Dynamic response and analysis of cracked beam subjected to transit mass

Jena, Shakti P.; Parhi, Dayal R.

doi:10.1007/s40435-017-0361-3

Cited by 14 publications

(7 citation statements)

References 31 publications

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“…The natures of the cracks on the structure are open and transverse and the detailed analysis of cracks are already analyzed by Jena and Parhi [11]. The cracks are open and transverse in nature, the load is assumed to be acting on the transverse direction only.…”

Section: Numerical Formulationsmentioning

confidence: 99%

“…Hakim et al [7] have developed a damage identification procedure in the domain ANNs by taking into account an I-beam structure. Jena et al [8][9][10][11] have carried out numerous studies like theoretical, FEA and experimental to determine the responses of different types of structures subjected to transit mass. They have determined the structure's response at various damage and moving load parameters.…”

Section: Introductionmentioning

confidence: 99%

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On the way to fault detection method in moving load dynamics problem by modified recurrent neural networks approach

Jena¹,

Parhi

2021

Mechanics & Industry

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Parameters identification on structure subjected to moving load can be predicted by using the accurate and reliable data. The concepts of recurrent neural networks (RNNs) approach have been used in parameters (crack locations and severities) identifications in structure subjected to moving load in the present methodology. This methodology has incorporated the knowledge based Elman's recurrent neural networks (ERNNs) and Jordan's recurrent neural networks (JRNNs) jointly for the identification of parameters. This approach has been addressed as the inverse problem for predicting the locations and quantification of cracks in the structure in a supervised manner. The Levenberg-Marquardt's back propagation algorithm is implemented to train the proposed networks. To check the robustness of the present method, Numerical studies followed by Finite Element Analysis (FEA) and experimental verifications (Forward problems) are presented as a case study by considering a multi-cracked simply supported structure under a moving mass. The estimated crack locations and severities obtained from the proposed RNNs model converge well with those of FEA and experiments. From the demonstration of the case study, it concludes that the proposed analogy can identify and quantify the crack locations and severities effectively.

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Section: Numerical Formulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the way to fault detection method in moving load dynamics problem by modified recurrent neural networks approach

Jena¹,

Parhi

2021

Mechanics & Industry

Self Cite

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“…Suitable mathematical expressions can be coined together to formulate rule based techniques [58][59] to address robot path planning problems and other engineering problems. Papers [60][61][62][63][64][65][66] discuss about various vibration patterns in dynamic robotic structures with the help of smart intelligent techniques. Paper [67] discusses analysis of robot manipulator used for various tasks.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Design of Automated Transport and Path Planning for Robots in Cluttered Environments using Novel Hybrid Average Genetic-Neural Control Technique

2021

CERJ

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In the current investigation on automated transport and navigational path planning of robots, a new Hybrid Average Genetic-Neural (HAGN) technique has been developed. The HAGN technique uses genetic algorithm and multi layered neural technique as important parts for its development. The robots are equipped with several sensors to map the surrounding environments and to recognize the obstacles and targets around. During the navigation robots take into account front, left and right obstacle distances obtained from sensors to negotiate with obstacles and reach targets with the help of HAGN technique. To prove authenticity of the proposed method several simulation and experimental exercises have been carried out. Comparisons between simulation and experimental results are presented in pictorial and tabular forms. The deviation between simulation and experimental results are found to be within 2.8%. Other engineering applications can also be addressed using HAGN AI technique.

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“…Scientists and engineers have used various methods to analyse crack identification [104][105][106][107][108][109][110][111] in vibrating structures. Papers [112][113][114][115][116][117][118][119][120][121][122][123][124][125] discuss about novel neural network and fuzzy logic to address problem of crack identification in complicated dynamic structures. Papers [126][127][128][129] discuss about hybrid AI techniques for robot control.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Review of Average Fuzzy Inference Technique and Other AI Techniques Used for Robot Control and Navigation

R¹,

Chidananda

2020

CTCSA

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In this paper application of average fuzzy inference technique has been analysed for navigation control of robotic agent. Also, the reviews of other AI techniques for control of robots are carried out. The robotic agent uses sensors to map the surroundings and take the decision with the help of Fuzzy AI technique to avoid obstacles. In this paper a novel averaging method has been deployed to optimize the results obtained from various fuzzy membership functions. Using the Average Fuzzy Inference technique robot navigates from start position to goal position avoiding obstacles while reaching the target. The simulation results agree with experimental results. The methodology can be used for various applications by the scientific communities to address various engineering problems.

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Dynamic response and analysis of cracked beam subjected to transit mass

Cited by 14 publications

References 31 publications

On the way to fault detection method in moving load dynamics problem by modified recurrent neural networks approach

On the way to fault detection method in moving load dynamics problem by modified recurrent neural networks approach

Analysis and Design of Automated Transport and Path Planning for Robots in Cluttered Environments using Novel Hybrid Average Genetic-Neural Control Technique

Analysis and Review of Average Fuzzy Inference Technique and Other AI Techniques Used for Robot Control and Navigation

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