scholarly journals 3D crack identification using the Nelder-Mead Simplex algorithm combined with a random generation of crack positions

2021 ◽  
Vol 16 (59) ◽  
pp. 243-255
Author(s):  
Nasreddine Amoura ◽  
Hocine Kebir ◽  
Abdelouahab Benzerdjeb
Keyword(s):  
Crack Detection ◽  
Three Dimensional ◽  
Stable Solution ◽  
Optimization Procedure ◽  
Simplex Algorithm ◽  
Measurement Noise ◽  
Crack Identification ◽  
Geometrical Parameters ◽  
Linear Elastic ◽  
The Difference

In this paper, we present a scheme for cracks identification in three-dimensional linear elastic mechanical components. The scheme uses a boundary element method for solving the forward problem and the Nelder-Mead simplex numerical optimization algorithm coupled with a low discrepancy sequence in order to identify an embedded crack. The crack detection process is achieved through minimizing an objective function defined as the difference between measured strains and computed ones, at some specific sensors on the domain boundaries. Through the optimization procedure, the crack surface is modelled by geometrical parameters, which serve as identity variables. Numerical simulations are conducted to determine the identity parameters of an embedded elliptical crack, with measures randomly perturbed and the residual norm regularized in order to provide an efficient and numerically stable solution to measurement noise. The accuracy of this method is investigated in the identification of cracks over two examples. Through the treated examples, we showed that the method exhibits good stability with respect to measurement noise and convergent results could be achieved without restrictions on the selected initial values of the crack parameters.

Experimental study of kriging-based crack identification in plate structure

2016 ◽  
Vol 231 (17) ◽  
pp. 3118-3129 ◽  
Author(s):  
Haiyang Gao ◽  
Xiaofei Hu ◽  
Fang Han ◽  
Xinming Li ◽  
Jungang Zhang
Keyword(s):  
Surrogate Model ◽  
Crack Detection ◽  
Model Updating ◽  
Computational Cost ◽  
Measurement Noise ◽  
Dynamic Responses ◽  
Detection Methods ◽  
Crack Identification ◽  
Kriging Surrogate Model ◽  
Plate Structure

One of the major issues that existing crack identification methods utilizing dynamic responses are facing is the limitation of engineering feasibility. How to suppress the effect of measurement noise and improve the identification accuracy is still challenging. In this work, an effective method is proposed to identify the size of an arbitrary internal crack in plate structure based on a Kriging surrogate model, and a series of laboratory tests are designed to verify the practicability of this strategy. The initial Kriging surrogate model is constructed by samples of crack parameters (tip locations) and corresponding root mean square (RMS) of random responses as the inputs and outputs, respectively. To further improve the surrogate accuracy and reduce computational cost during the inverse problem, an optimal point-adding process for Kriging model updating is then carried out. Experimental results of crack identification in a cantilever plate indicate that the proposed method can be an alternative to conventional crack detection methods even in the presence of measurement noise and modeling errors.

scholarly journals Vision Measurement of Tunnel Structures with Robust Modelling and Deep Learning Algorithms

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4945 ◽  
Author(s):  
Xiangyang Xu ◽  
Hao Yang
Keyword(s):  
Deep Learning ◽  
Health Monitoring ◽  
Crack Detection ◽  
Three Dimensional ◽  
Image Data ◽  
Measurement Unit ◽  
Crack Identification ◽  
Monitoring Method ◽  
Vision Measurement ◽  
Robust Modelling

The health monitoring of tunnel structures is vital to the safe operation of railway transportation systems. With the increasing mileage of tunnels, regular inspection and health monitoring are urgently demanded for the tunnel structures, especially for information regarding deformation and damage. However, traditional methods of tunnel inspection are time-consuming, expensive and highly dependent on human subjectivity. In this paper, an automatic tunnel monitoring method is investigated based on image data which is collected through the moving vision measurement unit consisting of camera array. Furthermore, geometric modelling and crack inspection algorithms are proposed where a robust three-dimensional tunnel model is reconstructed utilizing a B-spline method and crack identification is conducted by means of a Mask R-CNN network. The innovation of this investigation is that we combine the robust modelling which could be applied for the deformation analysis and the crack detection where a deep learning method is employed to recognize the tunnel cracks intelligently based on image sensors. In this study, experiments were conducted on a subway tunnel structure several kilometers long, and a robust three-dimensional model is generated and the cracks are identified automatically with the image data. The superiority of this proposal is that the comprehensive information of geometry deformation and crack damage can ensure the reliability and improve the accuracy of health monitoring.

Vibration-based breathing crack identification using non-linear intermodulation components under noisy environment

2019 ◽  
Vol 19 (1) ◽  
pp. 86-104 ◽  
Author(s):  
J Prawin ◽  
A Rama Mohan Rao
Keyword(s):  
Spectral Analysis ◽  
Crack Detection ◽  
Damage Index ◽  
Measurement Noise ◽  
Experimental Simulation ◽  
Crack Identification ◽  
Diagnostic Process ◽  
Breathing Crack ◽  
Spectral Correlation ◽  
Non Linear

Structural damages can result in non-linear dynamical signatures such as lower and higher order harmonics and signal modulation that can significantly enhance their detection. The conventional spectral analysis is used in most existing vibration-based damage diagnostic techniques to extract these damage-sensitive non-linear features. However, the major limitation of using spectral analysis is that the amplitudes of non-linear harmonics are highly sensitive to measurement noise and may mislead the damage diagnostic process. Keeping this in view, we present a new reference-free damage diagnostic technique for fatigue-breathing crack detection, localization and characterization using the cyclic spectral analysis-based technique. A new damage index based on spectral correlation exploiting the non-linear intermodulation in the response is proposed. The proposed cyclic spectral analysis-based diagnostics are highly immune to the measurement noise. Numerical and experimental simulation studies have been carried out by considering a beam with single and multiple breathing cracks, to test and verify the robustness and effectiveness of the proposed technique.

3D Modeling of Fracture Initiation From Perforated Noncemented Wellbore

SPE Journal ◽  
2013 ◽  
Vol 18 (03) ◽  
pp. 589-600 ◽  
Author(s):  
O.P.. P. Alekseenko ◽  
D.I.. I. Potapenko ◽  
S.G.. G. Cherny ◽  
D.V.. V. Esipov ◽  
D.S.. S. Kuranakov ◽  
...  
Keyword(s):  
Fracture Initiation ◽  
In Situ Stress ◽  
Current Treatment ◽  
Fracture Plane ◽  
Geometrical Parameters ◽  
Practical Applications ◽  
Linear Elastic ◽  
Initial Rupture ◽  
The Difference ◽  
Elastic Rock

Summary A 3D numerical model of fracture initiation from a perforated wellbore in linear elastic rock is developed, which allows one to determine the fracture-initiation pressure (FIP) and the location and direction of an initial rupture. The model assumes that the fracture initiates at the point at which the local maximal tensile stress exceeds the rock tensile strength. The 3D boundary-element method (BEM) is used for stress analysis. The model aims to predict the location of initial fractures and the difference in FIP between different perforation intervals in arbitrarily oriented noncemented wellbores. There are many practical applications for this knowledge, but of particular interest for this research is the employment of differently oriented perforations for creating heterogeneity of FIP between wellbore intervals in multistage fracturing treatment. This can enable stimulation of these intervals in a sequential mode and significantly simplify current treatment diversion and completion practices. Comprehensive analysis revealed that the main parameter that can be used for controlling FIP during multistage fracturing treatment is the angle between the direction of the perforation channel and the preferred fracture plane (PFP). The model allows obtaining the range of the angles that is the most suitable for designing and implementation of diversion between the perforated wellbore intervals. The influence of geometrical parameters of perforation (such as length, diameter, and shape) on FIP is substantially less. In addition, we found that against all expectations, increase of perforation diameter can result in higher FIP. It was also discovered that the influence of the intermediate in-situ stress on FIP is comparable with the effect of perforation misalignment, especially in the situation of a horizontal wellbore and properly aligned perforations. On the basis of the model developed, an approximate approach to the evaluation of the effect of wellbore cementation on fracture initiation was suggested. It was discovered that taking into account the state of stress within the cement before well pressurization can result in both an increase and a reduction of FIP, depending on the parameters of perforating and the wellbore orientation. The presented model is a necessary step toward predictable and controllable fracture initiation, which is vital for multistage-fracturing-treatment diversion.

scholarly journals A New Methodology to Establish Upper Bounds on Open-Cell Foams Homogenized Properties

10.14311/652 ◽  
2004 ◽  
Vol 44 (5-6) ◽  
Author(s):  
Z. Dimitrovová
Keyword(s):  
Three Dimensional ◽  
Sufficient Conditions ◽  
Upper Bounds ◽  
Geometrical Parameters ◽  
Open Cell ◽  
Linear Elastic ◽  
Internal Forces ◽  
Open Cell Foams ◽  
Necessary And Sufficient ◽  
First Time

The methodology for determining the upper bounds on the homogenized linear elastic properties of cellular solids, described for the two-dimensional case in Dimitrovová and Faria (1999), is extended to three-dimensional open-cell foams. Besides the upper bounds, the methodology provides necessary and sufficient conditions on optimal media. These conditions are written in terms of generalized internal forces and geometrical parameters. In some cases dependence on internal forces can be replaced by geometrical expressions. In such cases, the optimality of some medium under consideration can be verified directly from the microstructure, without any additional calculation. Some of the bounds derived in this paper are published for the first time, along with a proof of their optimality. 

Defocus ramp correction in spot-scan imaging

1992 ◽  
Vol 50 (1) ◽  
pp. 130-131
Author(s):  
Kenneth H. Downing
Keyword(s):  
Computer Control ◽  
Three Dimensional ◽  
Sufficient Accuracy ◽  
Objective Lens ◽  
Electron Crystallography ◽  
Contrast Transfer Function ◽  
Tilt Axis ◽  
Specimen Height ◽  
The Difference ◽  
Envelope Functions

Three-dimensional structures of a number of samples have been determined by electron crystallography. The procedures used in this work include recording images of fairly large areas of a specimen at high tilt angles. There is then a large defocus ramp across the image, and parts of the image are far out of focus. In the regions where the defocus is large, the contrast transfer function (CTF) varies rapidly across the image, especially at high resolution. Not only is the CTF then difficult to determine with sufficient accuracy to correct properly, but the image contrast is reduced by envelope functions which tend toward a low value at high defocus.We have combined computer control of the electron microscope with spot-scan imaging in order to eliminate most of the defocus ramp and its effects in the images of tilted specimens. In recording the spot-scan image, the beam is scanned along rows that are parallel to the tilt axis, so that along each row of spots the focus is constant. Between scan rows, the objective lens current is changed to correct for the difference in specimen height from one scan to the next.

Three-Dimensional Ultrasonic Crack Detection in Anisotropic Materials

1997 ◽  
Vol 9 (2) ◽  
pp. 59-79 ◽  
Author(s):  
J. Mattsson ◽  
A. J. Niklasson ◽  
A. Eriksson
Keyword(s):  
Crack Detection ◽  
Three Dimensional ◽  
Anisotropic Materials

The iron content of iron superoxide dismutase: determination by anomalous scattering

1983 ◽  
Vol 218 (1210) ◽  
pp. 119-126 ◽  
Keyword(s):  
Superoxide Dismutase ◽  
Iron Content ◽  
Three Dimensional ◽  
Anomalous Scattering ◽  
Total Iron Content ◽  
Iron Site ◽  
Iron Superoxide Dismutase ◽  
Density Map ◽  
The Difference ◽  
Electron Density Map

The number of iron atoms in the dimeric iron-containing superoxide dismutase from Pseudomonas ovalis and their atomic positions have been determined directly from anomalous scattering measurements on crystals of the native enzyme. To resolve the long-standing question of the total amount of iron per molecule for this class of dismutase, the occupancy of each site was refined against the measured Bijvoet differences. The enzyme is a symmetrical dimer with one iron site in each subunit. The iron position is 9 ņ from the intersubunit interface. The total iron content of the dimer is 1.2±0.2 moles per mole of protein. This is divided between the subunits in the ratio 0.65:0.55; the difference between them is probably not significant. Since each subunit contains, on average, slightly more than half an iron atom we conclude that the normal state of this enzyme is two iron atoms per dimer but that some of the metal is lost during purification of the protein. Although the crystals are obviously a mixture of holo- and apo-enzymes, the 2.9 Å electron density map is uniformly clean, even at the iron site. We conclude that the three-dimensional structures of the iron-bound enzyme and the apoenzyme are identical.

scholarly journals SVM-Based Bearing Anomaly Identification with Self-Tuning Network-Fuzzy Robust Proportional Multi Integral and Smart Autoregressive Model

2021 ◽  
Vol 11 (6) ◽  
pp. 2784
Author(s):  
Shahnaz TayebiHaghighi ◽  
Insoo Koo
Keyword(s):  
Machine Learning ◽  
Variable Structure ◽  
Rolling Element Bearing ◽  
Crack Identification ◽  
Original Signal ◽  
Signal Modeling ◽  
Residual Signal ◽  
Average Accuracy ◽  
Self Tuning ◽  
The Difference

In this paper, the combination of an indirect self-tuning observer, smart signal modeling, and machine learning-based classification is proposed for rolling element bearing (REB) anomaly identification. The proposed scheme has three main stages. In the first stage, the original signal is resampled, and the root mean square (RMS) signal is extracted from it. In the second stage, the normal resampled RMS signal is approximated using the AutoRegressive with eXternal Uncertainty (ARXU) technique. Moreover, the nonlinearity of the bearing signal is solved using the combination of the ARXU and the machine learning-based regression, which is called AMRXU. After signal modeling by AMRXU, the RMS resampled signal is estimated using a combination of the proportional multi-integral (PMI) technique, the variable structure (VS) Lyapunov technique, and a self-tuning network-fuzzy system (SNFS). Finally, in the third stage, the difference between the original signal and the estimated one is calculated to generate the residual signal. A machine learning-based classification technique is utilized to classify the residual signal. The Case Western Reserve University (CWRU) dataset is used to evaluate anomaly identification performance of the proposed scheme. Regarding the experimental results, the average accuracy for REB crack identification is 98.65%, 97.7%, 97.35%, and 97.67%, respectively, when the motor torque loads are 0-hp, 1-hp, 2-hp, and 3-hp.

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