Using Light Polarization to Identify Fiber Orientation in Carbon Fiber Components: Metrological Analysis.

In this work, a method for measuring tow angles in carbon fiber components, based on the use of a polarized camera, is analyzed from a metrological point of view. Carbon fibers alter the direction of the reflected light's electrical field, so that in each point of the surface of a composite piece, the angle of polarization of reflected light matches the fiber orientation. A statistical analysis of the angle of linear polarization (AoLP) in each pixel of each examined area allows to evaluate the average winding angle. An evaluation of the measurement uncertainty of the method on a cylinder obtained by a filament winding process is carried out, and the result appears adequate for the study of the distribution of angles along the surface of the piece, in order to optimize the process.

Guided wave multi-frequency damage localization method in variable-thickness structures by one pair of sensors based on frequency-dependent velocity anisotropy.

Variable thickness structures are prevalent in aircraft, ships, and other machines, necessitating numerous sensors for health monitoring to reduce safety hazards. This paper presents a guided wave multi-frequency localization method based on frequency-dependent velocity anisotropy. This method achieves damage localization in variable-thickness structures with a pair of sensors and can effectively reduce the number of sensors used for monitoring. Variations in structural thickness cause a gradient in guided wave velocity that bends the propagation path. Different thickness variations with different directions cause wave velocity anisotropy. As a result, variations in thickness cause possible damage loci determined by echo time to deviate from an elliptical shape. Because the velocity anisotropy is frequency-dependent, damage loci at different frequencies are close but do not overlap and intersect only at the damage location. So, the multi-frequency method can increase the damage information acquired by a single pair of sensors, enabling damage localization. Experimental validation was conducted on a steel plate with linearly varying thicknesses. The feasibility of the multi-frequency localization method was verified by successfully locating the damage at three different locations using a pair of receiver-excitation sensors. In addition, the experiments demonstrated the capability of this multi-frequency method in improving the localization accuracy of sensor networks. The method has potential applications in monitoring systems lightweight, phased arrays, and imaging enhancement.

Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review.

Non-destructive testing (NDT) techniques play a crucial role in industrial production, aerospace, healthcare, and the inspection of special equipment, serving as an indispensable part of assessing the safety condition of pressure equipment. Among these, the analysis of NDT data stands as a critical link in evaluating equipment safety. In recent years, object detection techniques have gradually been applied to the analysis of NDT data in pressure equipment inspection, yielding significant results. This paper comprehensively reviews the current applications and development trends of object detection algorithms in NDT technology for pressure-bearing equipment, focusing on algorithm selection, data augmentation, and intelligent defect recognition based on object detection algorithms. Additionally, it explores open research challenges of integrating GAN-based data augmentation and unsupervised learning to further enhance the intelligent application and performance of object detection technology in NDT for pressure-bearing equipment while discussing techniques and methods to improve the interpretability of deep learning models. Finally, by summarizing current research and offering insights for future directions, this paper aims to provide researchers and engineers with a comprehensive perspective to advance the application and development of object detection technology in NDT for pressure-bearing equipment.

Balancing of Resonant Differential Coils for Broadband Inductive Sensor Systems.

Differential coils are frequently implemented in inductive sensing systems. They can be considered as a single coil that is made up of two or more subcoils, wound in series opposition. They can be used on the transmit or receive side of measurement systems, and, if designed correctly, ensure no coupling between coils under background conditions. By cancelling background coupling, the receive electronics only needs to be able to measure the change in coupling produced by a target. This allows for a more efficient use of the dynamic range, and for larger receive-side amplifier gain, thereby improving SNR. When subcoils are not electrically similar, it can be hard to engineer the coil to be perfectly balanced across a wide bandwidth. This paper presents an analytical model of a resonant differential coil pair that is tested and applied on a planar metal detector for the detection of buried objects. The model demonstrates the capability to balance an arbitrary differential coil pair, which has a broad applicability across a range of inductive sensor applications such as metal detection and non-destructive testing. The method is applied to the practical system. The results show that the correction resulting from this method ensures a stable balance across a significantly enhanced bandwidth. In the case studied here, the bandwidth of the experimental system is increased from 20 kHz to 90 kHz.

Development of a High-Sensitivity Millimeter-Wave Radar Imaging System for Non-Destructive Testing.

There is an urgent need to develop non-destructive testing (NDT) methods for infrastructure facilities and residences, etc., where human lives are at stake, to prevent collapse due to aging or natural disasters such as earthquakes before they occur. In such inspections, it is desirable to develop a remote, non-contact, non-destructive inspection method that can inspect cracks as small as 0.1 mm on the surface of a structure and damage inside and on the surface of the structure that cannot be seen by the human eye with high sensitivity, while ensuring the safety of the engineers inspecting the structure. Based on this perspective, we developed a radar module (absolute gain of the transmitting antenna: 13.5 dB; absolute gain of the receiving antenna: 14.5 dB) with very high directivity and minimal loss in the signal transmission path between the radar chip and the array antenna, using our previously developed technology. A single-input, multiple-output (SIMO) synthetic aperture radar (SAR) imaging system was developed using this module. As a result of various performance evaluations using this system, we were able to demonstrate that this system has a performance that fully satisfies the abovementioned indices. First, the SNR in millimeter-wave (MM-wave) imaging was improved by 5.4 dB compared to the previously constructed imaging system using the IWR1443BOOST EVM, even though the measured distance was 2.66 times longer. As a specific example of the results of measurements on infrastructure facilities, the system successfully observed cracks as small as 0.1 mm in concrete materials hidden under glass fiber-reinforced tape and black acrylic paint. In this case, measurements were also made from a distance of about 3 m to meet the remote observation requirements, but the radar module with its high-directivity and high-gain antenna proved to be more sensitive in detecting crack structures than measurements made from a distance of 780 mm. In order to estimate the penetration length of MM waves into concrete, an experiment was conducted to measure the penetration of MM waves through a thin concrete slab with a thickness of 3.7 mm. As a result, Λexp = 6.0 mm was obtained as the attenuation distance of MM waves in the concrete slab used. In addition, transmission measurement experiments using a composite material consisting of ceramic tiles and fireproof board, which is a component of a house, and experiments using composite plywood, which is used as a general housing construction material in Japan, succeeded in making perspective observations of defects in the internal structure, etc., which are invisible to the human eye.

Advancements in and Research on Coplanar Capacitive Sensing Techniques for Non-Destructive Testing and Evaluation: A State-of-the-Art Review.

In contrast to conventional non-destructive testing (NDT) and non-destructive evaluation (NDE) methodologies, including radiography, ultrasound, and eddy current analysis, coplanar capacitive sensing technique emerges as a novel and promising avenue within the field. This paper endeavors to elucidate the efficacy of coplanar capacitive sensing, also referred to as capacitive imaging (CI), within the realm of NDT. Leveraging extant scholarly discourse, this review offers a comprehensive and methodical examination of the coplanar capacitive technique, encompassing its fundamental principles, factors influencing sensor efficacy, and diverse applications for defect identification across various NDT domains. Furthermore, this review deliberates on extant challenges and anticipates future trajectories for the technique. The manifold advantages inherent to coplanar capacitive sensing vis-à-vis traditional NDT methodologies not only afford its versatility in application but also underscore its potential for pioneering advancements in forthcoming applications.

A novel 3D LiDAR deep learning approach for uncrewed vehicle odometry.

Self-localization and pose registration are required for sound operation of next generation autonomous vehicles under uncertain environments. Thus, precise localization and mapping are crucial tasks in odometry, planning and other downstream processing. In order to reduce information loss in preprocessing, we propose leveraging LiDAR-based localization and mapping (LOAM) with point cloud-based deep learning instead of convolutional neural network (CNN) based methods that require cylindrical projection. The normal distribution transform (NDT) algorithm is then used to refine the former coarse pose estimation from the deep learning model. The results demonstrate that the proposed method is comparable in performance to recent benchmark studies. We also explore the possibility of using Product Quantization to improve NDT internal neighborhood searching by using high-level features as fingerprints.

Broad bandwidth and excellent thermal stability in BiScO3-PbTiO3 high-temperature ultrasonic transducer for non-destructive testing.

High-temperature ultrasonic transducer (HTUT) is essential for non-destructive testing (NDT) in harsh environments. In this paper, a HTUT based on BiScO3-PbTiO3 (BS-PT) piezoelectric ceramics was developed, and the effect of different backing layers on its bandwidth were analyzed. The HTUT demonstrates a broad bandwidth and excellent thermal stability with operation temperature up to 400 °C. By using a 10 mm thick porous alumina backing layer, the HTUT achieves a broad -6 dB bandwidth of 100 %, which is about 4 times superior to the transducer with an air backing layer. The center frequency (fc) of the HTUT remains stable with fluctuations of less than 10 % across the temperature range from room temperature to 400 °C. The HTUT successfully detected simulated defects in pulse-echo mode for NDT over 200 °C. This research not only advances high-temperature ultrasonic transducer technology but also expands the NDT applications in harsh environmental conditions.

Degradation Mechanisms of Mortar and Plaster Layers.

This article presents a case of complex investigation of defects of lime mortar and plaster that have been developing over a period of 48 years in a house in Prague and are strongly influenced by thermal and salt crystallization cycles. The aim of this research was to describe the degradation phenomena of mortars and plasters observed on a narrowly limited part of the building, combining structural elements of different types and ages and to explain the mechanisms of their formation and development. The geometric characteristics of the defects were determined by non-destructive methods, especially optical interference moiré, laser profilometry, photogrammetry, and infrared thermography. Material data were determined on samples by electron microscopy, ion exchange chromatography, and direct moisture content measurements. The results supported the hypothesis of the increase in the deformation of large buckles of detached plasters by the mechanism of buckling caused by loading of the edges with compression generated by volume changes. Direct loading of the boundary surfaces causes the formation of bulges in the confined areas. This study shows the importance of failure analysis of real structures to gain knowledge about the behavior of structures and materials under long-term service conditions.

A Complementary Fusion-Based Multimodal Non-Destructive Testing and Evaluation Using Phased-Array Ultrasonic and Pulsed Thermography on a Composite Structure.

Combinative methodologies have the potential to address the drawbacks of unimodal non-destructive testing and evaluation (NDT & E) when inspecting multilayer structures. The aim of this study is to investigate the integration of information gathered via phased-array ultrasonic testing (PAUT) and pulsed thermography (PT), addressing the challenges posed by surface-level anomalies in PAUT and the limited deep penetration in PT. A center-of-mass-based registration method was proposed to align shapeless inspection results in consecutive insertions. Subsequently, the aligned inspection images were merged using complementary techniques, including maximum, weighted-averaging, depth-driven combination (DDC), and wavelet decomposition. The results indicated that although individual inspections may have lower mean absolute error (MAE) ratings than fused images, the use of complementary fusion improved defect identification in the total number of detections across numerous layers of the structure. Detection errors are analyzed, and a tendency to overestimate defect sizes is revealed with individual inspection methods. This study concludes that complementary fusion provides a more comprehensive understanding of overall defect detection throughout the thickness, highlighting the importance of leveraging multiple modalities for improved inspection outcomes in structural analysis.