computational time is reduced by a factor of 1/5. Consequently, the proposed method is very advantageous in the stage of damage pattern database creation in a real-world model-based damage identification process based on pattern recognition.

Structural Damage Detection Using Curvature Mode Difference Curve

2011 ◽  
Vol 250-253 ◽  
pp. 1248-1251 ◽  
Author(s):  
Hang Jing ◽  
Ling Ling Jia ◽  
Yi Zhao
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Numerical Differentiation ◽  
Engineering Structures ◽  
System Parameters ◽  
Numerical Studies ◽  
Damage Indicator ◽  
Structural Damage Identification ◽  
Changing Rate

Damage detection in civil engineering structures using the dynamic system parameters has become an important area of research. The sensitivity of damage indicator is of great value to structural damage identification. The curvature mode is an excellent parameter in damage detection of structures, while in case that certain curvature mode curve can’t show existence of damage. In this paper, numerical studies are conducted to demonstrate the deficiency of curvature mode to damage detection. Then a new damage indicator called “curvature mode changing rate” (CMCR) is introduced which is processed by numerical differentiation of curvature mode curve. The simulation results show that the new index is superior to curvature mode for structural damage identification, and it is still sensitive to the damaged location in the mode node.

Sign in / Sign up

Export Citation Format

Share Document