scholarly journals Interfacial damage identification of steel and concrete composite beams based on piezoceramic wave method

2018 ◽  
Vol 16 (1_suppl) ◽  
pp. 70-80 ◽  
Author(s):  
Shi Yan ◽  
Yong Dai ◽  
Putian Zhao ◽  
Weiling Liu
Keyword(s):  
Damage Detection ◽  
Composite Structure ◽  
Composite Structures ◽  
Damage Identification ◽  
Composite Beams ◽  
External Loading ◽  
Interface Debonding ◽  
Composite Effect ◽  
Interface Damage ◽  
Flange Forming

Introduction: Steel-concrete composite structures are playing an increasingly important role in economic construction because of a series of advantages of great stiffness, good seismic performance, steel material saving, cost efficiency, convenient construction, etc. However, in service process, due to the long-term effects of environmental impacts and dynamic loading, interfaces of a composite structure might generate debonding cracks, relative slips or separations, and so on, lowering the composite effect of the composite structure. Methods: In this paper, the piezoceramics (PZT) are used as transducers to perform experiments on interface debonding slips and separations of composite beams, respectively, aimed at proposing an interface damage identification model and a relevant damage detection innovation method based on PZT wave technology. Results: One part of various PZT patches was embedded in concrete as “smart aggregates,” and another part of the PZT patches was pasted on the surface of the steel beam flange, forming a sensor array. Conclusions: A push-out test for four specimens was carried out and experimental results showed that, under the action of the external loading, the received signal amplitudes will increasingly decrease with increase of debonding slips along the interface. The proposed signal energy-based interface damage detection algorithm is highly efficient in surface state evaluations of composite beams.

FIRE RESISTACE OF SHEAR CONNECTORS FOR COMPOSITE BEAMS

2020 ◽  
Vol 92 (6) ◽  
pp. 59-65
Author(s):  
G.P. TONKIH ◽  
◽  
D.A. CHESNOKOV ◽  
◽  
Keyword(s):  
Fire Resistance ◽  
Composite Structure ◽  
Composite Structures ◽  
Composite Beams ◽  
Design Codes ◽  
Connection Strength ◽  
Shear Connectors ◽  
Shear Connection ◽  
Capacity Reduction ◽  
Russian Research

Most of Russian research about composite structure fire resistance are dedicated to the composite slab behavior. The composite beams fire resistance had been never investigated in enough volume: the temperature evaluation within the scope of the actual Russian design codes leads to the significant reduction in the shear connection strength. Meanwhile, there no correlation between the strength decreasing and type of the shear connection. The article provides an overview of the relevant researches and offers some approaches which could take into account bearing capacity reduction of the shear connectors within composite structures design.

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.

Damage Detection in Composite Skin Stiffener with Hybrid PZT-FO SHM System

2017 ◽  
Vol 754 ◽  
pp. 367-370 ◽  
Author(s):  
Florian Lambinet ◽  
Zahra Sharif Khodaei
Keyword(s):  
Damage Detection ◽  
Hybrid System ◽  
Composite Structure ◽  
Composite Structures ◽  
Diagnostic System ◽  
Fibre Optic ◽  
Artificial Damage

A hybrid piezoelectric (PZT)/fibre optic diagnostic system has been developed for damage detection in built up composite structures. The hybrid system uses PZT transducers to actuate the structure and fibre optic (FO) sensors to capture the propagating wave. The diagnostic system will then have the advantages of both PZT and FO sensors. The applicability of the system is then tested for detecting an artificial damage at a skin/stiffener interface of a thick composite structure. The response of the FO sensors is then compared to PZT sensors and presented.

scholarly journals Identification of Delamination in Composite Beams using the Fractal Dimension-Based Damage Identification Algorithm

2017 ◽  
Vol 2017 (9) ◽  
pp. 5-16
Author(s):  
Andrzej Katunin ◽  
Michał Zuba
Keyword(s):  
Fractal Dimension ◽  
Damage Detection ◽  
Damage Identification ◽  
Computational Study ◽  
Numerical Data ◽  
Composite Beams ◽  
Computational Time ◽  
Detection Accuracy ◽  
Identification Algorithm ◽  
Promising Alternative

AbstractDamage detection and identification is one of the most important tasks of proper operation of technical objects and structures. It is, therefore, essential to develop efficient and sensitive methods of early damage detection. Delamination is the type of damage occurring in laminated composites that is one of the most dangerous and most difficult to detect. In this paper, the computational study was performed on the numerical data of the modal shapes of laminated composite beams with simulated delaminations in order to detect them using a fractal dimension-based approach. The obtained results allowed for improvement of detection accuracy as compared to previously applied wavelet-based approach. An additional benefit was decreasing the computational time. Basing on the obtained results it is reasonable to consider the presented approach as a promising alternative to currently applied signal processing methods used for supporting non-destructive testing of structures.

Sparse damage detection via the elastic net method using modal data

2021 ◽  
pp. 147592172110219
Author(s):  
Rongrong Hou ◽  
Xiaoyou Wang ◽  
Yong Xia
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Measurement Data ◽  
Elastic Net ◽  
Sensitivity Matrix ◽  
Regularization Technique ◽  
Modal Data ◽  
Regularization Techniques ◽  
Net Method

The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice the independency criteria of the l1 regularization technique. This study employs the elastic net method to solve the problem by combining the l1 and l2 regularization techniques. Moreover, the proposed method enables the grouped structural damage being identified simultaneously, whereas the l1 regularization cannot. A numerical cantilever beam and an experimental three-story frame are utilized to demonstrate the effectiveness of the proposed method. The results showed that the proposed method is able to accurately locate and quantify the single and multiple damages, even when the number of measurement data is much less than the number of elements. In particular, the present elastic net technique can detect the grouped damaged elements accurately, whilst the l1 regularization method cannot.

Probability-based diagnostic imaging with corrected weight distribution for damage detection of stiffened composite panel

2021 ◽  
pp. 147592172110339
Author(s):  
Guoqiang Liu ◽  
Binwen Wang ◽  
Li Wang ◽  
Yu Yang ◽  
Xiaguang Wang
Keyword(s):  
Distribution Function ◽  
Diagnostic Imaging ◽  
Weight Distribution ◽  
Composite Structures ◽  
Damage Identification ◽  
Guided Wave ◽  
Composite Panel ◽  
Damage Localization ◽  
Localization Accuracy ◽  
Direct Interpretation

Due to no requirement for direct interpretation of the guided wave signal, probability-based diagnostic imaging (PDI) algorithm is especially suitable for damage identification of complex composite structures. However, the weight distribution function of PDI algorithm is relatively inaccurate. It can reduce the damage localization accuracy. In order to improve the damage localization accuracy, an improved PDI algorithm is proposed. In the proposed algorithm, the weight distribution function is corrected by the acquired relative distances from defects to all actuator–sensor pairs and the reduction of the weight distribution areas. The validity of the proposed algorithm is assessed by identifying damages at different locations on a stiffened composite panel. The results show that the proposed algorithm can identify damage of a stiffened composite panel accurately.

scholarly journals High Performance NbMoTa–Al2O3 Multilayer Composite Structure Manufacturing by Laser Directed Energy Deposition

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1685
Author(s):  
Hang Zhang ◽  
Zihao Chen ◽  
Yaoyao He ◽  
Xin Guo ◽  
Qingyu Li ◽  
...  
Keyword(s):  
Smart Materials ◽  
Composite Structure ◽  
Composite Structures ◽  
High Performance ◽  
Energy Deposition ◽  
Coefficient Of Thermal Expansion ◽  
Multilayer Composite ◽  
Forming Process ◽  
Directed Energy Deposition ◽  
Directed Energy

The conventional method of preparing metal–ceramic composite structures causes delamination and cracking defects due to differences in the composite structures’ properties, such as the coefficient of thermal expansion between metal and ceramic materials. Laser-directed energy deposition (LDED) technology has a unique advantage in that the composition of the materials can be changed during the forming process. This technique can overcome existing problems by forming composite structures. In this study, a multilayer composite structure was prepared using LDED technology, and different materials were deposited with their own appropriate process parameters. A layer of Al2O3 ceramic was deposited first, and then three layers of a NbMoTa multi-principal element alloy (MPEA) were deposited as a single composite structural unit. A specimen of the NbMoTa–Al2O3 multilayer composite structure, composed of multiple composite structural units, was formed on the upper surface of a φ20 mm × 60 mm cylinder. The wear resistance was improved by 55% compared to the NbMoTa. The resistivity was 1.55 × 10−5 Ω × m in the parallel forming direction and 1.29 × 10−7 Ω × m in the vertical forming direction. A new, electrically anisotropic material was successfully obtained, and this study provides experimental methods and data for the preparation of smart materials and new sensors.

scholarly journals Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2005
Author(s):  
Veronika Scholz ◽  
Peter Winkler ◽  
Andreas Hornig ◽  
Maik Gude ◽  
Angelos Filippatos
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Composite Structures ◽  
Damage Identification ◽  
Vibration Response ◽  
Damage Initiation ◽  
Matrix Cracks ◽  
Operational Life ◽  
Multiple Data Sets ◽  
Fully Connected

Damage identification of composite structures is a major ongoing challenge for a secure operational life-cycle due to the complex, gradual damage behaviour of composite materials. Especially for composite rotors in aero-engines and wind-turbines, a cost-intensive maintenance service has to be performed in order to avoid critical failure. A major advantage of composite structures is that they are able to safely operate after damage initiation and under ongoing damage propagation. Therefore, a robust, efficient diagnostic damage identification method would allow monitoring the damage process with intervention occurring only when necessary. This study investigates the structural vibration response of composite rotors by applying machine learning methods and the ability to identify, localise and quantify the present damage. To this end, multiple fully connected neural networks and convolutional neural networks were trained on vibration response spectra from damaged composite rotors with barely visible damage, mostly matrix cracks and local delaminations using dimensionality reduction and data augmentation. A databank containing 720 simulated test cases with different damage states is used as a basis for the generation of multiple data sets. The trained models are tested using k-fold cross validation and they are evaluated based on the sensitivity, specificity and accuracy. Convolutional neural networks perform slightly better providing a performance accuracy of up to 99.3% for the damage localisation and quantification.

scholarly journals Development of a Novel Damage Detection Framework for Truss Railway Bridges Using Operational Acceleration and Strain Response

Vibration ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 422-445
Author(s):  
Md Riasat Azim ◽  
Mustafa Gül
Keyword(s):  
Damage Detection ◽  
Damage Identification ◽  
Numerical Study ◽  
Damage Index ◽  
Strain Analysis ◽  
Time History ◽  
Principal Component ◽  
Element Model ◽  
Railway Bridges ◽  
Truss Bridge

Railway bridges are an integral part of any railway communication network. As more and more railway bridges are showing signs of deterioration due to various natural and artificial causes, it is becoming increasingly imperative to develop effective health monitoring strategies specifically tailored to railway bridges. This paper presents a new damage detection framework for element level damage identification, for railway truss bridges, that combines the analysis of acceleration and strain responses. For this research, operational acceleration and strain time-history responses are obtained in response to the passage of trains. The acceleration response is analyzed through a sensor-clustering-based time-series analysis method and damage features are investigated in terms of structural nodes from the truss bridge. The strain data is analyzed through principal component analysis and provides information on damage from instrumented truss elements. A new damage index is developed by formulating a strategy to combine the damage features obtained individually from both acceleration and strain analysis. The proposed method is validated through a numerical study by utilizing a finite element model of a railway truss bridge. It is shown that while both methods individually can provide information on damage location, and severity, the new framework helps to provide substantially improved damage localization and can overcome the limitations of individual analysis.

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