Non-destructive Testing Methods Research Articles

Non-destructive testing method of concrete based on piezoelectric sensor

Abstract This paper reviews the research and development of non-destructive techniques for monitoring concrete in the past. Active detection techniques, particularly Electro-Mechanical Impedance method and Wave Propagation method have been demonstrated to be effective in monitoring the concrete process. Electro-Mechanical Impedance method detects internal structural damage by analyzing the vibration characteristics of the structure by combining a piezoelectric transducer with the system to be measured. Compared to the Electro-Mechanical Impedance method, the fluctuation method uses two or more transducers, with one serving as an exciter to actively excite the signal. In contrast, the others form an array to receive the stress wave signal. This method offers several advantages, including the absence of dependence on an impedance meter and passive excitation, a simple operating principle, high response frequency, and high immunity to interference. In this work, the research status and progress in the field of non-destructive testing (NDT) of concrete are combined to summarize the results and refine the methodology of the research on the evaluation of concrete material properties and identification of structural damage; based on this, the bottlenecks, research difficulties and difficulties in the field are further outlined, and finally, the research outlook of NDT of concrete in response to these limitations is put forward.

Non-destructive testing methods commonly used in aviation

Non-Destructive Testing (NDT) methods play a pivotal role in ensuring the safety and reliability of aircraft in the aviation industry. This article provides a comprehensive overview of the NDT techniques commonly employed in aviation to assess the structural integrity and performance of aircraft components and materials without causing any damage. The article discusses the significance of NDT in aviation, highlighting the importance of early defect detection, maintenance cost reduction, and enhanced operational safety. It delves into various NDT methods, such as ultrasonic testing, eddy current testing, radiographic inspection, magnetic particle testing, and dye penetrant testing, explaining their principles and applications. In addition, in this article, the advantages and disadvantages of NDT methods and which methods are used in which part of the aircraft are mentioned. Understanding these NDT methods is crucial for aviation professionals, as they contribute to the continued airworthiness of aircraft, ensuring that passengers and crew can travel safely and confidently.

Исследование сигнала внешнего магнитного поля асинхронного электродвигателя в режиме выбега

Currently, one of the important scientific tasks is the development and improvement of methods for non-destructive testing of asynchronous electric motors during operation. One of the promising areas of diagnostics is the use of an external magnetic field signal. However, its study in the run-down mode is not given due attention by the authors of scientific publications, despite a number of advantages of this signal. Therefore, the aim of this research is to confirm the possibility to record and study the signal of the radial component of the induction of the external magnetic field in the run-down mode of an asynchronous motor. So, the aim is relevant. The research is carried out using several test benches, real low-voltage and high-voltage asynchronous motors and a simulation model of an asynchronous electric motor designed in the Ansys software package. To process the signals, namely, to construct the frequency-time spectra of the external magnetic field in the run-down mode, the authors have used a program based on the Short Time Fourier Transform using the Flat-top window as a window function to more accurately determine the amplitudes of the harmonic components. During the research conducted on test benches, it has been found that the external magnetic field of the motor in the run-down mode will exist due to the phenomenon of residual magnetization. The possibility of modeling asynchronous motors considering residual magnetization has been proven and the reliability of the resulting model has been confirmed. The spectra of external magnetic field signals on real motors and simulation models in the run-down mode are presented. The external magnetic field signal in the run-down mode can be recorded both on simulation models and on real low-voltage and high-voltage asynchronous electric motors. During further research, it is planned to analyze the possibility of identifying faults in asynchronous motors using this signal.

Stress Wave Propagation in a Rayleigh-Love Rod with Sudden Cross-Sectional Area Variations Impacted by a Striker Rod.

This paper presents an in-depth study of the stress wave behavior propagating in a Rayleigh-Love rod with sudden cross-sectional area variations. The analytical solutions of stress waves are derived for the reflection and transmission propagation behavior at the interface of the cross-sectional area change in the rod, considering inertia and Poisson's effects on the rod material. Examples solved using the finite element method are provided to verify the correctness of the analytical results. Based on the forward analysis of Rayleigh-Love wave propagation in a rod impacted by a striker rod, an impact-echo-type nondestructive testing (NDT) method is proposed to conduct defect assessment in rod-type structural components with sudden cross-sectional area changes within a cover medium. This proposed NDT method can identify the location, extension, and cross-sectional area drop ratios of an irregular zone in the rod to be inspected.

Mechanical Properties and Mesoscopic Numerical Simulation of Local Weakening in High-Performance Concrete after 10 Years of Alkali Solution Immersion

The natural environment in the high-altitude regions of Northwest China is extremely harsh, characterized by numerous salt lakes. The high concentrations of chloride salts, sulfates, and alkali metal ions in these areas can induce alkali–silica reactions (ASRs) in concrete. These reactions generate harmful gel within the concrete, causing expansion and cracking, which significantly impacts the durability of concrete structures. This study investigates the evolution of the mechanical properties in high-performance concrete (HPC) under long-term ASR by incorporating different admixtures and varying the equivalent alkali content. A three-dimensional random aggregate mesoscopic model was used to simulate static compression tests under various operational conditions. Non-destructive testing methods were utilized to determine the expansion rate, internal, and surface damage variables of the concrete. The experimental results indicate that the 10-year expansion rate differs from the 1-year rate by approximately 1%, and under long-term ASR mitigation measures, the internal damage in the HPC is minimal, though the surface damage is more severe. As the equivalent alkali content increases, the compressive strength of the concrete cubes decreases, initially rising before falling by 5–15% over time. The HPC with only air-entraining agent added exhibited better mechanical performance than the HPC with both air-entraining and corrosion inhibitors added, with the poorest performance observed in the HPC with only a corrosion inhibitor. A relationship was established between the surface and internal damage variables, with the surface damage initially increasing rapidly before stabilizing as the internal damage rose. Numerical simulations effectively describe the damage behavior of HPC under static uniaxial compression. Comparisons with actual failure morphologies revealed that, in the cube compression tests, crack propagation directly penetrated both coarse and fine aggregates rather than circumventing them. The simulations closely matched the experimental outcomes, demonstrating their accuracy in modeling experiments. This study discusses the compressive mechanical properties of concrete under prolonged ASR through a combination of experimental and simulation approaches. It also delves into the impact of surface damage on the overall mechanical performance and failure modes of concrete. The findings provide experimental and simulation support for the concrete structures in regions with high alkali contents.

Magneto acoustic emission technique: A review of methodology, applications, and future prospects in non-destructive testing

The magneto acoustic emission (MAE) technique is an emerging non-destructive testing (NDT) method that has shown potential for defect detection in the bulk of material, proven vital for the safety and integrity of the material. The MAE technique has shown promising results among modern non-destructive testing techniques for ferromagnetic materials. Although MAE technique is a long-established NDT method, it has the potential for further development. This paper provides an in-depth review of MAE signals' physical origin and characteristics, compares them with their counterpart, Magneto Barkhausen Noise (MBN), and explores data acquisition methods and applications, including specific case studies in material defect detection. The research gaps in the MAE technique are discussed, and the paper explores potential developments, highlighting future perspectives and possible improvements.

Heat flow density measurement during non-destructive testing

The object of the study is the development of a device capable of accurately and reliably measuring heat flux density in various environments. The development of a heat flux density meter designed for non-destructive analysis of thermal processes in various fields of application is presented. The developed device is intended for evaluating the thermal insulation condition of underground pipelines. The functionality of the heat flow device relies on comparing standard temperature values with experimental ones measured on the soil surface. To ensure accurate and reliable measurement of heat flux density, the basis is a thermoelectric battery converter, which uses the auxiliary wall method. The heat flow density measuring device is constructed in the shape of a restricted cylinder, with one base serving as the working surface, while the second base establishes thermal contact with the body at ambient temperature. Embedded heaters enable the generation of heat flow through the thermoelectric sensor in directions perpendicular to its base. For calibrating the heat flux device, experiments were conducted using a standard copper-constantan calibration table. Temperature increments were determined from thermo electromotive force, and tests were performed on an existing heating network. The conducted measurements validate the fundamental feasibility of employing the proposed device for implementing the non-destructive thermal testing method on underground heating mains. The results of the experiment can be used not only for research, but also for monitoring and regulating processes in various fields of science and technology. The developed heat flux meter promises a significant contribution to the development of modern methods for analyzing thermal processes. The dimensions of the thermoelectric battery converter are also determined and the coefficient (kq) should be in the range from 4.0 to 12.0 W/(m2⋅mV), and the electrical resistance should be in the range of 12–20 kOhm

Defect Detection of Topside Offshore Platform Structure Using Non-Destructive Testing Methods

Non-destructive testing on offshore rigs involves multiple sections. The topside platform structure, which consists of the main deck, cellar, and sub-cellar deck, is one of the most important sections. The purpose of this research is to use appropriate nondestructive testing (NDT) methods to assess the internal and surface defects as well as identify the material properties of the selected structure at the topside platform structure. Various NDT technologies can be utilized to detect faults on the topside of the offshore platform. The NDT techniques used in this study are ultrasonic, magnetic particle, and dye penetrant testing. To describe the material in the samples, a different method known as positive identification material is employed. Four tasks are involved in this process: identifying the material properties of each sample, identifying surface and interior faults, and comparing the two types of defects. The results of the analysis revealed that a 316L stainless steel specimen contained as much as 19.2% chromium, 11.8% nickel, and 3.0% molybdenum. Magnetic particle inspection was recommended for surface and subsurface inspection. In contrast, the ultrasonic testing examination yielded the best outcome for the topside offshore platform's interior problem.

Non-destructive evaluation method for track slabs damaged by impact of ice blocks detached from high-speed trains

In winter snowy or rainy weather, the phenomenon of icing under rolling stock during high-speed operation is significantly severe, posing a potential risk of detachment and impact on track structures due to the presence of ice blocks with substantial mass and velocity. Therefore, it is crucial to develop an efficient method for characterizing and evaluating this impact damage in order to assess the service life of the track. To address this issue, the indoor ice impact tests were conducted on track slab models, and a comprehensive analysis was performed on non-destructive testing data before and after the impact test, including 3D surface morphology assessment, surface hardness and wave velocity measurements. Additionally, in order to verify the effectiveness of the nondestructive testing method, the frozen-thawed and not frozen-thawed track slab models were tested and their results were compared. The experimental results revealed that when impacted by ice blocks at a velocity of 100 m/s, small dimples formed on the surface of track slab models with the maximum depth measured at 0.0694 mm. There was a maximum increase rate in surface hardness amounting to 11.61%, and a maximum decrease rate in wave velocity measuring at 6.52%. Furthermore, the impact damage of the two models has been evaluated, the not frozen-thawed track slab model exhibited minor damage after impact, whereas the frozen-thawed track slab model demonstrated moderate damage in the contact region and minor damage outside of that region. The proposed non-destructive testing method effectively enables assessing the impact damage inflicted upon slab models while providing valuable insights for maintenance and repair strategies related to track slabs.

Study on Rapid Non-Destructive Detection Method of Corn Freshness Based on Hyperspectral Imaging Technology.

(1) Background: To achieve the rapid, non-destructive detection of corn freshness and staleness for better use in the storage, processing and utilization of corn. (2) Methods: In this study, three varieties of corn were subjected to accelerated aging treatment to study the trend in fatty acid values of corn. The study focused on the use of hyperspectral imaging technology to collect information from corn samples with different aging levels. Spectral data were preprocessed by a convolutional smoothing derivative method (SG, SG1, SG2), derivative method (D1, D2), multiple scattering correction (MSC), and standard normal transform (SNV); the characteristic wavelengths were extracted by the competitive adaptive reweighting method (CARS) and successive projection algorithm (SPA); a neural network (BP) and random forest (RF) were utilized to establish a prediction model for the quantification of fatty acid values of corn. And, the distribution of fatty acid values was visualized based on fatty acid values under the corresponding optimal prediction model. (3) Results: With the prolongation of the aging time, all three varieties of corn showed an overall increasing trend. The fatty acid value of corn can be used as the most important index for characterizing the degree of aging of corn. SG2-SPA-RF was the quantitative prediction model for optimal fatty acid values of corn. The model extracted 31 wavelengths, only 12.11% of the total number of wavelengths, where the coefficient of determination RP2 of the test set was 0.9655 and the root mean square error (RMSE) was 3.6255. (4) Conclusions: This study can provide a reliable and effective new method for the rapid non-destructive testing of corn freshness.

Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.

The improper storage of seeds can potentially compromise agricultural productivity, leading to reduced crop yields. Therefore, assessing seed viability before sowing is of paramount importance. Although numerous techniques exist for evaluating seed conditions, this research leveraged hyperspectral imaging (HSI) technology as an innovative, rapid, clean, and precise nondestructive testing method. The study aimed to determine the most effective classification model for watermelon seeds. Initially, purchased watermelon seeds were segregated into two groups: One underwent sterilization in a dehydrator machine at 40°C for 36h, whereas the other batch was stored under favorable conditions. Watermelon seeds' spectral images were captured using an HSI with a charge-coupled device camera ranging from 400 to 1000nm, and the segmented regions of all samples were measured. Preprocessing techniques and wavelength selection methods were applied to manage spectral data workload, followed by the implementation of a support vector machine (SVM) model. The initial hybrid-SVM model achieved a predictive accuracy rate of 100%, with a test set accuracy of 92.33%. Subsequently, an artificial bee colony (ABC) optimization was introduced to enhance model precision. The results indicated that, with kernel parameters (c, g) set at 13.17 and 0.01, respectively, and a runtime of 4.19328s, the training and evaluation of the dataset achieved an accuracy rate of 100%. Hence, it was practical to utilize HSI technology combined with the PCA-ABC-SVM model to detect different watermelon seeds. As a result, these findings introduce a novel technique for accurately forecasting seed viability, intended for use in agricultural industrial multispectral imaging. PRACTICAL APPLICATION: The traditional methods for determining the condition of seeds primarily emphasize aesthetics, rely on subjective assessment, are time-consuming, and require a lot of labor. On the other hand, HSI technology as green technology was employed to alleviate the aforementioned problems. This work significantly contributes to the field of industrial multispectral imaging by enhancing the capacity to discern various types of seeds and agricultural crop products.

Assessment of Special Rubberized Concrete Types Utilizing Portable Non-Destructive Tests

Concrete is the second most common material demanded over the world. Recently, a trending issue is the vast tracking in constructing infrastructure to ensure traffic movement and life quality. Concrete types such as self and rolled compacted concrete offer magical solutions ensuring vast infrastructure and life quality. However, these structures must be assessed using non-destructive testing methods to observe the difference between the concrete types. Several studies have used recycled waste, specifically the crumb rubber extracted from old tires, as a potential replacement for natural aggregate in concrete manufacturing. However, limited research has been devoted to nondestructive testing of produced concrete to further evaluate existing concrete elements containing crumb rubber. This study investigates the self and rolled compacted concrete in comparison with normal ones, in addition to using chopped rubber as recycled materials. This study examines the concrete manufactured destructively by evaluating its compressive, tensile, and flexural strength, in addition to impact resistance, and correlates those results with the non-destructive such as Schmit hammer and Ultrasonic Pulse (UPV) for extended utilization of the concrete produced and data publication. The results showed unique performance and a high potential for data contribution to the extensive utilization of self-compacted rubberized concrete and rolled compacted concrete.

Automated weld defect segmentation from phased array ultrasonic data based on U-net architecture

Ultrasonic inspection is an environmentally friendly and easily deployable nondestructive testing (NDT) method widely used for defect detection of critical components in the industry. Phased array ultrasonic testing (PAUT) is one of the most advanced ultrasonic inspection methods, which gives volume inspection with increased resolution and coverage, improving inspection efficiency. Because of the weld structure echoes and the abstract nature of ultrasound images, especially facing meters and feature-changing weld joints with different thicknesses and welding methods in shipbuilding, the analysis of the PAUT weld data still relies on experienced rater random inspections. Rating complex welded products process is lengthy, costly, and prone to introduce human error during the manual rating but challenges automatic detection. To automatically segment defects in PAUT data, this work shows a combination of PAUT data of ship weld and three-dimensional (3D) U-net architecture. Combining PAUT imaging principles with welding and scan processes, a PAUT volumetric image dataset, including different thicknesses and scan angles, is established. We pioneered the application of 3D U-net architecture to segment defects in PAUT volume data. We found that U-net architecture with two encoding stages will perform better in segmenting defects in PAUT data, and region-based loss mainly improves the accuracy. Furthermore, a lightweight U-net architecture containing skip-connection and residual blocks is proposed with precision and efficiency improvement. The validation results show that the proposed U-net architecture offers a feasible solution to the problem of segmenting defects from PAUT data with a Dice accuracy of 90.9 %. Segmentation results help to locate and measure defects. This method makes locating and sizing defects in PAUT weld data possible within a fraction of a second.

ZOLLINGER LAMELLA VAULT OF EXISTING TIMBER HANGARS IN ŠIBENIK (CASE STUDY) – INITIAL CONDITION ASSESSMENT AND PRELIMINARY ANALYSIS OF GLOBAL STRUCTURAL FEATURES

<p class="KEYWORDS" style="text-align: justify;">A preliminary condition assessment using non-destructive testing methods for determining material quality, has been carried out on three adjacent wooden hangars near Šibenik with the aim of exploring the possibilities of their repurposing. Through visual inspection and detailed geometric measurements, it has been verified that their unique structure embodies the original Zollinger lamella vault system in which the joint typology is decisive for both, the overarching structural analysis and the execution of the structure. In this paper, the results of conducted investigation, including the developed detailed geometric model are presented, and guidelines for future comprehensive research focusing on the influence of joint stiffness on global structural features are discussed, as well.</p>

Strain analysis and non-destructive monitoring of the two-stage hydraulic-driven piston compressor for hydrogen storage

High-pressure gas storage is an important means of hydrogen application in the transportation industry, especially in hydrogen refuelling stations. The hydrogen compressor is the most crucial dynamic component for high-pressure gas storage in hydrogen refuelling stations. An effective control system is required to guarantee the compressor operates safely and efficiently, which is based on the safe and efficient monitoring of the operating condition of the compressor. However, significantly limited literature has been provided for the hydraulic-driven piston compressor. In this paper, a non-destructive testing method for monitoring the dynamic pressure by strain gauge in the hydraulic-driven piston compressor is proposed. The relationship between the strain of the cylinder head and key operating parameters is obtained through finite element analysis, based on which the optimal location for the pressure monitoring is identified. The proposed non-destructive testing method is validated by experiments of a two-stage hydraulic-driven piston compressor. The strain analysis indicates that the circumferential strain in the cylinder head has a good linear relationship with the in-cylinder gas pressure with a value above 99.6 %. The deformation of the four monitoring positions is almost unchanged with a maximum deviation of 0.5 % under different piston positions. A high uniformity of the circumferential strain of the cylinder head is observed from the analysis. Experimental results indicate that the proposed non-destructive monitoring method is effective in obtaining the dynamic pressure in-cylinder during the compressor operation with a maximum deviation of 5.13 % and an average deviation below 2.01 %.

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.

Evaluation of Structural Stability of Four-Storied building using Non-Destructive Testing Techniques

This paper mainly dealt with the evaluation of the structural stability of four storied building using non-destructive on-destructive testing methods. During the construction stage, there are many tests available to assess the excellence of concrete. The quality of concrete mainly depends on the quality of materials, concrete grade, and water-cement ratio. In the case of existing structures, to check the quality of concrete destructive tests are not possible, meanwhile, concrete quality will be assessed by using non-destructive testing (NDT) techniques such as rebound hammer, ultrasonic pulse velocity (UPV) etc. In this present study, an attempt has been made to check the quality of concrete in an existing four-storied building using non-destructive testing methods such as rebound hammer test and ultrasonic pulse velocity test. Moreover, the stability of the structure was also assessed. Non-destructive testing method was chosen since existing information of the structure was unavailable. Test results showed that the basement (B1) was susceptible to corrosion, and the compressive strength was not in the recommended range. Ultrasonic pulse velocity (UPV) results also proved that the average quality of the concrete was poor. Hence, significant suggestions were given for necessary retrofitting measures to improve the stability of the structure.

A Transformer-based neural network for automatic delamination characterization of quartz fiber-reinforced polymer curved structure using improved THz-TDS

Quartz fiber-reinforced polymer (QFRP) is a vital non-polar material used in aviation wave-transparent structural components. Automatic characterization of delamination defects in QFRP is critical to aviation structural component safety. Terahertz time-domain spectroscopy (THz-TDS) is one of the new non-destructive testing (NDT) methods with highly accurate characterization of internal defects in non-polar material. Hence, attempts to extract features of THz time-domain signals for automatic characterization have been made by using deep learning algorithms. In this work, a Transformer-based neural network to classify the THz time-domain signals collected from a QFRP curved structure for automatic characterization of pre-embedded delamination defects has been reported. A THz-TDS system combined with a collaborative robot for collecting the THz signals from QFRP curved structure has been built. An automatic characterization method framework is developed. Results show that the precision rates of Transformer-based neural network for 1st delamination to 5th delamination are 1.0, 1.0, 1.0, 0.985, 1.0, and F1 score of it is 0.982. During the process of testing, delamination defects inside the QFRP curved structure were visualized using pixels with different colors. Results indicate that the Transformer-based neural network can characterize all pre-embedded delamination defects while minimizing false identification of non-defective areas, performing outstanding generalization.

Advancements in 3D Printing: Directed Energy Deposition Techniques, Defect Analysis, and Quality Monitoring

This paper provides a comprehensive analysis of recent advancements in additive manufacturing, a transformative approach to industrial production that allows for the layer-by-layer construction of complex parts directly from digital models. Focusing specifically on Directed Energy Deposition, it begins by clarifying the fundamental principles of metal additive manufacturing as defined by International Organization of Standardization and American Society for Testing and Materials standards, with an emphasis on laser- and powder-based methods that are pivotal to Directed Energy Deposition. It explores the critical process mechanisms that can lead to defect formation in the manufactured parts, offering in-depth insights into the factors that influence these outcomes. Additionally, the unique mechanisms of defect formation inherent to Directed Energy Deposition are examined in detail. The review also covers the current landscape of process evaluation and non-destructive testing methods essential for quality assurance, including both traditional and contemporary in situ monitoring techniques, with a particular focus given to advanced machine-vision-based methods for geometric analysis. Furthermore, the integration of process monitoring, multiphysics simulation models, and data analytics is discussed, charting a forward-looking roadmap for the development of Digital Twins in Laser–Powder-based Directed Energy Deposition. Finally, this review highlights critical research gaps and proposes directions for future research to enhance the accuracy and efficiency of Directed Energy Deposition systems.

Application of non-destructive testing methods for assessing fracture resistance in dental ceramics: the sound harvesting test

IntroductionEvaluating the fracture resistance of dental ceramics such as monolithic zirconia crowns is crucial for assessing their durability. Conventional destructive laboratory tests often fail to accurately evaluate the timing and failing crack formation of these brittle materials. Non-destructive testing methods, such as acoustic emission testing (AET), offers an alternative by providing valuable data on material properties without causing damage to the samples.The in vitro study aimed to evaluate the sensitivity of a sound harvesting modified acoustic emission testing by comparing the fracture resistance of posterior monolithic zirconia crowns (MZCs) measured via the modified set up with that of a conventional fracture toughness test.Material and methodsA modified acoustic emission set up, the sound harvesting test (SHT), featuring a condenser microphone, an amplifier, a custom audio chipset and a cut-off switch integrated into a universal testing machine, was compared to a conventional fracture toughness test to measure fracture loads on 50 posterior monolithic zirconia crowns divided in two groups.ResultsThe sound harvesting test recorded a mean fracture load of 1,108.99 N, significantly less than the 1,292.52 N measured with the conventional test, indicating a more sensitive detection of fractures. Statistically significant differences (p < 0.05) were observed between the two groups.ConclusionDespite its limitations, the study suggests considering sound harvesting testing as an potential alternative for fracture load testing of dental brittle materials due to its ability to identify failures at lower loads enhancing therefore a more accurate evaluation of the behavior of dental materials. However, further testing on a broader range of dental materials is warranted to improve result accuracy and applicability.