Advanced Nondestructive Testing Research Articles

Construction of a stable YOLOv8 classification model for apple bruising detection based on physicochemical property analysis and structured-illumination reflectance imaging

Effective and accurate detection of bruises at all stages has always been a challenge in non-destructive grading of apples. In this study, the visible structured-illumination reflectance imaging (SIRI) combing with deep learning method was proposed to identify bruised ‘Fuji’ apples at four different time stages (0, 6, 12 and 24 h). The macroscopic/microscopic structures and physicochemical properties of bruised tissue were measured and analyzed to determine the relationship between bruising time and these properties, as well as how they affect the accuracy of bruising detection. Results indicated that classification accuracy increased with the decrease of water and total phenolic content of the bruised tissue, as well as with the increase of color browning and bruised area. The YOLOv8 model achieved the highest detection accuracy (99.5 %) and stability. This research enhances understanding of apple bruise optics and aids in developing advanced nondestructive testing techniques.

Three-dimensional reconstruction method for layered structures based on a frequency modulated continuous wave terahertz radar

The feasibility of employing a continuous-wave terahertz detection system for non-contact and non-destructive testing (NDT) in multi-layered bonding structures is assessed in this study. The paper introduces the detection principle of terahertz frequency modulated continuous wave (FMCW) radar and outlines the two-dimensional (2D) scanning platform, which integrates optical lenses, three linear actuators, a control platform, and data acquisition units. Experimental results on two types of insulation with prefabricated defects demonstrate the capability of terahertz waves for transparent inspection imaging. These results confirm the viability of terahertz FMCW detection technology as an advanced NDT tool for multi-layered bonding structures. However, the inherent limitations of terahertz wavelength and hardware systems pose challenges in discriminating reflection peaks on upper and lower surfaces. To address this issue, a local adaptive empirical wavelet coefficient modal decomposition (LAEWCMD) method is proposed to enhance the longitudinal discrimination ability of terahertz detection. The proposed method involves segmenting the 2D terahertz detection image into regions to differentiate between defective and non-defective areas. Continuous wavelet transforms (CWT) are then applied to the range signals of each region to derive continuous wavelet coefficients (CWCs). Subsequently, empirical mode decomposition (EMD) is performed on the CWCs to decompose them into intrinsic mode functions (IMFs) and residual signals. The 1st IMF is utilized for three-dimensional (3D) reconstruction, and the regions are fused to generate the final output. The effectiveness of the proposed method is validated on aircraft thermal protection structures (TPS), achieving high-precision 3D reconstruction. This offers a novel approach for the application of terahertz computed tomography imaging and NDT.

A living lab for Structural Health Monitoring at the Nibelungen Bridge Worms for Transfer Learning of Structural Dynamics

The Nibelungen Bridge in Worms, Germany has been selected as a national demonstration structure for advanced non-destructive testing (NDT) and structural health monitoring concepts to extend the lifetime of civil structures and to optimize O&M actions. Parts of the research that involves this bridge as a demonstrator belong to the focus area program SPP100+. In this program, the bridges SHM System has been extended and combined with an additional setup of vibration sensors. The used digital smart sensor with pre-processing functions, the arrangement of the sensors at the structure and additional edge computing capability allows the investigation of transfer learning and other methods directly into the real structure. The living lab with seven triaxial accelerometers can be reconfigured in real-time and adjusted to the needs of AI models for classification. The comparison with the existing conventional SHM sensors has been made possible by hardware synchronization to the existing SHM System and collocating sensors at similar positions, so that a hardware exchange can be an investigated use-case for the transfer learning. During idle times, the system collects vibration data like a conventional SHM system. Keywords: Structural Health Monitoring (SHM), Data acquisition, Sensor technology.

Mitigation of Steel Corrosion Threshold Utilizing Plant-Based Green Corrosion Inhibitors through Electrochemical Techniques

Corrosion of steel reinforcement is a major cause of deterioration in reinforced concrete structures. The corrosion process is influenced by the concrete-steel interface, with the alkaline concrete pore solution initially providing passivation. However, ingress of aggressive substances like chlorides can disrupt the passive layer, initiating active pitting corrosion above a threshold level often taken as 0.4% chloride by cement weight. Once the chloride threshold is exceeded, corrosion propagation depends on oxygen and moisture availability. The resulting rust formation causes expansive cracking and spalling of the concrete cover. Corrosion damage can be mitigated through use of inhibitors like calcium nitrite though high dosages impair concrete strength. Recently, plant-based organic compounds have shown promise as green corrosion inhibitors. The corrosion behavior of steel in concrete can be evaluated through impressed accelerated corrosion testing along with electrochemical techniques like half-cell potential mapping and resistivity measurements. These allow assessment of the probability of corrosion and corrosion rate. Techniques like linear polarization resistance and electrochemical impedance spectroscopy can also quantify instantaneous corrosion rate. Proper structural condition assessment and repair using both conventional and green inhibitors is crucial to control steel corrosion, maintain service life and ensure safety. Further research is needed on green corrosion mitigation methods and advanced non-destructive testing techniques.

Comparison between PA and PWI/TFM Techniques for Non-Destructive Testing of Carbon Steel Weld

The Total Focusing Method (TFM) technique is an advanced Non-Destructive Testing (NDT) Ultrasonic Testing (UT) technique well known for its representative images of high resolution. It was firstly developed together with Full Matrix Capture (FMC) acquisition which can be substituted later by Plane Wave Imaging (PWI) acquisition for its improved acquisition speed and gain reserve without lowering the image quality. For these advantages, the PWI/TFM technique is tending to be more and more widely implemented. This article presents some results of the related study on PWI/TFM technique. Starting by PWI/TFM reconstruction principles, mainly on the influences of beam steering settings and corresponding inspection coverage in predefined Region of Interest (ROI), it focuses on the comparison on the indication amplitudes of planar discontinuities between classical Phased Array (PA) technique and PWI/TFM technique.

Real-Time Phased Array Ultrasonic Monitoring of Debonding Growth Under Cycling Loading in CFRP

Carbon Fibre Reinforced Polymer (CFRP) composites are widely employed in diverse industries due to their specific stiffness and strength, and corrosion resistance. However, over time, service-induced damage can initiate a failure that can threaten the operation’s safety and reliability, especially in critical industries like aerospace applications. The challenge lies in identifying and monitoring the defects before they escalate into serious issues. Non-Destructive Testing (NDT) methods play a pivotal role in this scenario, aiming to detect and evaluate defects without causing harm to the material. Detecting flaws in composite materials such as CFRP remains a complex task. Traditional NDT methods often struggle to effectively pinpoint and assess defects within these intricate structures. However, recent advancements in ultrasonic testing, especially Phased Array Ultrasonic Testing (PAUT), show promise in examining the internal composition of CFRP composites with higher accuracy and reliability. This study aims to demonstrate the applicability of PAUT for real-time monitoring of debond growth under dynamic loading. The loading was applied to the test specimens up to one million cycles, and 64 elements 2 MHz linear phased array probe was attached to the specimen. The acquired signals were analyzed and could also be recorded for offline processing or archiving. To validate the credibility of the findings, the performance of PAUT was compared to Acoustic Emission (AE), a well-established method for detecting and analysing high-frequency signals emitted by materials undergoing deformation or damage. Encouragingly, both methods exhibited similar trends in capturing the growth of debond. Furthermore, to verify the final defect lengths, post-test ultrasonic C-Scans utilizing the through transmission technique were conducted, complemented by visual inspections. These assessments served to confirm the accuracy and reliability of the results obtained through Phased Array Ultrasonic Testing. Real-time monitoring of composite structures using phased array technology comprises a valuable tool for real- time assessment of debonding in the composite. As industries continue to rely on Carbon Fibre Reinforced Polymer composites for multifaceted applications, the utilization of advanced Non-Destructive Testing methodologies like Phased Array Ultrasonic Testing emerges as a cornerstone in guaranteeing their continued integrity and performance.

Rapid Non-Destructive Detection Technology in the Field of Meat Tenderness: A Review.

Traditionally, tenderness has been assessed through shear force testing, which is inherently destructive, the accuracy is easily affected, and it results in considerable sample wastage. Although this technology has some drawbacks, it is still the most effective detection method currently available. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into applying five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of the quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations to guide the future direction of non-destructive, AI-enhanced meat tenderness detection.

Approaching code-compliant Non-Destructive Testing of carbon steel weld using Total Focusing Method technique

The Total Focusing Method (TFM) technique is an advanced Non-Destructive Testing (NDT) Ultrasonic Testing (UT) technique. It is usually used together with special acquisition configurations such as Full Matrix Capture (FMC) or Plane Wave Imaging (PWI) and can supply synthetic post-processing results based on a quantity of ultrasonic signals. It is believed that it will accelerate the UT technique revolution toward the artificial intelligence era. Compared to the conventional UT technique, or even advanced UT techniques, such like Time of Flight Diffraction (TOFD) and Phased Array (PA) techniques, this advanced UT technique is well known for its easy-to-interpret and high-resolution representative images. For these reasons, it is used more and more in the flaw sizing and characterization assessment. Following the publication of the standard ISO 23864, TFM technique become a member among all standardized weld inspection techniques. This article presents some related study results toward a code-compliant weld inspection regarding the related standards, dealing especially with the sensitivity calibration which is a key point for the applicability of amplitude-based acceptance criteria.

Statistical Analysis and Automation Through Machine Learning of Resonant Ultrasound Spectroscopy Data from Tests Performed on Complex Additively Manufactured Parts

Additive manufacturing brings inspection issues for quality assurance of final parts because non-destructive testing methods are faced with shape complexity, size, and high surface roughness. Thus, to drive additive manufacturing forward, advanced non-destructive testing methods are required. Methods based on resonant ultrasound spectroscopy (RUS) can take on all the challenges that come with additive manufacturing. Indeed, these full body inspection methods are adapted to shape complexity, to nearly any size, and to high degrees of surface roughness. Furthermore, they are easy to implement, fast and low cost. In this paper, we present the benefit of a resonant ultrasound spectroscopy method, combined with a statistical analysis through Z score implementation, to classify supposedly identical parts, from a batch comprised of several individual builds. We also demonstrate that the inspection can be further accelerated and automated, to make the analysis operator independent, whether the analysis of the resonant ultrasound spectroscopy data is performed supervised or unsupervised with machine learning algorithms.

Monitoring and quantification of ultrasonic fatigue damage in copper based on internal friction measurement

Fatigue damage in metals and alloys would reduce their strength and should be identified as early as possible. However, fatigue damage is usually difficult to detect even using advanced nondestructive testing method. Here we developed an automated damping monitoring system for ultrasonic fatigue testing based on a quantitative electromechanical impedance method. During fatigue testing, the damping and resonance frequency of the Piezo actuator/horn/specimen system is measured regularly using an impedance analyzer. When the system damping suddenly increases, it implies that fatigue damage may be generated in the specimen. Separate impedance measurements on the copper specimen in a vacuum chamber show that the internal frictions of damaged specimens are much larger than the fresh specimens. Subsequent X-Ray micro-CT scanning shows that microcracks up to 0.8 mm in length were generated in those fatigued specimens with increased internal frictions. Further tensile testing shows that compared to the fresh specimen, specimens with fatigue damage exhibits reduced tensile strength and elongation at break. Furthermore, the larger the internal friction, the smaller the remaining yield strength and a nearly linear relationship between them holds. Finally, a damage variable DQ is defined based on internal friction which can act as a measure of fatigue damage in metals.

Spectral analysis of cross-hole sonic logging data for pile integrity assessment

Ensuring the safety of foundations requires advanced non-destructive testing techniques. Cross-hole sonic logging (CSL) is a widely adopted method for evaluating the integrity of deep foundation elements, such as bored piles, barrettes, and diaphragm walls. This method involves analyzing the propagation time and relative energy of ultrasonic pulses transmitted and registered by probes inserted into pre-installed access tubes. However, in certain cases, standard analyses may not effectively distinguish anomalous signals arising from defects and other factors unrelated to concrete quality. Our study explores the potential of an alternative frequency-domain approach for CSL data analysis. We propose new attributes to quantify ultrasonic signal spectra, including spectrum area, normalized spectrum area, weighted mean frequency, and maximum frequency. These attributes are automatically calculated, eliminating the need for additional data processing time and minimizing the risk of human error. The proposed approach was applied to CSL data collected from two bored piles of 46 m length and successfully identified signals classified as anomalous through standard time-domain analysis. Further research is deemed necessary to fully explore the potential of the frequency-domain approach in enhancing the information content and reliability of CSL pile integrity testing

Investigation on local monitoring paradigms of in-situ conformally fabricated piezopolymer coating-based array transducers: Ultrasonic bulk waves and local ultrasonic resonances

Realistic structures with complex features have been intricate challenges for structural health monitoring (SHM) with permanently installed transducers. Poor conformability of conventional rigid and brittle piezoceramic wafers is a typical issue of applications on surfaces with complex geometry. Moreover, the accompanied high-stress concentration requires high-sensitivity defect detection which is difficult to achieve with large-area monitoring methods like lamb waves at tens to hundreds kHz. Previously, in-situ conformally fabricated piezopolymer coating-based array transducers (PCATs) have been developed to build large-area, lightweight, flexible, and tunable Lamb wave networks. In this study, two novel local monitoring methods were investigated with PCATs, namely ultrasonic bulk wave array inspection and local ultrasonic resonance spectroscopy. For thick structures, ultrasonic bulk waves were generated and detected by PCATs with broadband operating frequencies (1–10 MHz) and flexible array parameters. Simulation tools and imaging algorithms of array inspection in non-destructive testing (NDT) were well implemented based on the analogous directivity pattern and normal-pressure coupling mechanism. As proof of concept, PCATs were applied on example structures with flat, concave, and convex surfaces for internal defect imaging. For thin-walled and/or multilayer structures, PCATs were used to measure local ultrasonic resonances, comparable to conventional non-contact methods. With negligible influence on local mechanical properties and broadband frequency response, multiple resonance peaks from 0 to 25 MHz were identified as zero group velocity (ZGV) Lamb modes and thickness vibration modes of host structures, which can be used as damage indices for local monitoring of corrosion, delamination, stiffness degradation, etc. Through embracing advanced NDT techniques with PCATs, high-sensitivity and quantitative local monitoring could be achieved with conformal networks, offering the possibility to integrate with large-area monitoring as multi-scale SHM for complex structures.

Review And Future of Non-Destructive Testing Methods for Composites in Aircraft

The application of carbon fiber in aerospace requires more advanced non-destructive testing methods due to its unique properties such as anisotropy. In this paper, mainstream non-destructive testing methods are introduced, including visual inspection, resonance test, acoustic emission, eddy current test, ultrasonic test, laser shearography, infra-red thermography, and X-ray. Their strengths and weaknesses are compared, and the common challenges are exposed. To solve those problems, some developing techniques such as hybrid methods and deep-learning-based automated inspection are proposed.

Experimental investigation on interfacial defect detection for SCCS with conventional and novel contact NDT techniques

In order to ensure the mechanical performance and structural safety of steel–concrete composite structures (SCCS), advanced nondestructive testing (NDT) technique for bonding status at steel–concrete interfaces needs to be developed. In this study, the feasibility of multichannel analysis of surface waves (MASW)-based interfacial debonding detection is validated using the contact sensors array. Herein, the multichannel sensor arrays are composed of piezoceramic lead zirconate titanate patches and high-frequency acceleration meters, respectively. For comparison, the impact-response (IR) method and impact-transmission (IT) method are performed utilizing a force hammer and high-frequency acceleration meters, and corresponding damage imaging algorithms are developed. The applicability of ultrasonic computed tomography (CT) scanning test, scanning impact echo (IE) method, ultrasonic tomography (UT) technique on interfacial debonding detection is further discussed in depth. Research findings indicate that the developed contact MASW measurement can fully capture the variation of dispersion characteristics of surface waves induced by debonding defects in SCCS. The developed IR and IT methods are suitable for detecting interfacial debondings in different dimensions. Besides, the damage nephogram resolution of IR is higher than that of the IT method. In addition, the practicability of traditional ultrasonic CT scanning tests, scanning IE method, and UT techniques using commercial equipment is investigated. Experimental observations show that classical NDT testing techniques are incapable of effectively identifying the existence of interfacial damage and are unsuitable for NDT tests on SCCS. The research findings in this study clearly exhibit the precision and limitation of various contact NDT techniques and lay a solid foundation for interfacial debonding detection in practical SCCS.

Fatigue fracture quantification in brittle cementitious materials using acoustic emission testing and digital image correlation

Fatigue loading in brittle materials introduces damage at the micro-scale. These micro-fractures can accumulate and cause a significant reduction in material stiffness or even lead to structural failure. Deformation-based monitoring techniques can be inadequate when detecting damage at the micro-level. Hence, here is where advanced non-destructive testing (NDT) methods such as acoustic emission testing (AET) and digital image correlation (DIC) can provide a significant improvement in quantifying fatigue damage. The paper aims to combine AET and DIC for advanced fatigue damage analysis on brittle cementitious mortars. Cylindrical samples with three different sizes are subjected to fatigue loading in a Brazilian splitting test. The damage advancement quantified from cumulative AE event count and energy analysis showed a good correlation with the tensile deformation measurement of the DIC. It was observed that for low cycle loading, the slowly progressing damage evolution may not always occur, instead abrupt failure similar to monotonic loading can occur even after passing several load cycles. The size of the fracture process zone (FPZ) was measured using several AE-based and DIC-based methods. The comparison of the approaches indicated that the AE energy-based method is the most suitable to quantify the FPZ size during fatigue damage progress. From AE-based FPZ analysis of the experimental results, it was concluded that for low-cycle loadings, the lack of a well-developed FPZ can be a cause of the sudden brittle failure.

Cone beam computed laminography based on adaptive-weighted dynamic-adjusted relative total variation

X-ray computed laminography (CL) is an advanced non-destructive testing technique. It allows 3D imaging of the interior of a plate–shell object using projections at a tilted angle, making up for the shortcomings of traditional computed tomography (CT) in imaging plate–shell objects. Nevertheless, the incomplete projections of the cone beam CL result in inter-slice aliasing and cone angle artifacts in the reconstructed image. To address this issue, we present an adaptive-weighted dynamic-adjusted relative total variation (AwDaRTV) minimization algorithm. Based on relative total variation (RTV), the proposed AwDaRTV considers the edge property among adjacent image voxels and introduces weights that are adaptively adjusted with local image gradients. In addition, a dynamically adjusted weight is designed for the regularization term in the hierarchical direction of the reconstructed image. And the weight updates with the number of iterations. To demonstrate the superiority of the proposed algorithm, experiments are carried out on the PCB phantom and the workpiece phantom. Qualitative and quantitative analyzes show that the proposed algorithm works well in reconstructing critical structural features and is effective at suppressing noise, as well as inter-slice aliasing and blurring.

Laser-based ultrasonics for non-destructive material testing: A practical guide

Materials play a crucial role in various industries, ranging from aerospace and automotive to healthcare and electronics. Understanding their mechanical properties is fundamental in ensuring their performance and reliability in different applications. Material testing not only aids in selecting the right material but also in optimizing treatments and processes for enhanced functionality and durability. In recent years, Non-Destructive Testing (NDT) methods have gained prominence due to their ability to assess material properties without causing damage. This approach not only saves time and resources but also allows for continuous monitoring and inspection during the lifespan of a material or component. Among the advanced NDT techniques, Laser-Based Ultrasonics (LBU) has emerged as a powerful tool for non-contact, high-resolution testing and characterization of materials. By harnessing laser technology to generate and detect ultrasonic waves, LBU offers unparalleled sensitivity and precision in assessing material integrity, defects, and structural variations. Its non-invasive nature makes it ideal for inspecting complex geometries, thin films, and delicate components where traditional destructive methods may not be feasible or practical. Furthermore, LBU can provide real-time data, enabling rapid decision-making and quality control in manufacturing processes. This paper aims to highlight the advantages of NDT, particularly the superiority of techniques like LBU, in ensuring the quality, reliability, and performance of materials across diverse industrial sectors. Through comprehensive material testing and characterization, informed decisions can be made regarding material selection, process optimization, and quality assurance, ultimately contributing to advancements in technology and product innovation.

NDT assessment of a thick-walled reinforced concrete mock-up of NPP concrete structures

Different materials within the Nuclear Power Plants (NPP) concrete structure can undergo ageing process which causes defects in the materials and can lose, partially or totally, their designed function. The typical defects include corrosion of reinforcement steel, delamination, cracks, malfunction of post-tensioning or steel composite systems etc. The testing methods to detect the defects of concrete structures are (i) destructive examinations and (ii) non-destructive testing (NDT). The challenges for assessing the performance of the NPP concrete structures using (NDT) methods include (i) the limited access time (only during the annual overhauls) and (ii) the accuracy and reliability of the available NDT testing devices. To overcome these challenges, a mock-up wall representing a section of the concrete containment of the NPP was built. Simulated defects and errors were embedded inside the wall such as dimensional errors, honeycombing, delamination, and voids in the post-tensioned grouted tendon ducts. Different NDT techniques and combinations were used for assessing the simulated defects of the mock-up wall. These techniques included basic NDT methods as rebound hammer, ultrasonic pulse velocity (UPV) and concrete cover meter and advanced NDT as Ground Penetrating Radar (GPR) and ultrasonic pulse echo (MIRA and MONOLITH). The results of basic NDT techniques as concrete cover meter, rebound hammer and UPV presented the basic characteristic properties of the concrete mock-up wall as concrete cover depth, compressive strength, and quality of concrete. The use of advanced NDT as GPR and MIRA and MONOLITH enabled us to detect and locate the embedded defect and the construction faults inside the mock-up wall. We conclude that the construction of the with simulated defects offers the possibility to investigate accuracy and reliably of the available NDT methods and increases the field experts’ skills providing also an important and very much needed educational platform for future NDE experts.

Performance of acoustic emission and digital image correlation for fracture analysis in cementitious mortars under fatigue loading

Fatigue loading in brittle materials introduces damage at a micro-scale. These micro-fractures can accumulate and cause a significant reduction in material stiffness or even lead to structural failure. Deformation-based monitoring techniques can be inadequate when detecting damage at a micro-level. Hence, here is where advanced nondestructive testing (NDT) methods such as acoustic emission (AE) and digital image correlation (DIC) can play a great role. The paper aims to combine AE and DIC for advanced fatigue damage analysis on a cylindrical sample subjected to a fatigue Brazilian splitting test. The damage progress quantified from cumulative AE event count, and horizontal displacement measured with DIC showed a very good correlation. The damaged region was identified with an AE localization plot and with a DIC displacement field plot, the damaged area was well represented by both techniques. When a material goes through an irreversible change, part of the released energy will generate an elastic wave. The wave will propagate through the material and the whole phenomenon is termed an acoustic emission. By using AE sensors on the surface of the sample, these waves are captured and analyzed to better understand the source of the emission. Its high sensitivity to micro-changes makes it an ideal technique to use for fatigue damage investigation. Digital image correlation relates sequentially taken images to determine displacement and strain measurements. While DIC analyzes material evolution using surface deformation measurements, AE on the other hand is capable of monitoring damage inside the volume of material. Hence, their combination provides an efficient test setup for monitoring fatigue micro-fracture. The paper aims to combine AE and DIC for advanced fatigue damage analysis on cylindrical samples that are subjected to monotonic and fatigue Brazilian splitting tests. The analysis will use damage progress under monotonic loading as a reference to further understand fatigue fracture. Methods of AE data filtering and AE source localization are discussed and evaluated for their use in fracture analysis. The utilization of DIC to track the material stiffness evolution is investigated. In addition, the paper compares fracture process zones quantified by AE and DIC. From the experimental analysis, it was found that both methods captured the fatigue damage patterns, yet provided complementary information for damage evaluation.

Ultrasonic and phased-array inspection in titanium-based alloys: A review

Ultrasonic testing procedures are among the most extensively used techniques in non-destructive testing and non-destructive evaluation systems. Meanwhile, phased array inspection or phased-array ultrasonic testing techniques as a well-known type of ultrasonic testing in advanced non-destructive testing systems are utilized in numerous applications, including oil and gas, medical imaging applications, railway, automotive, marine, and aviation industries. Phased-array ultrasonic testing-based methods can also be used in a variety of weld inspections, bond testing, thickness profiling, flaw detections, corrosion inspections, and in-service crack detection. The rapidity, safety, easiness, affordable price, and accurate visualization of phased array in measuring the defect characteristics such as size, shape, depth, and orientation allow its wide usage and even as a substitute for other inspection methods like radiographic methods. In phased array methods, more than one sound wave is employed to enhance the reliability and flexibility of inspection through the operation of several transducer assemblies, involving 16 to 256 small individual elements. Titanium having many desirable properties like high strength to weight ratio found many industrial applications, which highly necessitates its persistent inspection. For this aim, the present study focuses on the application of the phased-array ultrasonic testing technique for inspecting Ti components specifically in additive manufacturing, welding inspections, and defect detection of complex geometries and composites. Moreover, modern applications and improved computation methods are discussed. The development of phased-array ultrasonic testing inspection systems, particularly high throughput and efficient in situ and mobile equipment, and new computation methods will open new horizons toward the highly sophisticated inspection procedures.