Impulse Excitation Technique Research Articles

Resonance Frequency as an Indicator of the Damage in Carbon Composite Plates: Analysis on Composites Prepared with Conventional and Sustainable Resins Subjected to Impact Tests.

This paper experimentally investigates the impact response of composite laminates made with conventional and bio-based epoxy resin. Drop tower impact tests were conducted at varying energy levels, including repeated low-energy impacts, to evaluate perforation resistance. The laminates' residual strength and damage tolerance were assessed using the Damage Index (DI) and by analysing the resonance frequency variations through the Impulse Excitation Technique (IET). The study demonstrates a strong correlation between the DI and the resonance frequencies of the specimens, suggesting that IET can effectively track damage progression in composite laminates. Bio-based resin laminates exhibited higher energy absorption at perforation and lower damage progression during repeated impacts due to the higher ductility of the resin. This method of using resonance frequencies to assess impact damage progression directly in composite laminates throughout the IET technique has not been previously reported in the literature.

Elastic constant analysis of orthotropic steel sheets using multitask machine learning and the impulse excitation technique

Abstract This work presents a novel multitask learning approach featuring a dual convolutional neural network (CNN) system for determining the elastic constants of orthotropic rolled steel sheets. In the proposed model, resonance frequency spectra from the impulse excitation technique are converted into 2D image data. The first CNN focuses on detecting and predicting missing peak intensities, while the second CNN utilizes features from the entire spectrum image to predict elastic constants, including E11, E22, and G12. The input features include raw pixel data alongside three key categories for enhanced analysis: image-based features (such as the mean, median, mode, and skewness of pixel intensity distributions), spatial relations (including spatial frequency, pixel intensity correlations, and local contrast), and geometric features (such as shape descriptors and pixel connectivity). The results reveal that the optimal number of peaks (14), image resolution (121 pixels), and sample size (20 × 20 × 0.3 cm) maximize the model’s efficiency. Under these conditions, the model achieves R2 values of 0.952, 0.902, and 0.913, and RMSE values of 1.89 GPa, 3.09 GPa, and 1.92 GPa for E11, E22, and G12, respectively. It is suggested that the superior prediction accuracy for E11 is attributed to the stability of the Young’s modulus along the rolling direction, which is less variable in orthotropic materials. Furthermore, the study finds a dependency between input weight functions—including image-based features, spatial relations, and geometric features—as the material’s anisotropy changes, underscoring the importance of accounting for process variability in predictive modeling.

Local elasticity assessment of unidirectional fiber-reinforced polymer composites through impulse excitation and machine learning

This study presents a novel methodology that integrates the Impulse Excitation Technique (IET) and machine learning (ML) to predict local elastic properties within isolated regions of unidirectional polymeric composite plates. The proposed model incorporates fiber volume and plate thickness as input parameters and leverages the first resonance frequencies of the local region at different fiber orientations, thus accounting for the composite’s anisotropy. Regression results from the deep neural network (DNN) model demonstrate robust prediction performance across all output targets in both testing and training datasets, with R2 coefficients surpassing 0.9. The model exhibits particularly strong performance in predicting Young’s moduli. Additionally, each output objective shows sensitivity to a unique balance of input parameter weight factors for achieving optimal ML predictions. Moreover, a parabolic trend in the weight factors of fundamental frequencies at different orientations is observed as the rigidity of composites changes. Lastly, a comparative study between carbon-fiber and glass-fiber composites highlights the variations in fiber volume and elastic constants, emphasizing the effectiveness of the proposed model in accurately predicting material properties.

On the Damping and Fatigue Characterization of Additively Manufactured Ti-6Al-4V

With the recent implementation of additively manufactured parts into industrial applications, there is a dire need for nondestructive evaluation methods to qualify if these components are fit for service due to their sensitivity to processing conditions. The Impulse Excitation Technique (IET) is applied to additively manufactured Ti-6Al-4V bending specimens to determine natural frequencies and damping properties in order to predict fatigue performance relative to specimens fabricated with different processing parameters. From the damping and natural frequency results, it was found that the specimens, fabricated with intentional underheating to induce lack of fusion defects, had the lowest damping value in the pristine condition and the highest natural frequency. For the three batches of specimens tested, it was determined that the lack of fusion specimens had the best fully-reversed bending fatigue performance with the highest fatigue limit (297 MPa) and longest fatigue lives as compared to the other two batches, implying a relation of decreased fatigue life with increased material damping in the pristine condition. The theory of the IET related to materials is presented with damping and fatigue results, as well as microstructural analysis and fractography of three specimens batches fabricated with different processing parameters.

Machine learning-driven detection of anomalies in manufactured parts from resonance frequency signatures

ABSTRACT This study aims to enhance the detection and characterisation of anomalies in manufactured parts by integrating machine learning (ML) with resonance frequency spectra data. A key contribution of this work is the development of a novel Impulse Excitation Technique (IET)-based method that effectively evaluates material health and identifies subtle defects by leveraging numerous mathematical and physical metrics as input features. Three machine learning models – Random Forest (RF), K-Nearest Neighbor (KNN), and Multi-layer Perceptron (MLP) – were systematically compared to determine the most effective method for classifying defects, specifically focusing on healthy, cracked, and dimensionally deviated samples. Among these, the MLP model demonstrated the highest performance, achieving Receiver Operating Characteristic (ROC) values of 0.963, 0.901, and 0.942 for each class, respectively. Additionally, SHAP (SHapley Additive exPlanations) analysis showed anomalies were sensitive to specific resonance frequency metrics, improving prediction accuracy. Cracked samples exhibited slight peak broadening and negative peak shifts, while dimensionally deviated samples showed positive and negative shifts and missing peaks. Dimensional deviations were more pronounced than cracks, making them easier to identify and enhancing predictive accuracy.

New impulse-based test method for early-age elastic modulus measurement in cementitious materials

Accurate monitoring of the elastic modulus evolution during the early-age fluid-solid transition in cementitious materials is crucial for understanding their mechanical behavior under early stresses. While existing methods, such as EMM-ARM, have proven effective, they are often associated with high costs or complex setups. This study presents the development of a low-cost, easy-to-implement system that employs impulse excitation applied to a composite beam, introducing the EMM-IRM method for the effective assessment of the elastic modulus of cement paste from the earliest stages of hydration. The use of impulse excitation is particularly advantageous in low-cost systems with accelerometers of lower sensitivity, as it enhances signal clarity and reduces interference from background noise, thereby improving measurement reliability. The system was validated through experimental comparisons with conventional EMM-ARM, cyclic compression, and traditional impulse excitation techniques, using Portland cement paste as the test material. The results show that EMM-IRM consistently estimates the elastic modulus, with a maximum deviation of 6.33 % from other methods. Moreover, despite its cost-effectiveness, EMM-IRM demonstrates a higher signal-to-noise ratio compared to conventional EMM-ARM. This approach offers a practical solution for early-age characterization of cementitious materials, balancing cost, simplicity, and measurement accuracy.

Factors Influencing Measurement of Dynamic Elastic Modulus from Disk-Shaped Concrete Specimen

The decrease in dynamic elastic modulus is a primary indicator of quantitative damage in concrete. To quantitatively assess depth-by-depth damage within a concrete structure, cylindrical specimens obtained through coring can be cut into disk specimens to measure the dynamic elastic modulus of concrete at each depth. To minimize external damage during coring, it is essential to extract cylinders with the smallest possible diameter. In addition, for higher resolution in depth-based damage assessment, creating disk specimens with the smallest possible thickness is necessary. However, there is no information available in the literature on experimental limitation of smallest possible diameter and thickness for dynamic elastic modulus of disk-shaped specimens. This study evaluated whether the dynamic modulus measured from various sizes of concrete disk specimens provided sufficient reliability compared to reference values obtained from cylinders. Moreover, the study examined how the presence of coarse aggregate and variation in the water–cement ratio significantly influenced the dynamic modulus measurement. In addition, test results from impulse excitation technique (IET) and impact resonance (IR) were compared to find a more reliable test method for dynamic elastic modulus of disk specimen. The experimental findings revealed that as the thickness-to-radius ratio of the disk specimens decreased, measured data variation increased. Mortar specimens without coarse aggregates showed less variability compared to concrete specimens, and the variation in dynamic modulus measured by IR was lower than that measured by IET.

The sound of porosity: Suitability of the impulse excitation technique (IET) to determine the Young's modulus of 2D macroporous ceramics

The presence of pores in a ceramic leads to a lower Young's modulus compared to dense material. For the development of porous ceramics with tailored elastic properties, an exact determination of the Young's modulus is required, especially for industrial applications. Therefore, we investigated the suitability of the non-destructive impulse excitation technique for measuring the dynamic Young's modulus of two-dimensional ceramics with low porosity (P < 19 %). For rectangular samples it was shown that the measurement results depend on the geometric pore position, as added pores outside the nodal lines of the fundamental flexural vibration had no influence on the result. Pores in the inner part of the sample led to a decrease of the Young's modulus that is in good agreement with empirical and analytical models. For the investigated interval of porosity range, the influence of pore size and geometric position on the reduction of the Young's modulus was determined.

A new method for identifying elastic parameters of isotropic materials based on square specimens

This paper proposes a new impulse excitation technique using a square plate. First, the functional relationship between the modal frequency of the specimen and the geometrical dimensions and mechanical parameters was established by using the finite element method. Then, the continuous functional relationship derived by a homotopy method allowed the frequency ratios to be related to the thickness-to-length ratio and Poisson’s ratio. By measuring the frequency ratios and thickness-to-length ratio, Poisson’s ratio could be calculated using this functional relationship. When the density and Poisson’s ratio were known, Young’s modulus could be identified inversely in conjunction with the finite element analysis. Finally, a comparison test between this method and the traditional impulse excitation technique was designed and implemented, and the results showed that this method has advantages in both testing efficiency and accuracy. The study provides a new idea for system identification, which has important application value and promotion significance.

Design and characterization of novel Ti-8Mo-xFe-yCu alloys as implant materials: Evaluation of biocompatibility, mechanical properties, and antibacterial potential

Titanium and its alloys are highly desirable materials for biomedical metallic implants due to their superior specific strength, excellent corrosion resistance, and exceptional biocompatibility. Among these alloys, Ti6Al4V is widely used in practical biomedical applications because it offers an excellent combination of strength, fracture toughness, and corrosion resistance. However, recent research has revealed limitations in its biocompatibility attributed to the presence of toxic elements such as Al and V. In addition, it has been reported that Ti6Al4V is costly due to the addition of Vanadium and has the potential for post-implant inflammation. As a result, researchers have been investigating new biomedical beta-Ti alloys using biocompatible, affordable, and easily accessible beta-stabilizers like Mo, Fe, and Cu, to achieve similar performance as Ti6Al4V alloys. The present study aims to develop a novel biomedical alloy through the arc melting method, to obtain an implant material possessing low elastic moduli, biocompatibility, and antibacterial properties to mitigate the risk of post-implant inflammation. Microstructural analysis was conducted using microscopy and x-ray diffraction, while the mechanical properties were evaluated through micro vickers hardness testing machine and elastic moduli measurement utilizing the impulse excitation technique. Cytotoxicity assessment was performed using the (Cell Counting Kit-8) CCK-8 method, followed by an examination of the alloy's antibacterial properties using the point counting method. β-Ti single phase was obtained in this study with the addition of ≥1% Fe and ≥1% Cu. The Ti-8Mo-2Fe-2Cu alloy was found to have the lowest elastic moduli of 95 GPa. Electrochemical measurements show that the Ti-8Mo- xFe- yCu alloys have a lower corrosion current density of around 0.319–2.317 µA/cm2 compared to Ti6Al4V of 16.543 µA/cm2. The Ti-8Mo-1Fe-3Cu, Ti-8Mo-3Fe-1Cu, and Ti-8Mo-3Fe-3Cu alloys have comparable biocompatibility with Ti6Al4V with the viability of mesenchymal stem cells (MSCs) above 75% and have a positive antibacterial response. Ti-8Mo-3Fe-3Cu alloy demonstrates the most favorable blend of microstructure, mechanical attributes, corrosion resistance, cell viability, and antibacterial properties as an alternate biomaterial for implant applications.

Thermal cycling damage of silica refractories for high-temperature thermal energy storage (HT-TES) – Can it be healed?

Silica refractories are promising materials for high-temperature thermal energy storage (HT-TES), because they exhibit excellent thermal cycling properties, unless cooled below a critical temperature (usually assumed to be 600 °C). When cooling down to room temperature severe damage can occur, which can be conveniently monitored via the impulse excitation technique (IET). This damage is most severe when the cycling maximum temperature is low. The question is whether this damage can be healed again. In this short contribution we show that severe damage in silica refractories, caused by heating from room temperature to 300 °C and back again to room temperature, can indeed be healed by thermal cycling to 1300 °C. The healed material is actually better than the pristine material.

Effective Young’s modulus of highly porous 3D printed mono-material and coaxial structures

The dynamic elastic response of 3D macroporous scaffolds is crucial to determine their performance under operating conditions. In this work, the elastic behaviour of 3D printed bar-shaped scaffolds of γ-Al2O3 and γ-Al2O3/graphene nanoplatelets (GNP) composites (18 vol%), fabricated by Direct Ink Writing (DIW), is investigated. Dynamic Young’s modulus (E) is studied by the Impulse Excitation Technique (IET) and compared with theoretical results obtained by Finite Element Methods (FEM) and the multi-scale material simulator GeoDict®. In addition, Resonant Ultrasound Spectroscopy (RUS) is used to characterize E of single- and bi-material coaxial struts. While additions of GNP to γ-Al2O3 lead to an increase in E, it decreases in the coaxial struts due to the development of thermal residual stresses at the core/shell interface. The suitability of combining experimental and theoretical methods for the analysis of the elastic properties and the anisotropy associated with the lattice pattern is demonstrated.

Decision fusion based on vibrometric data for increase of reliability of damage detection and indentification for plate-like structures

In the realm of structural health monitoring (SHM) for plate-like structures, the need for accurate and reliable damage detection and identification techniques is paramount. This paper explores the application of decision fusion algorithms to vibrometric data, with a focus on increasing the reliability of damage assessment for such structures. The methodology involves leveraging diverse input data sources, including variations in data processing algorithms, excitation parameters, and multiple measurements. By amalgamating these sources of diversity, we aim to mitigate measurement noise and amplify damage indications, ultimately enhancing the precision of the final diagnostic outcome. The study presents results obtained from laser vibrometry measurements on a 10 mm thick aluminum sample containing flat-bottom holes of varying diameters. A network of 12 PZT transducers was used to excite elastic waves, with impulse and chirp excitation techniques employed. Convolution techniques using OpenCV libraries were applied for data processing and fusion. The outcomes reveal a significant reduction in background noise, demonstrating the effectiveness of the fusion approach. Furthermore, the presentation outlines a roadmap for the future development of this methodology, which includes automating data processing, evaluating the impact of damage indicators, processing parameters and usage of different excitation transducers.

Estimating the elastic modulus of concrete under moderately elevated temperatures via impulse excitation technique

PurposeTo evaluate the temperature-dependency of the Young’s and shear moduli of concrete after exposure to moderately elevated temperatures using the non-destructive impulse excitation technique (IET).Design/methodology/approachThe study involved heating the concrete up to 225 °C and measuring the dynamic Young’s and shear moduli using the non-destructive technique of impulse excitation, which measures the natural vibration frequency from a mechanical impulse received by an acoustic sensor. The effects of temperature on the dynamic Young’s and shear moduli were analysed and the importance of the spatial variability of the measured values was also verified.FindingsThe study found that even moderately elevated temperatures (below 225 °C) resulted in a significant permanent reduction in the Young’s modulus of concrete (reduction in the range of 23%–36% for the maximum temperature considered in this research) as well as a modest and permanent reduction in the shear modulus of around 6%. It was also observed that spatial variability of the mechanical properties of concrete plays an important role in the measured values; higher dispersion of the results was found for the values of the Young’s and shear moduli of concrete measured along the height of the beam. The non-destructive test method used in this study was found to be extremely useful in the investigation of heat-related damage in concrete structures for its ease of use, low time consumption and accuracy. The results were consistent with the published literature.Originality/valueThis study provides important insights into the temperature-dependent behaviour of the dynamic Young’s and shear moduli of concrete and highlights the significance of proper consideration of the spatial variability of the measured values. The use of a non-destructive test method for continuous acoustic testing during heating and cooling proved to be effective, and the findings contribute to the fields of materials science and civil engineering in understanding the effects of elevated temperatures on concrete properties. The findings confirm that IET can be easily used to gather important information in the condition assessment and rehabilitation of concrete structures after a fire event. Further studies to foster the application of this technique to real structures are suggested.

Non-destructive degradation assessment of GFRP beams subjected to hygrothermal ageing

This work used free vibration tests based on impulse excitation technique and experimental modal analysis using an impact hammer and an accelerometer to assess the local and global effects of the hygrothermal ageing of GFRP specimens exposed to salt-spray environment at 35°C and 60°C over a period of 136 days. Through the change in elastic properties, fifteen natural frequencies and damping ratios, the effects of degradation are associated with reductions in elastic properties and natural frequencies and an increase in damping ratios. In turn, the increase in elastic properties and natural frequencies – associated with a reduction in damping ratios – is mainly attributed to the post-curing effect.

Cu–Mg dilute alloys- Assessment of strengthening, internal friction, and electrical conductivity

Overcoming the strength-conductivity trade-off has long been an issue for commercial copper alloys. However, a synergy between strength and electrical conductivity can be achieved by reasonable adjustment of the microstructure. It is known that the formation of Short-Range Order (SRO) in a solid solution can change the mechanical and electrical behavior of the materials. Currently, the prediction of SRO formation is widely based on computational techniques. In the present study, Miedema's thermodynamical approach is applied for the assessment of alloying elements' potential to form SRO in the copper lattice. According to this methodology, magnesium tends to form SRO with copper. The mechanical, electrical, and structural properties of the oxygen-free copper (Cu-OFC), Cu–Mg0.14 wt%, and Cu–Mg0.50 wt% strips fabricated by continuous extrusion forming process (Conform) have been investigated. According to the optical microscopy investigations, the average grain sizes of the Mg alloyed samples were observed to be lower compared to that of OFC. The Vickers hardness measurements were carried out and the hardness values for Cu-OFC, Cu–Mg0.14, and Cu–Mg0.50 samples were recorded as 56.3 HV, 76.05 HV, and 87.68 HV, and the yield strengths as 80, 150 and 260 MPa, respectively. A decrement in electrical conductivity was observed with the increasing Mg addition. Dynamic elastic modulus test measurements, which refer to internal friction, have been performed by impulse excitation technique to elucidate the presence of SRO in the dilute Cu–Mg systems. The anomalous “bump” formation in the temperature-elastic modulus profiles of the Cu–Mg samples was remarkable which has been attributed to the SRO formation.

Evolution of Young’s modulus and damping of Czech kaolins during sintering monitored via impulse excitation

The evolution of Young’s modulus and damping is investigated for Czech kaolins in situ via the impulse excitation technique (IET) from room temperature to 1250 and 1400 °C. During heating the processes of drying, dehydroxylation, spinel formation, mullitization, silica release and glass melting are clearly discernible. During cooling Young’s modulus increases, exhibiting a flat maximum around 800 °C and a steep decrease below 200 °C when the cristobalite content is high. Differential IET curves are introduced as a new representation of IET results, and damping curves are shown to provide additional information. The phase composition is determined via XRD, including the glass phase. Based on the densities, Young’s moduli and volume fractions of the individual phases, the densities and Young’s moduli of the kaolin-based ceramics are calculated and compared to theoretical predictions, showing that Young’s modulus is nicely predicted by a benchmark relation for partially sintered ceramics with concave pores.

Enhanced mechanical performance and damping behavior of CFRP composites through exfoliated MWCNT functionalization

In evaluating high-performance multiwall carbon nanotube (MWCNT) based carbon fiber composites, effective chemical functionalization of fillers for sufficient exfoliation and precise interface interactions with resin matrix are challenging to attain due to significant interlayer cohesive energy and inactive surfaces of composites. Herein, we demonstrate an effective way to produce carbon fiber-reinforced polymer (CFRP) composite with amended interfacial characteristics via incorporation of MWCNT through oxidation followed by silane functionalization with their exfoliation levels (0/48/60/72 h). The surface functional elements, morphological changes, elemental groups, quantitative information, and thermal degradation of silane functionalized MWCNTs were characterized by FESEM/HR-TEM, XRD, UV, and TG-DTA analysis, respectively. The influence of silane functionalized MWCNT reinforcement on CFRP's mechanical properties were examined using tensile, flexural, ILSS, and damping behavior was analyzed through impulse excitation technique (IET). The resulting silane-modified MWCNTs with 60 h oxidation (OAC-60) infused CFRP demonstrated significant enhancement in flexural strength (73.8%), tensile strength (58.2%), interlaminar shear strength (28.5%) compared to pure-CFRP.

Polymer Waste Recycling of Injection Molding Purges with Softening for Cutting with Fresnel Solar Collector-A Real Problem Linked to Sustainability and the Circular Economy.

A plastic injection waste known as "purge" cannot be reintegrated into the recycling chain due to its shape, size, and composition. Grinding these cannot be carried out with traditional mills due to significant variations in size and shape. This work proposes a process and the design of a device that operates with solar energy to cut the purges without exceeding the degradation temperature. The size reduction allows reprocessing, revalorization, and handling. The purges are mixtures of processed polymers, so their characterization information is unavailable. Some characterizations were conducted before the design of the process and after the cut of the purges. Some of the most representative purges in a recycling company were evaluated. The flame test determines that all material mixtures retain thermoplasticity. The hardness (Shore D) presented changes in four of the purges being assessed, with results in a range of 59-71 before softening and 60-68 after softening. Young's modulus was analyzed by the impulse excitation technique (IET), which was 2.38-3.95 GPa before softening and 1.7-4.28 after softening. The feasibility of cutting purges at their softening temperature was evaluated. This was achieved in all the purges evaluated at 250-280 °C. FTIR allowed for corroboration of no significant change in the purges after softening. The five types of purges evaluated were polypropylene-ABS, polycarbonate-ABS-polypropylene, yellow nylon 66, acetal, and black nylon 66 with fillers, and all were easily cut at their softening temperature, allowing their manipulation in subsequent process steps.

Delamination Assessment in Composite Laminates through Local Impulse Excitation Technique (IET)

This paper deals with an innovative nondestructive technique for composites (local-IET), which is based on the Impulse Excitation Technique (IET) and, in the presence of damage, assesses the degradation of the elastic properties of a local region of the laminate by reversibly clamping its boundaries. In this paper, a numerical analysis of the sensitivity of the local-IET to the delamination damage mechanism is conducted. Firstly, a Finite Element (FE) model of the local-IET test is determined through experimental investigations on undamaged composite laminates, which cover a wide range and are made of glass or carbon fibers, through resin infusion or pre-preg consolidation and with unidirectional or fabric textures. The vibrational response of a glass fiber composite with local delamination is then assessed with the local-IET. By modeling the delamination in the simulation environment, the effectiveness of the FE model in replicating the vibrational response, even in the presence of delamination, is shown through a comparison with the experimental results. Finally, the FE model is exploited to perform a sensitivity analysis, showing that the technique is able to detect the presence of delamination.