Damage Position Research Articles

Damage detection and localization from linear and nonlinear global vibration features in concrete slabs subjected to localized thermal damage

In this study, different alternatives to detect and localize damage from linear and nonlinear vibration responses were investigated. These alternatives were compared on two concrete slabs subjected to different damage extents. Linear and nonlinear modal test configurations were considered. The variations of linear resonant frequencies, modal assurance criterion values, and nonlinear hysteretic parameters were used to detect damage. Then, the modal shapes were used to locate damage positions. The maximum principal curvatures derived from the original modal shape displacements between damaged and undamaged states made it possible to spot the damaged zones. Damage localization was further enhanced by weighting the principal modal shape curvature differences for every mode by their respective variations of the nonlinear hysteretic parameter. Finally, damage localization was achieved using different outlier identification techniques.

Hinge joint damage identification method of soft yoke mooring system based on multibody dynamic modeling and structural monitoring data

Soft yoke mooring system (SYMs) is a single-point mooring system used in shallow water oil and gas development. In general, SYMs consists of mooring framework support, mooring legs, yoke, and single-point turret and it forms a multibody dynamic system with 13 hinge joint structures such as universal joints and thrust bearings. The hinge joint is one of the key components of SYMs; therefore, it is necessary to accurately evaluate the operating behavior of the hinge joints. In this study, real-time damage identification is conducted based on the multibody dynamic features of the SYMs. First, a long-term monitoring strategy for the prototype application is developed based on the multibody governing equations of the SYMs. The motion behaviors and stress state of the hinge joints and bodies are calculated using prototype monitoring data. A hinge joint damage identification based on the virtual moment is proposed by considering the changes in the friction coefficient in the damage state. The virtual moment method is used to transform the damage identification problem of the SYMs into a problem of seeking the optimal solution to the dynamics identification function. Genetic algorithm (GA) is implemented to seek the optimal solution of the friction coefficient of each hinge joint. A large-scale model testing system of the SYMs is established to perform the damage identification of the bottom hinge joints of the SYMs. The results show that the proposed method can effectively identify the damage degree and position of the hinge joints of the SYMs and provide a real-time warning system for the in-service operation of the SYMs.

Neural network-based damage identification in composite laminated plates using frequency shifts

Delamination is the principal mode of failure of laminated composites. It is caused by the rupture of the fiber–matrix interface and results in the separation of the layers. This failure is induced by interlaminate tension and shear that is developed due to a variety of factors such as fatigue. Composites are known for excellent structural performance, which can be significantly affected by delamination. Such damages are not always visible on the surface and can lead to sudden catastrophic failures. To ensure a structural performance and integrity, accurate methods to monitor damages are required. This work presents a methodology for damage detection and identification on laminated composite plates using artificial neural networks fed with modal data obtained by finite element analysis. The proposed neural network to quantify damage severity achieved up to 95% success rate. A comparative study was done to evaluate the effect of boundary conditions on damage location. With the comparative study results, another neural network was proposed to locate damage position, achieving excellent results by successfully locating or by significantly reducing the search area. Both proposed ANNs use only frequency variation values as inputs, an easily obtainable quantity that requires few equipment to be acquired. The obtained results from these numerical examples indicate that the proposed approach can detect true damage locations and estimate damage magnitudes with satisfactory accuracy for this particular geometry, even under high measurement noise.

Modeling of damage behavior of carbon fiber reinforced plastic composites interference bolting with sleeve

Interference-fit is getting increasing attentions in the aerospace field owing to its excellent enhancement on the sealing and fatigue life of composites assembly, but the severe damage around the hole caused by installation is still a huge challenge. In this paper, a three-dimensional anisotropic non-linear progressive damage model based on continuum damage mechanics was developed to reveal the damage mechanism of carbon fiber reinforced plastic (CFRP) composites interference bolting with sleeve. The proposed model adopted strain-based failure criteria and non-linear damage evolution law to predict damage initiation and propagation of composite laminates. A cohesive model taking into account the traction-separation constitutive response was employed to capture the delamination behavior between the composite plies. The elastoplastic model was utilized to characterize the sleeve's deformation behavior. Numerical simulations of different installation modes are performed and compared with experiments. The inserting load, damage modes and damage positions predicted by the proposed model agree well with the experimental results. Moreover, it is also verified that the interference installation of sleeved fasteners can remarkably reduce the intra-laminar damage and avoid the inter-laminar delamination of composite laminates compared to the conventional bolt.

A reduced-order modelling for real-time identification of damages in multi-layered composite materials

This work is focused on the detection of interlayer damages in multi-layer composite materials, which use the inverse analysis approach based on the reduced-order models (ROMs). Direct problems including heat conduction through the solid and heat radiation to the space are solved by finite element method (FEM), and the solutions of transient nonlinear analysis are collected to build the snapshot data matrix. The Proper Orthogonal Decomposition (POD) method coupled with two surrogate models are utilized to construct a low dimensional model which can be used to rebuild physical fields. By minimizing the discrepancy of measured and simulated temperatures using ROMs, the optimal parameter values related to damages can be estimated efficiently. Results prove that an excellent estimation on the position of damages can be obtained in the multi-layer materials. The computational efficiency and solution accuracy of two ROMs are compared, which proves that the POD-Kriging method has faster convergence speed than the POD-RBF method, with the same fitness value. Moreover, noise analysis validates that two ROMs have similar stability, whereas the POD-Kriging method is easier to achieve convergence in this type of problems.

Single-crystalline SiC integrated onto Si-based substrates via plasma-activated direct bonding

We propose a plasma-activated direct bonding process at low temperatures (≤200 °C) to form heterostructures between single-crystalline SiC and conventional Si-based substrates (SiO2, Si, and glass) without any interlayers. Surface activation was performed via an inductively coupled O2 plasma for 60 s with a lower bombardment damage position. The SiC surfaces were much more hydrophilic after activation, and the generation of defect states was suppressed. Consequently, void-free and robust bonding interfaces of SiC/SiO2, SiC/Si and SiC/glass were successfully achieved. There were no carbon-enriched layers across the bonding interfaces, which could improve the electrical properties of SiC-based devices. Additionally, the bonding interface of SiC/glass exhibited excellent optical transparency, and interfacial corrosion resistance was confirmed via immersion tests in biological solutions. This bonding method provides a feasible route towards industry-compatible heterogeneous integration of single-crystalline bulk SiC onto Si-based platforms for electronic, optical, mechanical, and biomedical applications.

Foran Application on Damage Stability Assessment on a Container Vessel

The paper focuses on two aspects. One is SENER incentives to work with the educational community by providing the FORAN software as a collaboration mean that centres on helping to develop the FORAN system, and the other way around the use of the FORAN system for academic purposes in universities, to improve and complement the teaching and training process for students. The second part of the paper focuses more on a technical details on the design procedure for the damage stability and the safety assessment criteria that is established accordingly. Stability assessment is performed using the FORAN software, with the creation of explicit damage events by a fully automated simulation, established from the uniformly distributed random numbers with given probability distributions for size and position of damage and an example on a container ship presented.

Application of the DAD method for damage localisation on an existing bridge structure using close-range UAV photogrammetry

A novel damage detection and localisation method, the so-called Deformation Area Difference method for localisation of damages in bridge structures is introduced. The method is based on static load-deflection experiments with the prerequisite of high precise deflection measurement. This study presents the first experiences of applying the DAD method on a real bridge structure. The investigated structure is a prestressed concrete slab bridge with a span of about 27 m, which was built in 2013. The loading on the bridge is applied using six heavy trucks, each weighing up to 32 t. A wide range of the modern measurement technologies were used to achieve high precision measurements of the bridge deflection along the longitudinal axis, namely the photogrammetry using a big size drone, laser scanner, total station, levelling and displacement sensors. The performed load-deflection test was non-destructive since the maximum deformation did not exceed the serviceability limit state. The exercise of the novel damage detection and localisation method on a real structure initiated further optimisation opportunities of the DAD method and the study of its limits. Several boundary conditions and methodical influence factors related to the applicability of the proposed method were analysed, such as impacts of measurement precision, damage degree, the position of damage, and the number of measurement repetitions.

A nonlinear ultrasonic SHM method for impact damage localisation in composite panels using a sparse array of piezoelectric PZT transducers

Structural health monitoring techniques (SHM) for material damage identification have demonstrated higher sensitivity and accuracy when relying on the assessment of nonlinear features exhibited in the material response under ultrasonic wave propagation. In this paper, a novel nonlinear ultrasonic SHM method is introduced for localisation of impact damage in composite laminates using an array of surface-bonded sensors. Unlike existing algorithms, this method enables quick selection of a suitable signal transmission frequency based on the combined sensor-material response, it does not rely on baseline data or complex measurements of signal arrival time, and it allows identification of malfunctioning sensors to minimise damage localisation errors. The proposed technique is based on the transmission and reception of ultrasonic waves through the inspected panel. Initially, the functionality of the transducers is inspected by comparing the signal amplitude in both directions of sensor-to-sensor paths. Then a planar map of material nonlinearity parameter β is created, and the damage position is defined as the point of highest β amplitude. Experimental tests on three CFRP panels confirmed successful positioning of barely visible impact damage (BVID) within a range of 4–22 mm. Sensor functionality check was demonstrated on one of the composite laminates, and a malfunctioning transducer was detected. The results suggested that the presented method could be considered an improved alternative to existing SHM techniques for localisation of BVID in composite panels.

Fatigue life evaluation of web butt welding structure on boom of excavator by hot spot stress approach

The working load of excavator is complex and the working environment is bad. As the main part of excavator, the boom bears a large complex load and is prone to fatigue damage. A large hydraulic excavating boom is taken as the research object in this paper, aiming at the damaged position in the platform fatigue test, that is, the web butt weld on the root of the boom, and the fatigue life of this part is evaluated by means of hot spot stress and load spectrum. The result shows that the theoretical lifetime of this part is 4148 h, which is completely agree with the equivalent life 4278 h when the cracks appeared in bench fatigue tests. Accordingly, the hot spot stress approach is suitable for the fatigue life evaluation of the boom, and its accuracy is high.

Guided electromagnetic waves for damage detection and localization in metallic plates: numerical and experimental results

AbstractElectromagnetic waves in the microwave and millimeter-wave frequency range are used in non-destructive testing and structural health monitoring applications to detect material defects such as delaminations, cracks, or inclusions. This work presents a sensing concept based on guided electromagnetic waves (GEW), in which the waveguide forms a union with the structure to be inspected. Exploiting ultra-wideband signals a surface defect in the area under the waveguide can be detected and accurately localized. This paper presents numerical and experimental GEW results for a straight waveguide focusing on the detection of through holes and cracks with different orientation. It was found that the numerical model qualitatively replicates the experimental S-parameter measurements for holes of different diameters. A parametric numerical study indicates that the crack parameters such as its orientation and width has a significant influence on the interaction of the incident wave with the structural defect. On top, a numerical study is performed for complex-shaped rectangular waveguides including several waveguide bends. Besides a successful damage detection, the damage position can also be precisely determined with a maximum localization error of less than 3%.

Three-dimensional laser damage positioning by a deep-learning method.

A holographic and deep learning-based method is presented for three-dimensional laser damage location. The axial damage position is obtained by numerically focusing the diffraction ring into the conjugate position. A neural network Diffraction-Net is proposed to distinguish the diffraction ring from different surfaces and positions and obtain the lateral position. Diffraction-Net, which is completely trained by simulative data, can distinguish the diffraction rings with an overlap rate greater than 61% which is the best of results reported. In experiments, the proposed method first achieves the damage pointing on each surface of cascade slabs using diffraction rings, and the smallest inspect damage size is 8µm. A high precision result with the lateral positioning error less than 38.5µm and axial positioning error less than 2.85mm illustrates the practicability for locating the damage sites at online damage inspection.

An adaptive method of damage detection for fishing nets based on image processing technology

For offshore aquaculture cages, structural damage can cause serious economic property damage to the aquaculture industry, thus it is necessary to carry out regular inspections of the cage structure. At present, the main method of detecting netting damage is that the staff sneak into the water for manual investigation. This method not only does not guarantee personal safety, but is also labor-intensive and inefficient. This paper proposes a new feature curve method for non-contact underwater netting damage detection, which can effectively recognize damaged netting and analyze the degree of damage for the underwater net and return to its damage position. The new method presented in this paper was designed taking into consideration of effect of seaweed growth: Firstly, an image block within the ROI (region of interest) region was processed by bilateral filter. Secondly, the binary image was obtained via the OSTU (the maximum inter-class variance method) method and connected domain detection was performed. Thirdly, the feature gradient histogram was calculated according to the area of the mesh hole and the local peaks of the curve (named as feature curve) was searched to determine the position of damage in the netting. The proposed method combined the image processing technology with aquaculture engineering seamlessly, and reduced the complexity of the detection system greatly, and significantly improved the efficiency of the netting detection. Finally, the MATLAB program was developed to realize the netting detection process and the proposed method had been verified by the actual underwater netting experiment. The experimental results showed that the netting damage detection method proposed in this paper can successfully detect crack of the netting despite image degradation in water.

Seismic Behavior of Pile-Group-Supported Bridges in Liquefiable Soils with Crusts Subjected to Potential Scour: Insights from Shake-Table Tests

One-g shake-table tests were conducted to characterize seismic demands and reveal failure mechanisms of pile-supported bridges in liquefiable soils with crusts subjected to different scour scenarios, namely no scour, partial scour, and complete scour of the crusts. To this end, reinforced concrete bridge models, each consisting of a single pier supported by a 2×2 pile group, were constructed and embedded into liquefiable soil profiles with a full crust or with a partial crust or without crusts to represent the studied three scour scenarios. Physical observations and characteristic soil and structural responses are interpreted first, followed by the primary focus on seismic failure mechanisms and kinematic and inertial effects on pile responses. Test results indicate that scour tends to strongly affect failure mechanisms of the studied bridges via shifting damage positions from pier bottoms to pile heads and from piles at crust-sand interfaces to pile heads. This tendency is against the current capacity design principle that piers should fail before pile foundations. Special attention should be paid to future seismic design of bridges undergoing scour and liquefaction. Furthermore, the kinematic effect is found more prominent before scour, whereas the inertial effect itself becomes more influential after scour.

Exploration on Damage Mechanism and Equivalent Damage Model of High Arch Dams under Earthquakes

Damage identification technology of high arch dams has been well developed under strong earthquakes. However, the failure mechanism of high arch dams at different locations remains unclear. For this purpose, a series of deterministic dynamic analyses for a 3D 289-m-high arch dam based on concrete damaged plasticity constitutive model are performed. The failure mechanism at different locations of high arch dams under earthquakes is studied systematically. According to the sensitivity of different indicators to different damaged positions, an effective sensor placement scheme is proposed to assess the seismic reliability in practical engineering. Furthermore, a new effective equivalent damage model based on prior information is proposed, which can improve the efficiency of damage identification, as well as solving the problem that the real damage is concealed by homogenizing the damage in a pre-set region. The results provide suggestions and theoretical basis for sensor placement in actual monitoring of high arch dams; and the equivalent damage model provides a new solution to balance the efficiency and accuracy of damage identification.

Multi-scale method for recognizing damage in high-efficiency milling cutter

Under the influence of a high-speed, interrupted-cutting impact load, the damage degree quickly increases following any structural damage in a milling cutter. The presence of structural damage must be explored given the fact that these conditions may result in irreparable and serious accidents if not immediately detected. Milling cutter damage has multi-scale characteristics. Therefore, the single-scale damage research method cannot reveal the formation and evolution of the multi-scale damage of a milling cutter, which makes it difficult to identify and control the damage of a milling cutter. The damage scales of a milling cutter are divided according to the multi-scale characteristics of milling cutter damage. Based on continuum mechanics, the dislocation theory, and molecular dynamics, the damage characterization method of the macrostructure, lattice structure, and mesoscopic structure of a milling cutter were proposed in this study. Utilizing the multi-scale finite element method and the force connection method, the loading boundary conditions of the multi-scale damage of a milling cutter were established in order to achieve a trans-scale load transfer. The damage characteristics of the macrostructure, lattice structure, and mesoscopic structure of the milling cutter were studied, and the critical value of the multi-scale damage characteristic variable of the milling cutter was obtained. Thereby, the damage position, types, and size and damage occurrence sequences of the milling cutter were revealed, and the damage formation process and the characteristics of the milling cutter were clarified. Based on this, a method for recognizing the multi-scale damage in a milling cutter was proposed and verified by experiments. The results showed that the above method could effectively identify multi-scale damage characteristics and reveal the formation and evolution process of the damage of a high-efficiency milling cutter.

Study on gear contact fatigue failure competition mechanism considering tooth wear evolution

Contact fatigue issues are becoming more prominent in current gear anti-fatigue designs. Surface wear may result in unavoidable occurrence competition among contact fatigue failure modes such as micropitting and pitting. This work proposed a model incorporating the interface characteristics, mechanical properties and residual stress gradients to explore this competition mechanism during wear process of a wind turbine gear pair. Results reveal that the critical damage position moves deeper from near-surface to subsurface during the wear process, indicating that the most likely failure mode changes gradually from surface initiated contact failure to subsurface initiated contact failure. This illustrates that one-sided gear anti-fatigue designs may not satisfy the complex contact conditions because the dominant failure mode may change during operation.

Analysis on microseismic characteristics and stability of the access tunnel in the main powerhouse, Shuangjiangkou hydropower station, under high in situ stress

Access tunnel in the main powerhouse of Shuangjiangkou hydropower station was deep buried with high in situ stress and complex geological conditions. Microseismic monitoring technology was established to monitor microcrack evolution process inside the surrounding rock in early excavation stage. Serious falling blocks in the left spandrel of the tunnel were predicted in a timely manner by delimiting major damage areas in the tunnel. Based on comparative analysis on microseismic activity law and field failure characteristics of the access tunnel, a quantitative index was supposed between slight rockburst like falling blocks and microseismic events. Moreover, the change law of daily average apparent stress difference and b value were analyzed based on microseismic event data. In addition, a three-dimensional numerical simulation software (RFPA3D) was used to simulate the damage distribution around the tunnel, and a relationship between spatial position of tunnel damage and direction of the maximum principal stress was qualitatively analyzed. The study results showed that advance speed of the tunnel working face was an important factor affecting the state of stress redistribution in surrounding rock mass, and the change law of b values of microseismic events could be used to predict activity state inside the surrounding rock effectively, which reflected mechanical properties and stress state of surrounding rock. In particular, field falling blocks became more serious with increasing b value, and field surrounding rock was relatively stable with minor b value. A risk of surrounding rock instability was relatively high with small b values. It provided an efficient method of predicting and assessing slight rockburst like falling blocks. The study results can provide significant guidance for field construction and later construction planning.

Critical position of fatigue damage within asphalt pavement considering temperature and strain distribution

ABSTRACT The fatigue properties of the asphalt pavement layer are influenced significantly by different strain levels and temperatures. This research investigated the critical fatigue position within the asphalt pavement layer considering the couple effects of strain levels and temperatures. Firstly, field tests were conducted to measure the typical temperature distribution of the asphalt pavement layer. Secondly, laboratory four-point beam fatigue test and dynamic modulus test were applied to evaluate the fatigue life and the dynamic modulus of the asphalt mixture, respectively. Based on the results of field and laboratory tests, the distributions of strain and fatigue damage within the asphalt layer at different temperature conditions were calculated. It was found that the fatigue life of asphalt mixture decreased with the rising strain level but increased with the rising temperature. The critical fatigue position in the flexible pavement changed from 5 to 20 cm when the pavement temperature condition varied from high to medium/low. In terms of the semi-rigid pavement, this position varied between 6 and 12 cm at different temperature conditions. In addition, the fatigue damage within the semi-rigid pavement at high temperature was found to be as noticeable as that at medium/low temperatures. Thus, the fatigue properties of the asphalt layer at higher temperatures need to be carefully evaluated as well.

An effective deep feedforward neural networks (DFNN) method for damage identification of truss structures using noisy incomplete modal data

Structural damage assessment is a challenging problem of study due to lack of information in data measurement and the difficulty of extracting noisy features from the structural responses. Therefore, this paper proposes an effective deep feedforward neural networks (DFNN) method for damage identification of truss structures based on noisy incomplete modal data. In the proposed approach, incomplete datasets are randomly generated by a reducing finite element (FE) model. Based on the collected data, the DFNN model is constructed to predict damage position and severity of structures. To obtain a better performance of the network, the new ReLu activation function and Adadelta algorithm are employed in this work. In addition, the state-of-the-art mini-batch and dropout techniques are adopted to speed up the training process and avoid the over-fitting issue in training networks. Various hyperparameters such as number of hidden units, layers and epoches are surveyed to built a good training model. In order to demonstrate the efficiency and stability of the proposed method, a 31-bar planar truss structure and a 52-bar dome-like space truss structure are investigated with various damage scenarios. Moreover, the performance of the DFNN method is not only illustrated with the noise free input data but also with noisy input data. Different noise levels of the input data are taken into account in this study. To accurately predict the damage location and severity of the structures, 10000 and 20000 data samples corresponding to the 31-bar planar truss and the 52-bar dome-like space truss are randomly created in term of quantity of damage members, damage locations and damage severity of the structures for training the DFNN models. The results predicted by the DFNN using incomplete modal data are compared with those of the complete and actual models. The obtained results indicate that the DFNN is a promising method in damage localization and quantification of civil engineering structures.