Automated Tomographic Assessment of Structural Defects of Freeze-Dried Pharmaceuticals.

The topology and surface characteristics of lyophilisates significantly impact the stability and reconstitutability of freeze-dried pharmaceuticals. Consequently, visual quality control of the product is imperative. However, this procedure is not only time-consuming and labor-intensive but also expensive and prone to errors. In this paper, we present an approach for fully automated, non-destructive inspection of freeze-dried pharmaceuticals, leveraging robotics, computed tomography, and machine learning.

Ultra-Wideband Microwave Imaging System for Root Phenotyping.

The roots are a vital organ for plant growth and health. The opaque surrounding environment of the roots and the complicated growth process means that in situ and non-destructive root phenotyping face great challenges, which thus spur great research interests. The existing methods for root phenotyping are either unable to provide high-precision and high accuracy in situ detection, or they change the surrounding root environment and are destructive to root growth and health. Thus,we propose and develop an ultra-wideband microwave scanning method that uses time reversal to achieve in situ root phenotyping nondestructively. To verify the method's feasibility, we studied an electromagnetic numerical model that simulates the transmission signal of two ultra-wideband microwave antennas. The simulated signal of roots with different shapes shows the proposed system's capability to measure the root size in the soil. Experimental validations were conducted considering three sets of measurements with different sizes, numbers and locations, and the experimental results indicate that the developed imaging system was able to differentiate root sizes and numbers with high contrast. The reconstruction from both simulations and experimental measurements provided accurate size estimation of the carrots in the soil, which indicates the system's potential for root imaging.

Damage Diagnosis of Single-Layer Latticed Shell Based on Temperature-Induced Strain under Bayesian Framework.

Under the framework of Bayesian theory, a probabilistic method for damage diagnosis of latticed shell structures based on temperature-induced strain is proposed. First, a new damage diagnosis index is proposed based on the correlation between temperature-induced strain and structural parameters. Then, Markov Chain Monte Carlo is adopted to analyze the newly proposed diagnosis index, based on which the frequency distribution histogram for the posterior probability of the diagnosis index is obtained. Finally, the confidence interval of the damage diagnosis is determined by the posterior distribution of the initial state (baseline condition). The damage probability of the unknown state is also calculated. The proposed method was validated by applying it to a latticed shell structure with finite element developed, where the rod damage and bearing failure were diagnosed based on importance analysis and temperature sensitivity analysis of the rod. The analysis results show that the proposed method can successfully consider uncertainties in the strain response monitoring process and effectively diagnose the failure of important rods in radial and annular directions, as well as horizontal (x- and y-direction) bearings of the latticed shell structure.

High-energy high-dose microfocus X-ray computed tomography driven by high-average-current photo-injector.

High-energy, high-dose, microfocus X-ray computed tomography (HHM CT) is one of the most effective methods for high-resolution X-ray radiography inspection of high-density samples with fine structures. Minimizing the effective focal spot size of the X-ray source can significantly improve the spatial resolution and the quality of the sample images, which is critical and important for the performance of HHM CT. The objective of this study is to present a 9 MeV HHM CT prototype based on a high-average-current photo-injector in which X-rays with about 70µm focal spot size are produced via using tightly focused electron beams with 65/66µm beam size to hit an optimized tungsten target. In digital radiography (DR) experiment using this HHM CT, clear imaging of a standard 0.1 mm lead DR resolution phantom reveals a resolution of 6 lp/mm (line pairs per mm), while a 5 lp/mm resolution is obtained in CT mode using another resolution phantom made of 10 mm ferrum. Moreover, comparing with the common CT systems, a better turbine blade prototype image was obtained with this HHM CT system, which also indicates the promising application potentials of HHM CT in non-destructive inspection or testing for high-density fine-structure samples.

Research and development of anti-maceration laparoscopic surgical cotton swabs.

INTRODUCTION: Although laparoscopic cotton swabs have been used in procedures such as blunt tissue dissection and elevation of organs, fluid maceration is widely known to reduce their original performance. Thus, we developed an anti-maceration laparoscopic surgical cotton swab that is expected to solve this problem by coating the cotton swab with water-resistant resin. This study aimed to determine whether anti-maceration cotton swabs perform better than conventional products. MATERIAL AND METHODS: Fine surface shape analysis of cotton swabs was performed using microfocus X-ray computed tomography, and changes due to fluid absorption of the anti-maceration cotton swabs and pre-existing products were quantitatively compared. As indices, the degree of expansion by maceration and SMD (surface roughness index of the fiber industry showing the size of irregularities on the surface) were evaluated. RESULTS: The degree of expansion was lower in anti-maceration swabs than in conventional products. Maceration reduced SMD in existing products, whereas the SMD in anti-maceration cotton swabs did not change. CONCLUSIONS: Anti-maceration cotton swabs have a superior performance over conventional products.

Non-Destructive Identification of Fibre Orientation in Multi-Ply Biaxial Laminates Using Contact Temperature Sensors.

Fibre orientation within composite structures dictates the material properties of the laminate once cured. The ability to accurately and automatically assess fibre orientation of composite parts is a significant enabler in the goal to optimise the established processes within aftermarket aerospace industries. Incorrect ply lay-up results in a structure with undesirable material properties and as such, has the potential to fail under safe working loads. Since it is necessary to assure structural integrity during re-manufacture and repair assessment, the paper demonstrates a novel method of readily and non-destructively determining fibre orientation throughout multi-ply Biaxial woven composite laminates using point temperature contact sensors and data analysis techniques. Once cured, only the outermost laminates are visible to assess orientation. The inspection method is conducted visually, with reference guides to allow for rapid adoption with minimum training, as well as harnessing established temperature sensors within the Maintenance Repair and Overhaul (MRO) environment. The system is amenable to integration within existing repair/re-manufacture processes without significant impact to process flow. The method is able to identify noisy samples with an accuracy, precision and recall of 0.9, and for synthetically created samples of double the cure ply thickness, a precision of 0.75, a recall of 0.7 and an accuracy of 0.87.

Defect Detection in Aerospace Sandwich Composite Panels Using Conductive Thermography and Contact Sensors.

Sandwich panels consisting of two Carbon Fibre Reinforced Polymer (CFRP) outer skins and an aluminium honeycomb core are a common structure of surfaces on commercial aircraft due to the beneficial strength-weight ratio. Mechanical defects such as a crushed honeycomb core, dis-bonds and delaminations in the outer skins and in the core occur routinely under normal use and are repaired during aerospace Maintenance, Repair and Overhaul (MRO) processes. Current practices rely heavily on manual inspection where it is possible minor defects are not identified prior to primary repair and are only addressed after initial repairs intensify the defects due to thermal expansion during high temperature curing. This paper reports on the development and characterisation of a technique based on conductive thermography implemented using an array of single point temperature sensors mounted on one surface of the panel and the concomitant induced thermal profile generated by a thermal stimulus on the opposing surface to identify such defects. Defects are classified by analysing the differential conduction of thermal energy profiles across the surface of the panel. Results indicate that crushed core and impact damage are detectable using a stepped temperature profile of 80 ∘C The method is amenable to integration within the existing drying cycle stage and reduces the costs of executing the overall process in terms of time-to-repair and manual effort.

Composite Laminate Delamination Detection Using Transient Thermal Conduction Profiles and Machine Learning Based Data Analysis.

Delaminations within aerospace composites are of particular concern, presenting within composite laminate structures without visible surface indications. Transmission based thermography techniques using contact temperature sensors and surface mounted heat sources are able to detect reductions in thermal conductivity and in turn impact damage and large disbonds can be detected. However delaminations between Carbon Fibre Reinforced Polymer (CFRP) plies are not immediately discoverable using the technique. The use of transient thermal conduction profiles induced from zonal heating of a CFRP laminate to ascertain inter-laminate differences has been demonstrated and the paper builds on this method further by investigating the impact of inter laminate inclusions, in the form of delaminations, to the transient thermal conduction profile of multi-ply bi-axial CFRP laminates. Results demonstrate that as the distance between centre of the heat source and delamination increase, whilst maintaining the delamination within the heated area, the resultant transient thermal conduction profile is measurably different to that of a homogeneous region at the same distance. The method utilises a supervised Support Vector Classification (SVC) algorithm to detect delaminations using temperature data from either the edge of the defect or the centre during a 140 s ramped heating period to 80 °C. An F1 score in the classification of delaminations or no delamination at an overall accuracy of over 99% in both training and with test data separate from the training process has been achieved using data points effected by transient thermal conduction due to structural dissipation at 56.25 mm.

Influence of physical and biological variability and solution methods in fruit and vegetable quality nondestructive inspection by using imaging and near-infrared spectroscopy techniques: A review.

Over the past decades, imaging and spectroscopy techniques have been rapidly developing and widely applied in nondestructive fruit and vegetable quality assessment. The physical properties (including size, shape, color, position, and temperature) and biological properties (including cultivar, season, maturity level and geographical origin) of fruits and vegetables vary from one to another. A great variety of physical and biological properties of agricultural products influence the optical propagation properties and interaction behaviors with incident light, thus decreasing the quality inspection accuracy. Many attempts have been made in image correction and spectral compensation methods to improve the inspection accuracy. This paper gives a detailed summary about influence of physical and biological variability, as well as the correction and compensation methods for eliminating or reducing the effects in fruit and vegetable quality nondestructive inspection by using imaging and spectroscopy techniques. The advantages and disadvantages of the solution methods are discussed and summarized. Additionally, the future challenges and potential trends are also reported.

A CBCT series slice image segmentation method.

BACKGROUND: Images of industrial cone-beam computed tomography (CBCT) contain noise and beam hardening artifacts, which induce difficulty and low precision in segmenting regions of interest. OBJECTIVE: The primary objective of this study is to improve the segmentation precision of CBCT series slice images. METHODS: This paper presents a method based on the Phansalkar to segment CBCT series slice images precisely. First, the basics of the proposed method and the necessity of changing the local window size are analysed. The adaptive accumulated Phansalkar, which collects each pixel's classification results in different local windows, is proposed. Second, the bimodal distribution of the histogram is used to calculate the appropriate local window size for each pixel adaptively. Third, the characteristics of the accumulated probability (the accumulated classification results divided by the accumulated times) are analysed, from which an adaptive method is applied to segment the accumulated probability. Last, experiments are conducted on CBCT series slice images of three workpieces and one computer-aided design (CAD) model with internal defects. RESULTS: The proposed new method can segment CBCT images with noise and beam-hardening well. Moreover, for the segmentation of all four CBCT series slice images, the new method acquired the highest BF and AOM scores (1 and 0.9981) with the smallest standard deviation (0.0013) as compared with other existing methods including CMF (continuous max-flow/min cut), MS (mean-shift), DRLSE (distance regularized level set evolution), and ARKFCM (adaptively regularized kernel-based fuzzy c-means clustering). CONCLUSIONS: The experimental results support that our new method can more precisely segment CBCT series slice images with noise and artifacts than many existing methods. Thus, the new method has prospective application value and can provide valuable technical support for the industrial CBCT image post-processing system.

Microwave Non-Destructive Inspection and Prediction of Modulus of Rupture and Modulus of Elasticity of Engineered Cementitious Composites (ECCs) Using Dual-Frequency Correlation.

This research article presents dual-frequency correlation models for predicting the growth of elasticity and flexural strength of engineered cementitious composites (ECCs) using microwave nondestructive inspection technique. Parallel measurements of microwave properties and mechanical properties of ECC specimens were firstly undertaken in the sense of cross-disciplinary experiments. Regression models were developed via means of nonlinear regression to the measured data. The purpose of the study is: (i) to monitor the flexural strength and elasticity growth; and (ii) to predict their mature values under the influence of different initial water contents, via microwave effective conductance at early ages. It has been demonstrated that both the modulus of rupture (MOR) and modulus of elasticity (MOE) can be accurately modeled and correlated by microwave conductance using exponential functions. The moduli developed as a function of conductance whereas the regression coefficient exhibited a linear relation with water-to-binder ratio. These findings have highlighted the effectiveness of the microwave non-destructive technique in inspecting the variation of liquid phase morphology of ECCs. The dual-frequency correlation can be used for structural health monitoring, which is not only for prediction but also provides a means of verification.

Non-Destructive Inspection of Physicochemical Indicators of Lettuce at Rosette Stage Based on Visible/Near-Infrared Spectroscopy.

Lettuce is a globally important cash crop, valued by consumers for its nutritional content and pleasant taste. However, there is limited research on the changes in the growth indicators of lettuce during its growth period in domestic settings. Quality assessment primarily relies on subjective evaluations, resulting in significant variability. This study focused on hydroponically grown lettuce during the rosette stage and investigated the patterns of changes in the indicators and spectral curves over time. By employing spectral preprocessing and selecting characteristic wavelengths, three models were developed to predict the indicators. The results showed that the optimal model structures were S_G-UVE-PLSR (SSC and vitamin C) and Nor-CARS-PLSR (moisture content). The PLSR models achieved prediction set correlation coefficients of 0.8648, 0.8578, and 0.8047, with residual prediction deviations of 1.9685, 1.9568, and 1.6689, respectively. The optimal models were integrated into a portable device, using real-time analysis software written in Matlab2021a, for the prediction of the physicochemical indicators of lettuce during the rosette stage. The results demonstrated prediction set correlation coefficients of 0.8215, 0.8472, and 0.7671, with root mean square errors of prediction of 0.5348, 1.5813, and 2.3347 for a sample size of 180. The small discrepancies between the predicted and actual values indicate that the developed device can meet the requirements for real-time detection.

Characterisation of corrosion-induced crack in concrete using ultrasonic diffuse coda wave.

Corrosion damage in reinforcing steel bars has been a major cause of cracking and spalling of reinforced concrete. To extend the service life of concrete structures, non-destructive testing methods are necessary to assess the corrosion status in order to conduct a timely repair. At the early stage of corrosion, rust grows from the reinforcing bar, subsequently generates cracks towards the surface of the concrete. Ultrasonic methods have been widely used to detect cracks in concrete. However, it is challenging to characterise them due to the heterogeneous material properties of the concrete. In this paper, ultrasonic imaging technique based on diffuse coda wave has been explored to inspect and characterise corrosion-induced cracks. In this method, scattering cross-section of the crack is reconstructed with the Locadiff imaging technique. Based on the assumption that both crack tips have the same scattering cross-section, the size of the crack can be estimated when the location of the reinforcing bar is known. Numerical simulations were carried out to image straight and curved cracks, showing excellent accuracy. Experiments were designed subsequently on concrete samples with accelerated corrosion. The induced cracks were characterised by the proposed ultrasonic method, and compared with X-ray CT results, showing very good agreement.

Comparison and characterization of pigments and dyes by Raman spectroscopy.

This review provides a general understanding of Raman spectroscopy for use in the identification of pigments and dyes. The methodologies associated with a number of different related applications are also summarized. The first part of this review clarifies our basic knowledge regarding natural minerals and pigments. The second part discusses the fundamentals of currently used Raman spectroscopy, including surface-enhanced Raman scattering, µ-Raman spectroscopy, Raman imaging and spatially offset Raman spectroscopy. The third part focuses on recent applications, including the identification and analysis of various pigments and dyes that are used in paintings and related artworks. These studies show that Raman spectroscopy has great potential for use as a method for the rapid, non-destructive identification of such substances.

Relationship between porcine carcass grades and estimated traits based on conventional and non-destructive inspection methods.

As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R 2) and 0.980 (R 2), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.

Weld acoustic emission inspection of structural elements embedded in concrete.

After a catastrophic failure of the weld of the anchoring element of one cable in a stayed bridge, a non-destructive inspection was required to evaluate the weld condition of the 111 remaining anchoring elements to prevent future and similar failures. This examination was quite complicated since the anchoring elements are partially embedded in the reinforced concrete tower, and the weld is fully integrated into the concrete. Considering that direct access to the weld was not possible, acoustic emissions (AE) were a feasible alternative for these inspections. This study describes the inspection method, from laboratory tests simulating actual conditions for calibration to field tests for the method's tuning and evaluation. The AE inspection results are presented, and welds' condition is classified according to the acoustic energy, measured through a severity index and graded from a zonal intensity plot. Two structural elements were selected for concrete demolition to expose the weld for penetrant and ultrasonic inspections to correlate measurements of the actual condition of the welds and their defect size. Because of the analysis, welds are identified for immediate repair and the rest for AE monitoring to evaluate defect evolution through the increase of the severity index.

Maintenance and Inspection of Fiber-Reinforced Polymer (FRP) Bridges: A Review of Methods.

Fiber-reinforced polymers (FRPs) are materials that comprise high-strength continuous fibers and resin polymer, and the resins comprise a matrix in which the fibers are embedded. As the technique of FRP production has advanced, FRPs have attained many incomparable advantages over traditional building materials such as concrete and steel, and thus they play a significant role in the strengthening and retrofitting of concrete structures. Bridges that are built out of FRPs have been widely used in overpasses of highways, railways and streets. However, damages in FRP bridges are inevitable due to long-term static and dynamic loads. The health of these bridges is important. Here, we review the maintenance and inspection methods for FRP structures of bridges and analyze the advantages, shortcomings and costs of these methods. The results show that two categories of methods should be used sequentially. First, simple methods such as visual inspection, knock and dragging-chain methods are used to determine the potential damage, and then radiation, modal analysis and load experiments are used to determine the damage mode and degree. The application of FRP is far beyond the refurbishment, consolidation and construction of bridges, and these methods should be effective to maintain and inspect the other FRP structures.

Topology Optimization-Based Damage Identification Using Visualized Ultrasonic Wave Propagation.

This study proposes a new damage identification method based on topology optimization, combined with visualized ultrasonic wave propagation. Although a moving diagram of traveling waves aids in damage detection, it is difficult to acquire quantitative information about the damage, for which topology optimization is suitable. In this approach, a damage parameter, varying Young's modulus, represents the state of the damage in a finite element model. The feature of ultrasonic wave propagation (e.g., the maximum amplitude map in this study) is inversely reproduced in the model by optimizing the distribution of the damage parameters. The actual state of the damage was successfully estimated with high accuracy in numerical examples. The sensitivity of the objective function, as well as the appropriate penalization exponent for Young's modulus, was discussed. Moreover, the proposed method was applied to experimentally measured wave propagation in an aluminum plate with an artificial crack, and the estimated damage state and the sensitivity of the objective function had the same tendency as the numerical example. These results demonstrate the feasibility of the proposed method.

On-Line Monitoring of Blind Fastener Installation Process.

Blind fasteners are of special interest for aircraft construction since they allow working on joints where only one side is accessible, as is the case in many common aerospace box-type structures, such as stabilizers and flaps. This paper aims to deliver an online monitoring method for the detection of incorrect installed blind fasteners. In this type of fastener, the back side of the assembly is not accessible, so monitoring the process installation is suitable as a system to assess the formed head at the back side with no access. The solution proposed consists of an on-line monitoring system that is based on sensor signals acquired during the installation. The signals are conveniently analyzed in order to provide an evaluation outcome on how the fastener was installed. This new method will help production to decrease/eliminate time and cost-intensive inspections and fasteners over installation in structures. The decrease of the number of installed fasteners will also contribute to weight savings and will reduce the use of resources.

Impact damage visualization in a honeycomb composite panel through laser inspection using zero-lag cross-correlation imaging condition.

A fully non-contact laser-based nondestructive inspection (NDI) system is developed to detect and visualize damage in structures. The study focuses on the size quantification and characterization of a barely visible impact damage (BVID) in a honeycomb composite panel. The hardware consists of a Q-switched Nd:YAG pulse laser that probes the panel by generating broadband guided waves via thermo-elastic expansion. The laser, in combination with a set of galvano-mirrors is used to raster scan over a two-dimensional surface covering the damaged region of an impacted quasi-isotropic [60/0/-60]s honeycomb composite panel. The out-of-plane velocities are measured at a fixed location normal to the surface by a laser Doppler vibrometer (LDV). An ultrasonic full wavefield assembled from the three-dimensional space-time data matrix in the interrogated area is first acquired and then processed for imaging the impacted damage area. A wavenumber filtering technique in terms of wave vectors is applied to distinguish the forward and backward wavefields in the wavenumber-frequency domain. A zero-lag cross correlation (ZLCC) imaging condition is then employed in the space-frequency domain for damage imaging. The ZLCC imaging condition consists of cross correlating the incident and reflected wavefields in the entire scanned region. The condition not only images the damage boundary between incident and reflected waves outside the damage region but also, for longer time windows, enables to capture the momentary standing waves formed within the damaged region. The ZLCC imaging condition imaged two delaminated region: a main delamination, which was a skewed elliptic with major and minor axis lengths roughly 17 mm and 10 mm respectively, and a secondary delamination region approximately 6 mm by 4 mm, however, which can only be shown at higher frequency range around 80-95 kHz. To conclude, the ZLCC results were in very good agreement with ultrasonic C-scan and X-ray computed tomographic (X-ray CT) scan results. Since the imaging condition is performed in the space-frequency domain, the imaging from ZLCC can also reveal resonance modes which are shown in the main delaminated area by windowing a narrow frequency band sequentially.