Evaluation of the health of riveted joints with active and passive structural health monitoring techniques

Demetgül, Mustafa; Senyurek, Volkan; Uyandik, R.; Tansel, İbrahim N.; Yazıcıoğlu, Osman

doi:10.1016/j.measurement.2015.03.032

Cited by 31 publications

(18 citation statements)

References 41 publications

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“…Artificial neural networks, are the computer systems developed with the aim of accomplishing some abilities such as acquiring, creating and exploring new information, which are some of the characteristics of the human brain, automatically, through learning and without getting any help [9].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…Twenty training approaches have been carried out, using two transfer functions such as hyperbolic tangent sigmoid (tansig) and logarithmic sigmoid (logsig) and ten different neuron numbers (4,5,6,7,8,9,10,15,20,25) in the hidden layer, to determine the structure by which the best results could be obtained. Max-epoch value of 300 has been selected in training and the best prediction value of the optimum experiment result has been reached using the tansig function with eight neurons in the hidden layer.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

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The Prediction and Optimization of the Effects of Abrasive Waterjet Cutting Parameters On Kerf

2016

Acta Phys. Pol. A

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In this study, Inconel 718 material, which is widely used in space aircraft and defense industry and is difficult to be processed by traditional methods, has been cut off with abrasive water-jet. The effects of cutting parameters such as pressure, cutting speed, abrasive consumption and cutting height on kerf have been studied. The input levels needed to be used to obtain the minimum kerf have been determined through Taguchi analysis and the experimental test. The setup of experiment was modelled using linear regression model and an artificial neural network and the results were compared. It was seen that the artificial neural network model gives better results when compared to regression model. The results of experimental test to which the related models were applied are satisfactory.

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Section: Artificial Neural Networkmentioning

confidence: 99%

Section: Artificial Neural Networkmentioning

confidence: 99%

The Prediction and Optimization of the Effects of Abrasive Waterjet Cutting Parameters On Kerf

2016

Acta Phys. Pol. A

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“…In recent years, numerous signal processing strategies (SPS) that analyze vibrations to perform damage detection in civil structures have been proposed, among which the Fast Fourier transform (FFT) and its variants known as frequency response function (FRF) [18][19][20][21][22], multiple signal classification (MUSIC) [3,[23][24][25], Wigner-Ville distribution (WVD) [26,27], and statistical time series models (STSM) [4,[28][29][30][31][32] are the most employed. Nevertheless, although good results have been reported using the aforementioned techniques, they present significant limitations.…”

Section: Introductionmentioning

confidence: 99%

EMD-Shannon Entropy-Based Methodology to Detect Incipient Damages in a Truss Structure

et al. 2018

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Truss-type designs are widely used in civil structures. Despite the fact that they are robust and reliable structures, different kinds of damage can appear. In order to avoid human and economic losses, the development and application of damage-detection methodologies are paramount. In this work, a methodology based on the empirical mode decomposition (EMD) method and the Shannon Entropy Index (SEI) to detect incipient damages associated with corrosion in a 3D 9-bay truss-type bridge is presented. As different EMD methods are presented in literature, the most representative methods are investigated in order to evaluate their performance for this task. To this end, the vibration signals generated in the truss-type bridge at different conditions are analyzed. For the damage condition, four severity levels of simulated corrosion (1 mm, 3 mm, 5 mm, and 8 mm of diameter reduction) generated into the elements of truss-type bridge are considered. Results demonstrate the effectiveness of the proposal in terms of detecting corrosion in its very early stage (1 mm of reduction in the element).

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“…Actuators are used for controlled and systematic excitation of structures and sensors collect the response of a target structure to a known excitation. Instead, methods that do not utilize actuators and only use sensors for detection of defects are called passive methods [28], [29]. In linear active methods, the input to the system is known and the main focus is on the interpretation of the response.…”

Section: Research Goals Scope and Objectivesmentioning

confidence: 99%

Detecting Structural Defects Using Novel Smart Sensory and Sensor-less Approaches

Baghalian¹

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Evaluation of the health of riveted joints with active and passive structural health monitoring techniques

Cited by 31 publications

References 41 publications

The Prediction and Optimization of the Effects of Abrasive Waterjet Cutting Parameters On Kerf

The Prediction and Optimization of the Effects of Abrasive Waterjet Cutting Parameters On Kerf

EMD-Shannon Entropy-Based Methodology to Detect Incipient Damages in a Truss Structure

Detecting Structural Defects Using Novel Smart Sensory and Sensor-less Approaches

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