A Review of Structural Health Monitoring Techniques as Applied to Composite Structures.

Structural Health Monitoring (SHM) is the process of collecting, interpreting, and analysing data from structures in order to determine its health status and the remaining life span. Composite materials have been extensively use in recent years in several industries with the aim at reducing the total weight of structures while improving their mechanical properties. However, composite materials are prone to develop damage when subjected to low to medium impacts (ie 1 – 10 m/s and 11 – 30 m/s respectively). Hence, the need to use SHM techniques to detect damage at the incipient initiation in composite materials is of high importance. Despite the availability of several SHM methods for the damage identification in composite structures, no single technique has proven suitable for all circumstances. Therefore, this paper offers some updated guidelines for the users of composites on some of the recent advances in SHM applied to composite structures; also, most of the studies reported in the literature seem to have concentrated on the flat composite plates and reinforced with synthetic fibre. There are relatively fewer stories on other structural configurations such as single or double curve structures and hybridised composites reinforced with natural and synthetic fibres as regards SHM

Smart FRP Composite Sandwich Bridge Decks in Cold Regions

INE/AUTC 12.0

Comparative study of minimum quantity lubrication and dry drilling of CFRP/titanium stacks using TiAlN and diamond coated drills

Although minimum quantity lubrication (MQL) has been proved beneficial for the machinability improvement of metallic materials, it is still not well understood whether or not to use the MQL when machining the composite-titanium stacks and whether the MQL can achieve a comparable effect as it operates in the metal cutting processes. The current work is aimed at revealing the underlying mechanisms of the MQL drilling on the CFRP/Ti6Al4V stacks. Both the MQL and dry conditions were examined using the TiAlN-coated and diamond-coated carbide drills to quantify how the MQL operates when compared with the conventional dry machining. The effects of the MQL environment on the machinability of the composite-titanium stacks were quantified in terms of drilling thrust forces, delamination damage of the composite phase and tool wear signatures. A particular emphasis is put on the wettability testing of cut stack hole surfaces versus the minimum quantity lubricants in terms of the contact angle. The results indicate that the machined composite surface shows a strong ability to absorb the lubricants under the MQL condition and fails to form a protective oil film at the drill-chip interface, resulting in an increase of thrust forces and delamination damage. Moreover, the MQL environment cannot prevent the drill bits from premature failures during the machining of CFRP/Ti6Al4V. It is indicated that the MQL fails to yield a comparable beneficial role as it operates in the machining of individual metal alloys in terms of the examined drilling responses.publishe

Artificial neural network based delamination prediction in composite plates using vibration signals

Dynamic loading on composite components may induce damages such as cracks, delaminations, etc. and development of an early damage detection technique for delaminations is one of the most important aspects in ensuring the integrity and safety of composite components. The presence of damages such as delaminations on the composites reduces its stiffness and further changes the dynamic behaviour of the structures. As the loss in stiffness leads to changes in the natural frequencies, mode shapes, and other aspects of the structure, vibration analysis may be the ideal technique to employ in this case. In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network (ANN) is used to determine the position and area of delaminations in GFRP plates using changes in natural frequencies as inputs. The natural frequencies were obtained by finite element analysis and results are validated by experimentation. The findings show that the suggested technique can satisfactorily estimate the location and extent of delaminations in composite plates

Supervised and non-supervised AE data classification of nanomodified CFRP during DCB tests

Aim of the paper is to use acoustic emissions to study the effect of electrospun nylon 6,6 Nanofibrous mat on carbon-epoxy composites during Double Cantilever beam (DCB) tests. In order to recognize the effect of the nanofibres and to detect different damage mechanisms, k-means clustering of acoustic emission signals applied to rise time, count, energy, duration and amplitude of the events is used. Supervised neural network (NN) is then applied to verify clustered signals. Results showed that clustered acoustic emission signals are a reliable tool to detect different damage mechanisms; neural network showed the method has a 99% of accuracy

Analysis of the Response of Modal Parameters to Damage in CFRP Laminates Using a Novel Modal Identification Method

Nowadays, composite materials are widely used in several industries, e.g. the aeronautical, automotive, and marine, due to their excellent properties, such as stiffness and strength to weight ratios and high resistance to corrosion. However, they are prone to develop Barely Visible Impact Damage (BVID) from low to medium energy impacts (i.e. 1 – 10 m/s and 11 – 30 m/s respectively) that are reported to occur during both service and maintenance, such as bird strike; hailstones and tool drops. Therefore, Structural Health Monitoring (SHM) techniques have been developed to allow identifying damage at an early stage, in an attempt to avoid catastrophic consequences. Vibration measurement was conducted on healthy and damaged Carbon Fibre Reinforced Polymers (CFRPs) specimens. Damage is introduced to the specimen through a static indentation and the work done by the hemispherical indenter measured. This test was mainly for the purpose of damage introduction in the test samples. In this work, the effects of damage on the individual mode were studied to understand the response pattern of the modal parameters. It is intended that the current study will inform the development of a new damage identification method based on the variations between healthy and damaged specimen’s dynamic results. A new modal identification method (“Elliptical Plane”) that uses an alternative plot of the receptance has been developed in this work. The Elliptical Plane method used the energy dissipated per cycle of vibration as a starting point, to identify modal constants from Frequency Response Functions (FRFs). In comparison with the method of inverse, this new method produces accurate results, for systems that are lightly damped with its modes well-spaced. The sine of the phase of the receptance is plotted against the amplitude of the receptance, through which damping was calculated from the slope of a linear fit to the resulting plot. The results show that, there are other relevant properties of the plot that were not yet delve into by researchers. The shape of the plot is elliptical, near the resonant frequencies, whereby both parts of the modal constants (real and imaginary) can be determined from numerical curve-fitting. The method offers a new perspective on the way the receptance may be represented, in the Elliptical Plane, which may bring valuable insights for other researchers in the field. The novel method is discussed through both numerical and experimental examples. It is a simple method and easy to use. Interestingly, as the energy level increases, the percentage changes in both the modal frequency and damping increases. The linear equations reveal that there is a correlation between the increase in energy and the percentage variation in modal frequency and damping, especially from a threshold energy level determined to be between 15J and 20J for the analysed cases. Finally, modal identification is conducted on the healthy and damaged specimens, and the results were analysed with BETAlab software and the Elliptical Modal identification method. It was observed that the Elliptical Modal identification method provides some interesting results. For instance, a comparison between the modal damping from the ellipse and BETAlab methods revealed that, the level of reduction in the modal damping from the ellipse method is higher than that of the BETAlab. This behaviour offers a promising future in the area of damage identification in structures

Recent advances in drilling of carbon fiber–reinforced polymers for aerospace applications: a review

Drilling is considered as one of the most challenging problems in aerospace structures where stringent tolerances are required for fasteners such as rivets and bolts to join the mating parts for final assembly. Fiber-reinforced polymers are widely used in aeronautical applications due to their superior properties. One of the major challenges in machining such polymers is the poor drilled-hole quality which reduces the strength of the composite and leads to part rejection at the assembly stage. In addition, rapid tool wear due to the abrasive nature of composites requires frequent tool change which results in high tooling and machining costs. This review intended to give in-depth details on the progress of drilling of fiber-reinforced polymers with special attention given to carbon fiber–reinforced polymers. The objective is to give a comprehensive understanding of the role of drilling parameters and composite properties on the drilling-induced damage in machined holes. Additionally, the review examines the drilling process parameters and its optimization techniques, and the effects of dust particles on human health during the machining process. This review will provide scientific and industrial communities with advantages and disadvantages through better drilled-hole quality inspection

Structural Health Monitoring in Composite Structures: A Comprehensive Review.

This study presents a comprehensive review of the history of research and development of different damage-detection methods in the realm of composite structures. Different fields of engineering, such as mechanical, architectural, civil, and aerospace engineering, benefit excellent mechanical properties of composite materials. Due to their heterogeneous nature, composite materials can suffer from several complex nonlinear damage modes, including impact damage, delamination, matrix crack, fiber breakage, and voids. Therefore, early damage detection of composite structures can help avoid catastrophic events and tragic consequences, such as airplane crashes, further demanding the development of robust structural health monitoring (SHM) algorithms. This study first reviews different non-destructive damage testing techniques, then investigates vibration-based damage-detection methods along with their respective pros and cons, and concludes with a thorough discussion of a nonlinear hybrid method termed the Vibro-Acoustic Modulation technique. Advanced signal processing, machine learning, and deep learning have been widely employed for solving damage-detection problems of composite structures. Therefore, all of these methods have been fully studied. Considering the wide use of a new generation of smart composites in different applications, a section is dedicated to these materials. At the end of this paper, some final remarks and suggestions for future work are presented

Natural Frequency based delamination estimation in GFRP beams using RSM and ANN

The importance of delamination detection can be understood from aircraft components like Vertical Stabilizer, which is subjected to heavy vibration during the flight movement and it may lead to delamination and finally even flight crash can happen because of that. Any solid structure's vibration behaviour discloses specific dynamic characteristics and property parameters of that structure. This research investigates the detection of delamination in composites using a method based on vibration signals.  The composite material's flexural stiffness and strength are reduced as a result of delaminations, and vibration properties such as natural frequency responses are altered. In inverse problems involving vibration response, the response signals such as natural frequencies are utilized to find the location and magnitude of delaminations. For different delaminated beams with varying position and size, inverse approaches such as Response Surface Methodology (RSM) and Artificial Neural Network (ANN) are utilized to address the inverse problem, which aids in the prediction of delamination size and location