scholarly journals Damage Identification Algorithm of Hinged Joints for Simply Supported Slab Bridges Based on Modified Hinge Plate Method and Artificial Bee Colony Algorithms

Algorithms ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 198 ◽  
Author(s):  
Hanbing Liu ◽  
Xin He ◽  
Yubo Jiao
Keyword(s):  
Artificial Bee Colony ◽  
Damage Identification ◽  
Joint Damage ◽  
Identification Accuracy ◽  
Identification Algorithm ◽  
Plate Method ◽  
Simply Supported ◽  
Hinge Joint ◽  
Bee Colony ◽  
Hinge Plate

Hinge joint damage is a typical form of damage occurring in simply supported slab bridges, which can present adverse effects on the overall force distribution of the structure. However, damage identification methods of hinge joint damage are still limited. In this study, a damage identification algorithm for simply supported hinged-slab bridges based on the modified hinge plate method (MHPM) and artificial bee colony (ABC) algorithms was proposed by considering the effect of hinge damage conditions on the lateral load distribution (LLD) of structures. Firstly, MHPM was proposed and demonstrated, which is based on a traditional hinge plate method by introducing relative displacement as a damage factor to simulate hinge joint damage. The effectiveness of MHPM was verified through comparison with the finite element method (FEM). Secondly, damage identification was treated as the inverse problem of calculating the LLD in damage conditions of simply supported slab bridges. Four ABC algorithms were chosen to solve the problem due to its simple structure, ease of implementation, and robustness. Comparisons of convergence speed and identification accuracy with genetic algorithm and particle swarm optimization were also conducted. Finally, hinged bridges composed of four and seven slabs were studied as numerical examples to account for the feasibility and correctness of the proposed method. The simulation results revealed that the proposed algorithm could identify the location and degree of damaged joints efficiently and precisely.

A multivariate adaptive regression splines based damage identification methodology for web core composite bridges including the effect of noise

2017 ◽  
Vol 20 (7) ◽  
pp. 885-903 ◽  
Author(s):  
Tanmoy Mukhopadhyay
Keyword(s):  
Optimization Algorithm ◽  
Damage Identification ◽  
Multivariate Adaptive Regression Splines ◽  
Identification Accuracy ◽  
Identification Algorithm ◽  
Regression Splines ◽  
Multi Objective ◽  
Composite Bridges ◽  
Adaptive Regression ◽  
Adaptive Regression Splines

A novel computationally efficient damage identification methodology for web core fiber-reinforced polymer composite bridges has been developed in this article based on multivariate adaptive regression splines in conjunction with a multi-objective goal-attainment optimization algorithm. The proposed damage identification methodology has been validated for several single and multiple damage cases. The performance of the efficient multivariate adaptive regression splines-based approach for the inverse system identification process is found to be quite satisfactory. An iterative scheme in conjunction with the multi-objective optimization algorithm coupled with multivariate adaptive regression splines is proposed to increase damage identification accuracy. The effect of noise on the proposed damage identification algorithm has also been addressed subsequently using a probabilistic framework. The multivariate adaptive regression splines-based damage identification algorithm is general in nature; therefore, in future it can be implemented to other structures.

Damage Identification Method of Simply Supported Beam Bridge with Multiple Girders

2013 ◽  
Vol 437 ◽  
pp. 377-381
Author(s):  
Ping Yi Sun ◽  
Yan Hua Wang ◽  
Yan Feng Niu ◽  
Han Bing Liu ◽  
Guo Jin Tan
Keyword(s):  
Numerical Simulation ◽  
Damage Identification ◽  
Identification Algorithm ◽  
Damage State ◽  
Simply Supported Beam ◽  
Simply Supported ◽  
Svm Algorithm ◽  
Damage Extent ◽  
Beam Bridge ◽  
T Beam

Considering the complexity of the simply supported beam with multiple girders, a two-step damage identification algorithm for this kind of bridge is presented. This algorithm first locates the damage by means of curvature of flexibility change, and then utilizes the PSO-SVM algorithm to identify the damage extent. At last, a numerical simulation calculation is conducted to identify the damage state of a simply supported T-beam bridge with five girders. The numerical simulation results show that the algorithm proposed is valid, reliable and with high recognition precision.

PERFORMANCE EVALUATION OF CULTURAL ARTIFICIAL BEE COLONY AND CULTURAL ARTIFICIAL FISH SWARM ALGORITHM

2019 ◽  
Vol 6 (4) ◽  
pp. 43
Author(s):  
HADIR ADEBIYI BUSAYO ◽  
TIJANI SALAWUDEEN AHMED ◽  
FOLASHADE O. ADEBIYI RISIKAT ◽  
◽  
◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Artificial Bee Colony ◽  
Artificial Fish Swarm Algorithm ◽  
Bee Colony ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm

Path Planning of Mobile Robot Using Improved Artificial Bee Colony Algorithm

2020 ◽  
Vol 38 (9A) ◽  
pp. 1384-1395
Author(s):  
Rakaa T. Kamil ◽  
Mohamed J. Mohamed ◽  
Bashra K. Oleiwi
Keyword(s):  
Mobile Robot ◽  
Comparative Research ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Dynamic Control ◽  
Computational Time ◽  
Bee Colony ◽  
Shortest Distance ◽  
Minimum Number ◽  
Cubic Polynomial

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

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