Non-destructive Testing Methods Research Articles

Detection of air- and water-filled cavities beneath concrete plate using electromagnetic and acoustic waves

Underground excavation and tunneling may result in cavities filled with air or water. This study aims to detect cavities beneath underground concrete walls or tunnel linings and assess their risks by estimating the cavity thickness and width using electromagnetic and acoustic waves. In this study, air- and water-filled cavities are simulated, and nondestructive testing methods such as ground penetrating radar (GPR), time domain reflectometry (TDR), and microphones are used to investigate the thickness and width of a cavity beneath a reinforced concrete plate. The results show that GPR signals converted from temporal to spatial scales, combined with TDR measurements, can be used to accurately examine the cavity thickness. However, the examination of the cavity width based on GPR signals remains challenging because of the strong parabolic patterns caused by steel bars. Therefore, this study employs flexibility, which is the ratio of the particle velocity of the structure to the load signal according to the frequency. The flexibility of the concrete plate calculated using microphone signals increases in the cavity section for both air- and water-filled cavities because the flexural vibration mode prevails at the cavity–concrete plate interface. The characteristics of the microphone signals analyzed in the context of flexibility enabled the prediction of the cavity width beneath the concrete plate in both air- and water-filled cavities. GPR and TDR signatures combined with microphone signals can be used for the detection and risk assessment of cavities beneath underground structures when subjected to variations in the groundwater level.

Destructive and non-destructive testings of 304 austenitic stainless steel produced by investment casting method

ABSTRACT In this study, the properties and structures of 304 austenitic stainless steels produced by investment casting methods and stages through destructive and non-destructive (NDT) testing methods are examined. First, the model mould was created from recycled wax containing 5–25% water, 15–35% filler and 0.5% ceramic for the production of a water pipe armature by investment casting method. Then, the ceramic coated mould was sintered at 1350°C, and 304 austenitic stainless steel was melted in the induction furnace at 1150°C at a speed of 1.36 kg/min and poured into this mould. The hardness value of the 304 austenitic stainless steel water pipe armature was obtained as 86.16 HRB and the tensile strength value was 518.76 MPa. As a result of examination with an optical metal microscope, ferrite and austenite structures were observed. Linear and round defects were detected in the liquid penetrant test, and third level (RT-3) shrinkage-delta defects were detected in the radiography test. These results showed that the armature part was acceptable in terms of mechanical strength, corrosion and leakage.

Concrete acoustic emission signal augmentation method based on generative adversarial networks

With the development of concrete structure health monitoring (SHM), the utilization of acoustic emission (AE) as an effective non-destructive testing method has attracted increasing attention among researchers. However, the acquisition of concrete AE signals in real-world scenarios is often limited, which poses challenges to the training as well as the practical application of deep learning (DL) models. To address this problem, a concrete acoustic emission signal augmentation method based on generative adversarial networks (GAN) is proposed in this paper. This method features a unique architecture where both the generator and discriminator are built upon a Bidirectional Long Short-Term Memory (BiLSTM) network. Additionally, the generator integrates an attention mechanism between the BiLSTM layers, enhancing its ability to capture the temporal dynamics of AE signals. To improve the local details of the generated signals, a temporal difference mean square error (TD-MSE) regularization is incorporated into the loss function. Experimental results demonstrate that the method not only substantially increases the amount of data available but also significantly enhances the model’s generalization capabilities and classification accuracy.

Ultrasonic resonance evaluation method for deep interfacial debonding defects of multilayer adhesive bonded materials

Abstract Multilayer adhesive bonded structures/materials (MABS) are widely used as structural components, especially in the field of aerospace. However, for MABS workpieces, the facts that the weak echo of the deep interfacial debonding defects (DB) caused by the large acoustic attenuation coefficient of each layer and this echo, which generally aliases with the excitation wave and the backwall echo of the surface layer, pose a great challenge for the conventional longitudinal wave ultrasonic nondestructive testing methods. In this work, an ultrasonic resonance evaluation method for deep interfacial DBs of MABS is proposed based on the ultrasonic resonance theory and the aliasing effect of ultrasonic waves in MABS. Theoretical and simulation analysis show that the optimal inspection frequency for II-interfacial DBs is 500 kHz when the shell thickness is 1.5 mm and the ethylene propylene diene monomer (EPDM) thickness is 1.5 mm, and the optimal inspection frequency is 250 kHz when the shell thickness is 1.5 or 2.0 mm and the EPDM thickness is 2.0 mm. Verification experiments show that the presence of a DB in the II-interface causes a resonance effect, and in the same inspection configuration, the larger the defect size, the more pronounced this effect is. This resonance effect manifests itself as an increase in the amplitude and an increase in the vibration time of the A-scan signal as well as a pronounced change in the frequency of the received ultrasonic wave. In addition, the increase in the excitation voltage further highlights the ultrasonic resonance effect. Four imaging methods – the integrations of the signal and the signal envelope curve, the maximum amplitude of the fast Fourier transform (FFT) of the signal, and the signal energy – were used for C-scan imaging of ultrasonic resonance evaluation of MABS’s deep interfacial DBs and all these methods can clearly show the sizes and locations of the artificial defects and internal natural defect. The normalized C-scan imaging method proposed in this study can further highlight the weak changes in the signals in the C-scan image. The research results of this study have laid a solid theoretical and practical foundation for the ultrasonic resonance evaluation of MABS.

Methods of determining internal damage in power transformers

Due to the variety of defects that arise in electrical machines, it is necessary to use more effective methods for monitoring their condition. All over the world research and development of new means and methods for monitoring powerful electrical machines during their operation is underway. Some examples of recent advances are vibration diagnostic methods for assessing the compaction of components inside a transformer, acoustic and electrical systems for monitoring partial discharges, data processing using digital methods, and new sensors for continuous monitoring of gases and moisture in oil, as well as hot spot temperatures. Additionally, thermal imaging testing of power equipment is also an important tool to ensure reliable operation. It is believed that the most effective method is gas chromatographic oil analysis, which can identify most defects in oil-filled equipment. During the operation of powerful electrical machines, the use of existing non-destructive testing methods does not allow a complete assessment of the condition of the main parts of the equipment, as an analysis of damage locations shows, 25% are damage to the core and windings. Effective monitoring of the condition and determination of the performance of transformers is of particular importance, since they are key elements in the operation of nuclear power plants. The paper considers the possibility of using the eddy current testing method; determining a defect in magnetic core steel is based on fixing the unevenness of the magnetic field on the horizontal or vertical planes of a yoke or rod consisting of electrical steel plates. Monitoring and evaluating the functioning of existing equipment, detecting deficiencies in the early stages of their development, when repair costs are still minimal, and preventing emergency failures become a priority. In accordance with the growth rate of detected deficiencies, monitoring is carried out from time to time or continuously, the maximum number of monitored characteristics is achieved when the transformer is fully tested to determine its functionality.

Imaging tree root systems using ground penetrating radar (GPR) data in Brazil

Trees sequester carbon dioxide from the atmosphere through photosynthesis, storing it in branches, stems, and roots, where the belowground carbon fraction, approximately ¼ of the total amount, exhibits significant interspecies root biomass variability. Estimating the amount of carbon stored in tree roots of different species is key to understanding an important aspect of climate change and exploring how natural forests, urban tree planting policies, and reforestation projects might help to address it. In this context, one of the most prominent Non-Destructive Testing methods capable of estimating the diameter and length of roots at different depths is ground penetrating radar (GPR). It has been widely used for geological, archaeological, and geotechnical studies due to its accuracy in locating buried material in different contexts, although standards for the correct management of datasets related to belowground root systems are still been developed. This paper reports a GPR signal processing flow to estimate the root diameter of three species of tropical forest trees, and to demonstrate the method’s viability, a dataset was collected in a study area with a 900 MHz shielded antenna. A multi-stage data processing flow is then presented, including raw data, file format conversion, zero-time adjustment, background removal, signal gain, Stolt FK migration, and time-to-depth conversion with hyperbolic adjustment velocity. The resulting data were converted from true amplitude data to a trace envelope. High amplitudes on the envelope section, with lateral continuity in parallel sections, were interpreted as roots. However, the interpretation of outcomes encounters notable complexities, primarily attributable to the intricate nature of subsurface root architectures, the soil matrix characterized by significant clay content, and the co-occurrence of buried materials proximate to the arboreal subjects. Consequently, amplitudes discerned within ground penetrating radar (GPR) 2D sections necessitate cautious interpretation, as they are not immediately indicative of subsurface roots. To overcome this difficulty, this study used direct measurements of the roots in the field, to confirm the GPR data. Despite these complexities, the study demonstrates GPR’s efficacy, particularly in the uppermost soil layer-a pivotal carbon reservoir with a 96% correlation (R2) between GPR-derived coarse-root diameter estimates and field measurements.

WATER PERMEABILITY OF CONCRETE TESTING INSTRUMENT

Instrument we mentioned for checking water permeability in concrete sounds super cool! It's designed with advanced technology and non-destructive testing methods to accurately evaluate how resistant concrete is to water. The instrument has End Cap Set , Booster Pump , Pressure Guage , Pressure Cutoff Switch. Making it comprehensive and efficient for testing. And the best part? It provides real-time measurements and immediate results, saving time and improving accuracy. Plus, it's non-destructive, so it's safe for evaluating concrete structures already in use. This instrument has the potential to revolutionize the construction industry and help engineers, researchers, and construction professionals make informed decisions for more durable concrete structures. Key Words: (Water permeability , Concrete , Durability ,testing methods , booster pump, pressure cut of switch , end cap set , pressure Guage)

The Magnitude and Impact of Food Allergens and the Potential of AI-Based Non-Destructive Testing Methods in Their Detection and Quantification.

Reaction to food allergens is on the increase and so is the attending cost on consumers, the food industry, and society at large. According to FDA, the "big-eight" allergens found in foods include wheat (gluten), peanuts, egg, shellfish, milk, tree nuts, fish, and soybeans. Sesame was added to the list in 2023, making the target allergen list nine instead of eight. These allergenic foods are major ingredients in many food products that can cause severe reactions in those allergic to them if found at a dose that can elicit a reaction. Defining the level of contamination that can elicit sensitivity is a work in progress. The first step in preventing an allergic reaction is reliable detection, then an effective quantification method. These are critical steps in keeping contaminated foods out of the supply chain of foods with allergen-free labels. The conventional methods of chemical assay, DNA-PCR, and enzyme protocols like enzyme-linked immunosorbent assay are effective in allergen detection but slow in providing a response. Most of these methods are incapable of quantifying the level of allergen contamination. There are emerging non-destructive methods that combine the power of sensors and machine learning to provide reliable detection and quantification. This review paper highlights some of the critical information on the types of prevalent food allergens, the mechanism of an allergic reaction in humans, the measure of allergenic sensitivity and eliciting doses, and the conventional and emerging AI-based methods of detection and quantification-the merits and downsides of each type.

Insight into the early hydration characteristics of Portland cement with hydroxyethyl methyl cellulose highlighted by 1H low-field NMR

1H low-field nuclear magnetic resonance (1H NMR) as a non-destructive test method can effectively capture the water state changes in cement pastes. The water changes can in turn reflect the early hydration characteristics of cement pastes. Hydroxyethyl methyl cellulose (HEMC) with different viscosities affects the hydration characteristics of cement by acting on the water in different states. The following experimental results are obtained by testing hydration of cement pastes with HEMC by using 1H NMR test. Incorporating 0.1–3% HEMC with different viscosities all can effectively control the bleeding water phenomenon. HEMC can absorb a part of the water in the cement pastes. Incorporating 2–3% HEMC significantly delays the enrichment of the gel pores water and interlayer water. When the content of HEMC increases from 0% to 3%, the hydration degree of cement pastes tends to decrease. Besides, HEMC with higher viscosity of 15000–40000 mPa·s obviously delays the hydration process of cement pastes compared to HEMC with lower viscosity of 400 mPa·s.

Inspecting epoxy layer defects in steel-epoxy-steel sandwich structures using guided waves

Steel-epoxy sleeves are widely used in the repair of pipelines. The integrity of the epoxy layer between the sleeve and pipeline directly determines the repair quality. However, there is a lack of effective nondestructive testing methods for inspecting the integrity of the epoxy layer. In this work, a guided wave-based inspection method is developed to detect the defects of the epoxy layer in the steel-epoxy-steel sandwich structure. Firstly, the dispersion characteristics of guided waves in the sandwich are analyzed. Two wave modes (ASH1 and SSH0) are selected for defect detection. Then, piezoelectric transducers are designed to excite and receive ASH1 and SSH0 waves. The sensitivities of the two waves to defects are further explored by simulations and experiments. Results indicate that the SSH0 wave can detect defects in the adhesive layer, while the ASH1 wave presents difficulties. This work can provide a feasible way to detect epoxy defects in steel-epoxy-steel sandwich structures.

Analysis of the effect of the direction of reinforcement of a fibrous composite material on the inhomogeneity of localization of deformations and stresses using the method of thermoelastic response

The purpose of the article is to study the effect of the direction of reinforcement of a composite material relative to the cyclic load on the inhomogeneity of stress distribution by the thermal method of non-destructive testing using the thermoelastic effect. This method is widely used in all industries for the control of structural elements and in research work. The degree of stress inhomogeneity is used when choosing the safety factors necessary to ensure the safety of technical objects. In this study, the thermoelastic effect is used to show the possibility of estimating the local distribution of stresses using the temperature field of the test object, proceeding from the linear relation between the temperature of the elastic body and mechanical stresses. The results of studying composite laminates (fibrous filler (fiberglass) with an epoxy matrix) with different laying of fibers with respect to the direction of loading are presented. Four laminate samples were considered: single-layer [0] and [90], three-layer [0]3 and [90]3. Statistical data and estimates of the coefficients of variation, methods of clustering and averaging over the length of the laminates the values of the temperature distribution over the surface of the laminates. The numerical characteristics of the distribution of local temperatures are obtained. It is shown that a more uniform distribution occurs when reinforcing is directed along the direction of the material loading. The integral and local characteristics of the temperature distribution in the samples are compared. The differences in the local temperature distribution depending on the laminate thickness were noted visually for single-layer and three-layer samples. A more uniform distribution of the load is also observed in the direction of reinforcement and with an increase in the number of reinforcement layers. The results obtained lead to the conclusion that the choice of the value of the safety factor, which evaluates the level of stress inhomogeneity, depends on the design features of the laminates. During operation of products made of composite materials in the presence of significant accumulated damage, when the uneven distribution of stresses increases, the levels of safety factors should be adjusted.

Review of Ground Penetrating Radar Applications for Bridge Infrastructures

Infrastructure bridges play a crucial role in fostering economic and social development. However, the adverse effects of natural hazard and weather degradation, coupled with escalating rates of traffic, pose a significant threat. The resultant strain on the structure can lead to undue stress, elevating the risk of a critical asset failure. Hence, non-destructive testing (NDT) has become indispensable in the surveillance of bridge infrastructure. Its primary objectives include ensuring safety, optimizing structural integrity, minimizing repair costs, and extending the lifespan of bridges. NDT techniques can be applied to both existing and newly constructed bridge structures. However, it is crucial to recognize that each NDT method comes with its own set of advantages and limitations tailored to specific tasks. No single method can provide an effective and unequivocal diagnosis on its own. Among the various NDT methods, Ground Penetrating Radar (GPR) has emerged as one of the most widely employed techniques for monitoring bridges. In fact, recent technical regulations now mandate the use of GPR for bridge monitoring and characterization, underscoring its significance in ensuring the structural health and longevity of these critical infrastructures. Ground Penetrating Radar (GPR) stands out as one of the most highly recommended non-destructive methods, offering an efficient and timely assessment of the structural conditions of infrastructure. Recognizing the pivotal role of non-destructive testing (NDT) in this context, this paper aims to elucidate recent scientific endeavors related to the application of GPR in bridge engineering structures. The exploration will commence with a focus on studies conducted both at the model level within laboratory settings and on real cases. Subsequently, the discussion will extend to encompass the characterization and monitoring of the bridge’s main elements: slab, beam, and pillar. By delving into these scientific experiences, this paper intends to provide valuable insights into the efficacy and applicability of GPR in assessing and ensuring the structural integrity of bridges. This paper provides a concise survey of the existing literature on the application of Ground Penetrating Radar (GPR) in the assessment of bridges and viaducts constructed with masonry and reinforced concrete, taking into account papers of journal articles and proceedings available on open databases. Various approaches employed in both laboratory and field settings will be explored and juxtaposed. Additionally, this paper delves into discussions on novel processing and visualization approaches, shedding light on advancements in techniques for interpreting GPR data in the context of bridge and viaduct evaluations.

Investigation of the influence of pre-crack number on acoustic emission characterization of red-sandstone short-term creep damage and failure precursors

Rock crack is one of the main factors responsible for rock failure. Uniaxial compression creep tests are performed using acoustic emission techniques, a high-sensitivity, non-radiative, non-destructive testing method to understand the influence of crack number on the precursor characteristics of short-term creep damage in the fractured rock mass. Based on the Grassberger-Procaccia (G-P) algorithm, the calculation step size for the correlation dimension value (D 2) of the acoustic emission ringing count rate is consistent with that for the acoustic emission b-value. The influence of the number of pre-cracks on the Acoustic emission precursor characteristics of red sandstone creep is analyzed. The results show that near the destabilization of the specimen, the Acoustic emission accumulative ringing count surges in a stepwise manner, the Acoustic emission b-value decreases, the D 2-value increases, the Acoustic emission amplitude shows high intensity and high frequency, and the ringing count increases sharply, all with the characteristics of failure precursors. During the accelerated creep stage of the specimens, with the increase of pre-cracks number, the precursory time points of acoustic emission b-value and D 2-value advance, and their acoustic emission ringing counts increase sharply.

Image and audio characterization of electromagnetic signals in cable defect detection

Power cables play a very important role in urban development. On the other hand, the integrity and the safe operation of power cables are crucial as even a minor potential mishap can result in serious loss of life and property. Hence, early diagnosis and warning of cable faults are imperative. Addressing the current lack of practical detection technologies, this study proposes a non-destructive testing method based on electromagnetic field principles. Through scanning the power-on power cables with probes, the electric field intensity around the cables can be measured, and the weak anomaly caused by structural and material defects can be detected using Superlets transformation. Additionally, to gain a better characterization of the faults, a digital post-processing approach consisting of imaging and sonification algorithms is developed to aid in pinpointing the location of the faults. Both numerical simulation and experimental test indicate that the proposed non-destructive detection method is feasible and can achieve good accuracy in locating cable faults. With image and audio characterization, the present method has great potential applications in ensuring the safety of power cables.

Non-contact detection of the interfacial microdefects in metal/CFRP hybrid composites using air-coupled laser ultrasound

Metal/CFRP (carbon fiber reinforced plastic) hybrid composites are crucial in aerospace applications, demanding non-contact, high-resolution inspection. Traditional non-destructive testing methods face daunting technical challenges due to varying densities and impedance between fiber and metal layers. Here, a hybrid air-coupled laser-ultrasound (ACLU) system was presented for non-contact detection of internal microdefects on the non-homogeneous metal/CFRP interface. The near-surface resolution of the system can reach as high as 80 µm on a long effective working distance of 50 mm. Three types of experiments, specifically ACLU, phased-array, and X-ray inspection, were performed in Al/CFRP composites with the interfacial microdefects located in Al, bonded, and CFRP layers respectively. Comparing with traditional methods, the proposed ACLU system can detect the microdefects of bonding failure, cohesive failure, and delamination at the Al/CFRP interface with higher contrast, resolution, and sensitivity. A significant advantage of the ACLU system is its ability to detect defects on curved surface structure materials, making it highly versatile for various composite configurations. Our eventual goal is to offer an affordable non-contact laser-ultrasound approach for quality and damage inspection of metal/CFRP hybrid composites.

Study on Early Age Concrete’s Compressive Strengths in Unmanaged Curing Condition Using IoT-Based Maturity Monitoring

Although accurately estimating the early age compressive strength of concrete is essential for the timely removal of formwork and the advancement of construction processes, it is challenging to estimate it in cool, cold, hot, or unmanaged conditions. Various nondestructive testing methods, including recent IoT-based techniques, have been proposed to determine the compressive strength of concrete. This study evaluates the maturity method using the wireless thermocouple sensor in assessing the early age compressive strength of concrete slabs, particularly those not subjected to watering and protection in a cool environment below 20 °C. For this purpose, wire and wireless thermocouple sensors were installed in reinforced concrete (RC) slabs, whereas wire thermocouple sensors were installed in concrete cylinders. In addition, the compressive strengths of standard-cured cylinders, field-cured cylinders, and core samples extracted from the RC slab were measured. On day 7, the maturity index (M) values for the field-cured cylinders were 7% lower than those of the standard-cured cylinders, and the M values for the RC slabs with wire and wireless sensors were 6% lower. The compressive strengths of the field-cured cylinders and core samples extracted from the RC slabs were 19% and 14% lower than those of the standard-cured cylinders, respectively. Thus, while the difference in M values was 6–7%, the difference in compressive strength was significantly higher, at 14–19%. In a cool environment without watering or protection, the difference in strength can be even greater. Consequently, a commercial IoT-based thermocouple sensor can replace conventional wire sensors and adopt to estimate early age compressive strength of concrete in unmanaged curing condition.

Virus detection light diffraction fingerprints for biological applications.

The transmission of viral diseases is highly unstable and highly contagious. As the carrier of virus transmission, cell is an important factor to explore the mechanism of virus transmission and disease. However, there is still a lack of effective means to continuously monitor the process of viral infection in cells, and there is no rapid, high-throughput method to assess the status of viral infection. On the basis of the virus light diffraction fingerprint of cells, we applied the gray co-occurrence matrix, set the two parameters effectively to distinguish the virus status and infection time of cells, and visualized the virus infection process of cells in high throughput. We provide an efficient and nondestructive testing method for the selection of excellent livestock and poultry breeds at the cellular level. Meanwhile, our work provides detection methods for the recessive transmission of human-to-human, animal-to-animal, and zoonotic diseases and to inhibit and block their further development.

Research Status and Progress on Non-Destructive Testing Methods for Defect Inspection of Micro-Electronic Packaging

Abstract In a highly competitive and demanding micro-electronics market, non-destructive testing (NDT) technology has been widely applied to defect detection and evaluation of micro-electronic packaging. However, the trend of micro-electronic packaging toward miniaturization, high-density, ultrathin, ultralight, and with small chip footprint, poses an urgent demand for novel NDT methods with high-resolution and large penetration depth, which is utilized for internal defect detection and identification of advanced complicated packages. The conventional NDT methods for micro-electronic packaging mainly include optical visual inspection, X-ray inspection, active infrared thermography, scanning acoustic microscopy (SAM), atomic force microscopy (AFM), laser Doppler vibration measuring technique, scanning SQUID microscopy (SSM), electrical impedance spectroscopy, scanning electron microscope (SEM), and so on. This paper aims to provide a review of addressing their basic principles, advantages, limitations, and application researches in the field of defect inspection of micro-electronic packaging. Moreover, in order to overcome the shortcomings of the existing NDT methods, this paper emphasizes a novel NDT approach, called hybrid ultrasonic-laser digital holographic microscopy (DHM) imaging inspection method, and discusses its basic principle, merits, key techniques, system construction, and experimental results in detail. When some key technical problems can be solved in further research, this method will become a potentially promising technique for defect detection and evaluation of advanced complicated packages.

Detection and quantification of corrosion defects in CFRP-strengthened steel structures based on low-power vibrothermography

ABSTRACT For CFRP-strengthened steel structures, corrosion defects in steel are incredibly hazardous, but there is a lack of effective non-destructive testing methods. Based on the low-power vibrothermography (LVT) technique, this study proposes a quantitative detection framework for corrosion defects of CFRP-strengthened steel structures, including feature extraction algorithms for improving the defect detectability, and a feature enhancement method for reducing the quantification error. First, a finite element model is built to simulate the heat generation under ultrasonic excitation and to obtain the temperature distribution on the specimen surface. The processing results of the simulated thermal images show that feature extraction algorithms (FFT, PCA, and PLSR) effectively extract defect features. Subsequently, the LVT experimental setup was established to detect corrosion defects in CFRP-strengthened steel specimens. The experimental results demonstrate that the LVT technique can selectively heat corrosion defects, and processing results prove that the FFT and PLSR can further enhance the defect detectability. Finally, we propose a feature enhancement method based on gravitational calculation and double-threshold segmentation to reduces the quantification error. The quantitative evaluation relative errors of defects with diameters of 10 mm, 8 mm, and 6 mm are 5.26%, 5.26%, and 10.09%, respectively.

Non-Destructive Detection of Golden Passion Fruit Quality Based on Dielectric Characteristics

This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit’s electrical characteristics. By using dielectric properties, the method accurately predicted the soluble solids content (SSC), Acidity and pulp percentage (PP) in passion fruit. The investigation entailed measuring the relative dielectric constant (ε′) and dielectric loss factor (ε″) for 192 samples across a spectrum of 34 frequencies from 0.05 to 100 kHz. The analysis revealed that with increasing frequency and fruit maturity, both ε′ and ε″ showed a declining trend. Moreover, there was a discernible correlation between the fruit’s physicochemical indicators and dielectric properties. In refining the dataset, 12 outliers were removed using the Local Outlier Factor (LOF) algorithm. The study employed various advanced feature extraction techniques, including Recursive Feature Elimination with Cross-Validation (RFECV), Permutation Importance based on Random Forest Regression (PI-RF), Permutation Importance based on Linear Regression (PI-LR) and Genetic Algorithm (GA). All the variables and the selected variables after screening were used as inputs to build Extreme Gradient Boosting (XGBoost) and Categorical Boosting (Cat-Boost) models to predict the SSC, Acidity and PP in passion fruit. The results indicate that the PI-RF-XGBoost model demonstrated superior performance in predicting both the SSC (R2 = 0.9240, RMSE = 0.2595) and the PP (R2 = 0.9092, RMSE = 0.0014) of passion fruit. Meanwhile, the GA-CatBoost model exhibited the best performance in predicting Acidity (R2 = 0.9471, RMSE = 0.1237). In addition, for the well-performing algorithms, the selected features are mainly concentrated within the frequency range of 0.05–6 kHz, which is consistent with the frequency range highly correlated with the dielectric properties and quality indicators. It is feasible to predict the quality indicators of fruit by detecting their low-frequency dielectric properties. This research offers significant insights and a valuable reference for non-destructive testing methods in assessing the quality of golden passion fruit.