Characterization and Localization of Sub-Surface Structural Features Using Non-Contact Tomography

2016 ◽  
Author(s):  
Sumit Gupta ◽  
Kenneth J. Loh
Keyword(s):  
Damage Detection ◽  
Composite Structures ◽  
Electrical Response ◽  
Surface Damage ◽  
Structural Features ◽  
Electrical Signal ◽  
Rotor Blades ◽  
Function Generator ◽  
Manufacturing Defects ◽  
Electrical Permittivity

The main objective of this work is to develop a non-contact, non-invasive, structural health monitoring technique for surface and sub-surface damage detection in structures such as composite helicopter rotor blades. In many cases, composite structures are prone to damage in the form of cracks, delamination, and manufacturing defects, which can propagate beneath structural surfaces and cause severe component or catastrophic structural failure. The damage detection technique in this study works on the principle of electrical capacitance tomography. Different patterns of electrical field are propagated in a pre-defined sensing area. Using measurements of electrical response along boundaries of the sensing area, the permittivity distribution within that space can be reconstructed. First, a series of numerical simulations was performed by altering the electrical permittivity at different locations to simulate damage. The shapes and locations of permittivity changes were captured by the proposed technique. Second, to demonstrate its validity, an experimental test setup was built with a set of boundary electrodes. The system was connected to a function generator that supplied an electrical signal and induced electrical fields between electrodes. Capacitance between pairs of electrodes were then measured, which were used as inputs for solving the inverse permittivity reconstruction problem. Various test cases with different objects placed in the sensing area were conducted for validating this technique. The preliminary results show that the system was able to reconstruct spatial permittivity distributions and detect the presence, shapes, and locations of objects, thereby suggesting potential for damage detection.

scholarly journals Computer Vision-Based Bridge Damage Detection Using Deep Convolutional Networks with Expectation Maximum Attention Module

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 824
Author(s):  
Wenting Qiao ◽  
Biao Ma ◽  
Qiangwei Liu ◽  
Xiaoguang Wu ◽  
Gang Li
Keyword(s):  
Damage Detection ◽  
Complex Structure ◽  
Surface Damage ◽  
Break Point ◽  
Convolutional Networks ◽  
Concrete Crack ◽  
Current State ◽  
Bridge Damage ◽  
Bridge Inspections ◽  
Impact Problems

Cracks and exposed steel bars are the main factors that affect the service life of bridges. It is necessary to detect the surface damage during regular bridge inspections. Due to the complex structure of bridges, automatically detecting bridge damage is a challenging task. In the field of crack classification and segmentation, convolutional neural networks have offer advantages, but ordinary networks cannot completely solve the environmental impact problems in reality. To further overcome these problems, in this paper a new algorithm to detect surface damage called EMA-DenseNet is proposed. The main contribution of this article is to redesign the structure of the densely connected convolutional networks (DenseNet) and add the expected maximum attention (EMA) module after the last pooling layer. The EMA module is obviously helpful to the bridge damage feature extraction. Besides, we use a new loss function which considers the connectivity of pixels, it has been proved to be effective in reducing the break point of fracture prediction and improving the accuracy. To train and test the model, we captured many images from multiple bridges located in Zhejiang (China), and then built a dataset of bridge damage images. First, experiments were carried out on an open concrete crack dataset. The mean pixel accuracy (MPA), mean intersection over union (MIoU), precision and frames per second (FPS) of the EMA-DenseNet are 87.42%, 92.59%, 81.97% and 25.4, respectively. Then we also conducted experiments on a more challenging bridge damage dataset, the MIoU, where MPA, precision and FPS were 79.87%, 86.35%, 74.70% and 14.6, respectively. Compared with the current state-of-the-art algorithms, the proposed algorithm is more accurate and robust in bridge damage detection.

Damage detection in composite structures using Lamb wave analysis and time-frequency approach

2011 ◽  
Author(s):  
Yingtao Liu ◽  
Masoud Yekani Fard ◽  
Seung B. Kim ◽  
Aditi Chattopadhyay ◽  
Derek Doyle
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Composite Structures ◽  
Wave Analysis ◽  
Time Frequency

Feasibility of PZT ceramics for impact damage detection in composite structures

2015 ◽  
Author(s):  
Gerges Dib ◽  
Ermias Koricho ◽  
Oleksii Karpenko ◽  
Mahmood Haq ◽  
Lalita Udpa ◽  
...  
Keyword(s):  
Damage Detection ◽  
Composite Structures ◽  
Impact Damage ◽  
Pzt Ceramics

scholarly journals Numerical Simulation on Micro-damage Detection In CFRP Composites Based on Nonlinear Ultrasonic Guided Waves

2021 ◽  
Keyword(s):  
Damage Detection ◽  
Composite Structures ◽  
Guided Waves ◽  
Second Harmonic ◽  
Wave Mode ◽  
Guided Wave ◽  
Reinforced Plastics ◽  
Matrix Cracks ◽  
Nonlinear Ultrasonic ◽  
Contact Acoustic Nonlinearity

Abstract. Micro-damages such as pores, closed delamination/debonding and fiber/matrix cracks in carbon fiber reinforced plastics (CFRP) are vital factors towards the performance of composite structures, which could collapse if defects are not detected in advance. Nonlinear ultrasonic technologies, especially ones involving guided waves, have drawn increasing attention for their better sensitivity to early damages than linear acoustic ones. The combination of nonlinear acoustics and guided waves technique can promisingly provide considerable accuracy and efficiency for damage assessment and materials characterization. Herein, numerical simulations in terms of finite element method are conducted to investigate the feasibility of micro-damage detection in multi-layered CFRP plates using the second harmonic generation (SHG) of asymmetric Lamb guided wave mode. Contact acoustic nonlinearity (CAN) is introduced into the constitutive model of micro-damages in composites, which leads to the distinct SHG compared with material nonlinearity. The results suggest that the generated second order harmonics due to CAN could be received and adopted for early damage evaluation without matching the phase of the primary waves.

Robust Autonomous Damage Detection and Assessment in Polymeric Composite Structures

2008 ◽  
Author(s):  
Ajay Kesavan ◽  
Sabu John ◽  
Henry Li ◽  
Israel Herszberg
Keyword(s):  
Damage Detection ◽  
Composite Structures ◽  
Research Study ◽  
Polymeric Composite ◽  
Variable Loading ◽  
Damage Scenarios ◽  
Damage Location ◽  
Joint Structure ◽  
Analytical Work ◽  
Load Angle

This paper introduces the some of the experimental and analytical work behind the autonomous damage detection technique. The research study conducted here resulted in the development of a Structural Health Monitoring (SHM) system for a 2-D polymeric composite T-joint, used in maritime structures. Two methods of damage detection are discussed — A statistics-based outlier technique and one using Artificial Neural Networks (ANNs). The SHM using ANNs system was found to be capable of not only detecting the presence of multiple delaminations in a composite structure, but also capable of determining the location and extent of all the delaminations present in the T-joint structure, regardless of the load (angle and magnitude) acting on the structure. The system developed relies on the examination of the strain distribution of the structure under operational loading. Finally, on testing the SHM system developed with strain signatures of composite T-joint structures, subjected to variable loading, embedded with all possible damage configurations (including multiple damage scenarios), an overall damage (location & extent) prediction accuracy of 94.1% was achieved. These results are presented and discussed in detail in this paper.

scholarly journals A transmittance-based methodology for damage detection under uncertainty: An application to a set of composite beams with manufacturing variability subject to impact damage and varying operating conditions

2018 ◽  
Vol 18 (1) ◽  
pp. 318-333 ◽  
Author(s):  
Aggelos G Poulimenos ◽  
John S Sakellariou
Keyword(s):  
Damage Detection ◽  
Production Line ◽  
Composite Structures ◽  
Impact Damage ◽  
Parametric Representation ◽  
Composite Beams ◽  
Operating Conditions ◽  
Ratio Test ◽  
Detection Characteristic ◽  
Testing Procedures

Oftentimes, the complexity in manufacturing composite materials leads to corresponding structures which although they may have the same design specifications they are not identical. Thus, composite parts manufactured in the same production line present differences in their dynamics which combined with additional uncertainties due to different operating conditions may lead to the complete concealment of effects caused by small, incipient, damages making their detection highly challenging. This damage detection problem in nominally identical composite structures is pursued in this study through a novel data-based response-only methodology that is founded on the autoregressive with exogenous (ARX) excitation parametric representation of the transmittance function between vibration measurements at two different locations on the structure. This is a statistical time series methodology within which two schemes are formulated. In the first, a single-reference transmittance model representing the healthy structure is employed, while multiple transmittance models from a sample of available healthy structures are used in the second. The model residual signal constitutes for both schemes the damage detection characteristic quantity that is used in appropriate hypothesis testing procedures with the likelihood ratio test. The methodology is experimentally assessed via damage detection for a population of composite beams which are manufactured in the same production line representing the half of the tail of a twin-boom unmanned aerial vehicle. The damage detection results demonstrate the superiority of the multiple transmittance models based scheme that may effectively detect damages under significant manufacturing variability and varying boundary conditions.

RESIDUAL PLASTIC STRAIN STATE AND DELAMINATION PATTERN OF COMPOSITE LAMINATES WITH AUTOMATED INDUCED-GAP SUBJECTED TO HEMI-SPHERICAL IMPACT LOADING

2021 ◽  
Author(s):  
MOHAMMADHOSSEIN GHAYOUR ◽  
MEHDI HOJJATI ◽  
RAJAMOHAN GANESAN
Keyword(s):  
Plastic Strain ◽  
Impact Loading ◽  
Residual Strain ◽  
Composite Structures ◽  
Strain State ◽  
Composite Plates ◽  
Structural Level ◽  
Manufacturing Defects ◽  
Initiation And Propagation ◽  
The Impact

Automated manufacturing defects are types of composite structure defects that occur during fiber deposition by advanced robots. The induced gap is the most probable type of defect in the Automated Fiber Placement (AFP) technique. This defect can affect the mechanical performance of the composite structures at both material level by inducing the material inhomogeneity and the structural level by introducing the consolidation effect in the structure during the curing process. The current study investigates the effect of induced-gaps on the damage assessment of thin composite plates under Low-Velocity Impact (LVI) loading. The paper focuses on the delamination initiation and propagation and the residual plastic strain state of the impacted plates. The primary application of this study is to understand the interaction of induced gaps on the delamination pattern of composite samples subjected to LVI. For this purpose, a series of LVI tests are performed. Ultrasonic C-scan analysis and microscopic observation are implied to evaluate the internal damage due to impact loading. Finite Element (FE) analyses are then performed to evaluate the residual strain of the composite plates under Impact Energy (IE) loading less than 15 J. Then, the residual plastic strain in the impact zone is evaluated using a meso-macro method, and the effect of the local plasticity that occurs in the gap zones on the delamination initiation and propagation is studied. Results show that the stress relaxation due to the resin plasticity at the gap areas can affect the delamination pattern of the impacted composite plates. It is also shown that the residual strain of the impacted plates at the gap areas are new sources of the damages that need to be considered in the LVI analysis of the composite plates manufactured by the AFP technique.

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