1,721,009 research outputs found
Shape prediction of bistable plates based on Timoshenko and Ashwell theories
No full textThis work is concerned with the geometrical characterisation of bistable composite plates in order to investigate their curvatures interdependence. The main non linear feature of bistable asymmetric laminates concerns large deflection with small energy input. This is an aspect of particular interest for several applications. Accordingly, there is an increasing importance placed on accuracy/sensitivity of predicting techniques to model bistable deformation shapes. This paper presents a novel forecast model to map the surface profiles of bistable laminates. By Timoshenko and Ashwell approaches, an analytical model is developed to provide an interpretation of the bistable shapes, in terms of principal and anticlastic curvatures. The experimental data (via laser acquisitions), with analytical and Finite Element models, help to understand the relation between material properties, plate dimensions, stacking sequence, curing features of the composite laminates and the bistability phenomenon
S 4 : simple quasi-1D model for structural health monitoring of single lap joint software
No full textImpact detection on thin structures via machine learning approaches
No full textIn this study, machine learning algorithms are trained and compared to identify and characterise impacts effects on typical aerospace panels with different geometries. Experiments are conducted to create a suitable impact dataset. Polynomial regression algorithms and shallow neural networks are applied to panels without stringers and optimised to test their ability to identify the impacts. The algorithms are then applied to panels reinforced with stringers, which represents a significant increase in complexity in terms of the dynamic characteristics of the system under test. The focus is not only on the detection of the impact position, but also on the severity of the event. The aim of the work is to demonstrate the validity of the application of machine learning to impact localization on realistic structures and to demonstrate the simplicity and efficiency of the computations despite the complexity of the test specimens
Elastic waves interference for the analysis of disbonds in single lap joints
Full text linkIn the present paper a method for the Structural Health Monitoring (SHM) of bonded lap joints is presented. This method is based on the interference of elastic waves generated by piezo sensors and travelling along thin bonded plates through the adhesion area. Tone bursts of different extension were generated and, when they encountered the debonded area, the wave speed changed. This affected the wave reflection at the boundary of the disbond and the subsequent interference of the reflected wave with the main wave travelling along the joint. Destructive interference conditions were promoted when the adhesive was partially debonded and this was related to the length of the disbond. In the present study numerical simulations based on finite elements were performed and compared with a simplified analytical model describing the Lamb waves propagation through the joint. The simulation results were subsequently compared with the experimental data and a good agreement was found: the proposed method was simple, straightforward and its application on thin single lap joints provided reliable results
Impact characterization on thin structures using machine learning approaches
No full textMachine learning algorithms are trained and compared to identify and to characterise the impact on typical aerospace panels of different geometry. Experimental activities are conducted to build a proper impacts’ dataset. Polynomial regression algorithm and artificial neural network are applied and optimised to panels without stringer to test their capability to identify the impacts. Subsequently, the algorithms are applied to panels reinforced with stringers that represent a significant increase of complexity in terms of dynamic features of the system to test: the focus is not only on the impact position's detection but also on the event's severity. After the identification of the best algorithm, the corresponding machine learning model is deployed on an ARM processor mini-computer, implementing an impact detection system, able to be installed on board an aerial vehicle, making it a smart aircraft equipped with an artificial intelligence decision-making system
Subharmonics and beating: A new approach to Local Defect Resonance for bonded single lap joints
No full textThe present paper is focused on the analysis of the adhesion integrity of Single Lap Joints (SLJ). The technique adopted for the monitoring is based on the employment of vibration signals generated and received by piezo sensors attached on the specimens surfaces on the two opposite sides of the adhesive. Undamaged joints, when subjected to harmonic excitation, behave linearly exhibiting a spectral response including just the excitation frequency. As soon as the adhesive fails, harmonic excitation induces a rich variety of spectral components in the joints response, including subharmonics and superharmonics. A new approach is presented based on the beating resulting from the superposition of harmonic waves. The interpretation of the spectral content of the joint response is based on an analytical model of the single lap joint with different amounts of debondings associated with a nonlinear behaviour. Local Defect Resonance (LDR)conditions are promoted with the consequent superposition of defect with main structure vibration. Analytical results are compared with experiments and Finite Elements (FE)simulations demonstrating the consistence of the formulation. An efficient method for the Structural Health Monitoring (SHM)of the bonded single lap joints is provided, able to correlate the joint vibrational response to the debonding extension through the analysis of the response spectral content
SHM of Aerospace Bonded Structures with Improved Techniques Based on NEWS
No full textThis work aims at presenting techniques for the damage identification in single lap joints (SLJs). The two proposed experimental approaches, exploiting particular interactions of the structure with vibrational waves produced by piezoelectric sensors, allow to perform a Structural Health Monitoring (SHM) without a baseline. The first technique involves the excitation of the structure by means of stationary sinusoidal waves: the presence of a subharmonic in the frequency response spectrum at a receiver point indicates the presence of damage in the joint. In addition, through a simplified analytical model it is possible to relate the frequency of this subharmonic to the size of the damage. The second technique is based on the use of a tone burst: the exciting sensor sends this transient signal that travels through the bonded area and is subsequently read by the receiving sensor; the information received is the result of an interaction between the sent wave and the reflection of the boundaries, sensitive to possible damages. The attenuation of the burst, studied through the wave equations, gives indications on the size of the damage. Both experimental campaigns were carried out on aluminum SLJs bonded with acrylic adhesive, using piezoelectric sensors (one exciting and one receiving). Simplified analytical models were used to validate the experimental results. The good analytical-experimental correlation confirms the validity of the proposed approaches
Impact characterization on RC airplane model in operation using machine learning
No full textStructural Health Monitoring represents a growing field of great interest for aerospace engineering. This manuscript proposes an on-working SHM method for impact detection on RC airplane by ultrasounds, that is based on Machine Learning algorithms (polynomial regression and neural networks) and is useful to establish critical and dangerous operational conditions. The proposed method can be used to detect impact events both in metallic or composite structures, it is specifically designed to be used on typical fuselage and wing panels and is based on the propagation of Lamb waves in the structure on which PZT sensors are bonded for receiving signals. Algorithms are implemented in order to evaluate the impact location by post-processing the acquired signals. Several test cases are numerically studied before being tested in laboratory and reproduced on-working conditions. A good agreement between the numerical, laboratory and in-flight results is achieved
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