Advances in Non-Destructive Testing Methods, 2nd Volume

This study analyzes the pigments and binders used in the painted wooden structure of DaZhong Gate in the Confucius Temple in Qufu, Shandong Province, China. Five samples were collected from the building and analyzed using techniques such as polarized light microscopy (PLM), energy-dispersive X-ray spectroscopy (EDX), micro-Raman spectroscopy (m-RS), and Fourier-transform infrared spectroscopy (FT-IR). The findings reveal that the red, yellow, green, and blue pigments are identified as lead red, lead chromate yellow, emerald green, and ultramarine, respectively. The white pigment is determined to be a combination of chalk and lead white or anglesite. Considering the production period of the yellow and green pigments, it is inferred that architectural paintings underwent restoration or repainting during the late Qing Dynasty. The analysis of the binder in the pigment using pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) reveals that the binder employed is a protein-based glue. Additionally, the detected presence of Heat-bodied tung oil suggests a potential connection to traditional Chinese painting techniques on wooden surfaces. This discovery not only contributes to the historical research of the Confucius Temple but also provides crucial data for the conservation and restoration efforts of this culturally significant heritage site. Full article

The correlation between magnetic Barkhausen noise (MBN) features and the surface hardness of two types of die steels (Cr12MoV steel and S136 steel in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established with MBN magnetic features extracted by different methods as the input nodes to realize the quantitative prediction of surface hardness. The accuracy of the BP-NN model largely depended on the quality of the input features. In the extraction process of magnetic features, simplifying parameter settings and reducing manual intervention could significantly improve the stability of magnetic features. In this study, we proposed a method similar to the magnetic Barkhausen noise hysteresis loop (MBNHL) and extracted features. Compared with traditional MBN feature extraction methods, this method simplifies the steps of parameter setting in the feature extraction process and improves the stability of the features. Finally, a BP-NN model of surface hardness was established and compared with the traditional MBN feature extraction methods. The proposed MBNHL method achieved the advantages of simple parameter setting, less manual intervention, and stability of the extracted parameters at the cost of small accuracy reduction. Full article

A series of advanced equipment exposed to sub-/supercritical water environments at high temperatures, high pressures, and extreme water chemistry with high salt and dissolved oxygen content faces serious corrosion problems. Obtaining on-site corrosion data for typical materials in harsh environments is crucial for operating and maintaining related equipment and optimizing various corrosion prediction models. First, this article introduces the advantages and disadvantages, usage scenarios, and future development potential of several in situ monitoring technologies, including ultrasonic thickness measurement, the infrared thermography method, microwave imaging, eddy current detection, and acoustic emission. Considering the importance of electrochemical corrosion data in revealing microscale and nanoscale corrosion mechanisms, in situ testing techniques such as electrical resistance probes, electrochemical corrosion potential, electrochemical impedance spectroscopy, and electrochemical noise that can be applied to sub-/supercritical water systems were systematically discussed. The testing platform and typical data obtained were discussed with thick and heavy colors to establish a mechanical prediction model for corrosion behavior. It is of great significance to promote the development of corrosion monitoring techniques, such as breaking through testing temperature limitations and broadening the industrial application scenarios and maturity. Full article

The persistent challenge of adhesion in Fused Filament Fabrication (FFF) technology is deeply rooted in the mechanical and chemical properties of utilized materials, necessitating the exploration of potential resolutions. This involves adjustments targeting the interplay of printing parameters, the mechanical fortification of print beds, and the integration of more adhesive materials, resonating across user levels, from enthusiasts to complex industrial configurations. An in-depth investigation is outlined in this paper, detailing the plan for a systematically designed device. Engineered for FFF device installation, the device facilitates the detachment of printed models, while precisely recording the detachment process, capturing the maximum force, and its progression over time. The primary objective is fabricating a comprehensive measurement apparatus, created for adhesion assessment. The device is adaptable across diverse FFF machines and print bed typologies, conforming to pre-defined conditions, with key features including compactness, facile manipulability, and capacity for recurrent measurements. This pursuit involves evaluating adhesion levels in prints made from diverse materials on varying print bed compositions, aiming to establish a comprehensive database. This repository facilitates judicious material and bed type selection, emphasizing maximal compatibility. Emphasis is placed on operating within a thermally stable context, a pivotal prerequisite for consistent and reproducible results. Full article

The ultimate analysis parameters, including carbon (C), hydrogen (H), nitrogen (N), and oxygen (O) content in biomass, were rarely found to be predicted by non-destructive tests to date. In this research, we developed partial least squares regression (PLSR) models to predict the ultimate analysis parameters of chip biomass using near-infrared (NIR) raw spectra of non-wood and wood samples from fast-growing tree and agricultural residue and nine different traditional spectral preprocessing techniques. These techniques include first derivative (sd1), second derivative (sd2), constant offset, standard normal variate (SNV), multiplicative scatter correction (MSC), vector normalization, min-max normalization, mean centering, sd1 + vector normalization, and sd1 + MSC. Additionally, we employed a genetic algorithm (GA), successive projection algorithm (SPA), multi-preprocessing (MP) 5-range, and MP 3-range to develop a PLSR model for rapid prediction. A dataset consisting of 120 chip biomass samples was utilized for model development in which the samples were non-wood samples of 65–67% and wood samples of 33–35%, and the model performance was evaluated and compared. The selection of the optimum performing model was mainly based on criteria such as the coefficient of determination in the prediction set (R²_P), root mean square error of the prediction set (RMSEP), and the ratio of prediction to deviation (RPD). The optimal model for weight percentage (wt.%) of C was obtained using GA–PLSR, yielding R²_P, RMSEP, and RPD values of 0.6954, 1.1252 wt.%, and 1.8, respectively. Similarly, for wt.% of O, the most effective model was obtained using the multi-preprocessing PLSR–5 range method with R²_P of 0.7150, RMSEP of 1.3088 wt.%, and RPD of 1.9. For wt.% of N, the optimal model was obtained using the MP PLSR-3 range method, resulting in R²_P, RMSEP, and RPD values of 0.6073, 0.1008 wt.%, and 1.6, respectively. However, wt.% of the H model provided R²_P, RMSEP, and RPD values of 0.5162, 0.2322 wt.%, and 1.5, respectively. Notably, the limit of quantification (LOQ) values for C, H, and O were lower than the minimum reference values used during model development, indicating a high level of sensitivity. However, the LOQ for N exceeded the minimum reference value, implying the samples to be predicted by the model must be in the range of reference range in the calibration set. By scatter plot analysis, the effect of combined non-wood and wood spectra of biomass chips on rapid prediction of ultimate analysis parameters using NIR spectroscopy was investigated. To include different species in a model, the species have to be not only in the different values of the constituents to make a wider range for a robust model, but also must provide their trend line characteristics in the scatter plot, i.e., correlation coefficient (R), slope, and intercept (same slope and slope approached to 1, and intercept is same (no gap) and approached zero, high R approached to 1). The effect of the R, slope, and intercept to obtain the better-optimized model was studied. The results show that the different species affected the model performance of each parameter prediction in a different manner, and by scatter plot analysis, which of these species were affecting the model negatively and how the model could be improved was indicated. This is the first time the effect has been studied by the principle of a scatter plot. Full article

The productivity of plants is considerably affected by various environmental stresses. Exploring the specific pattern of the near-infrared spectral data acquired non-destructively from plants subjected to stress can contribute to a better understanding of biophysical and biochemical processes in plants. Experiments for investigating NIR spectra of maize plants subjected to water stress were conducted. Two maize lines were used: US corn-belt inbred line B37 and mutant inbred XM 87-136, characterized by very high drought tolerance. After reaching the 4-leaf stage, 10 plants from each line were subjected to water stress, and 10 plants were used as control, kept under a regular water regime. The drought lasted until day 17 and then the plants were recovered by watering for 4 days. A MicroNIR OnSite-W Spectrometer (VIAVI Solutions Inc., Chandler, AZ, USA) was used for in vivo measurement of each maize leaf spectra. PLS models for determining drought days were created and aquagrams were calculated separately for the plants’ second, third, and fourth leaves. Differences in absorption spectra were observed between control, stressed, and recovered maize plants, as well as between different measurement days of stressed plants. Aquagrams were used to visualize the water spectral pattern in maize leaves and how it changes along the drought process. Full article

Transverse cracking is thought of as the typical distress of asphalt pavements. A faster detection technique can provide pavement performance information for maintenance administrations. This paper proposes a novel vehicle-vibration-based method for transverse cracking detection. A theoretical model of a vehicle-cracked pavement vibration system was constructed using the d’Alembert principle. A testing system installed with a vibration sensor was put in and applied to a testing road. Then, parameter optimization of the Short-time Fourier transform (STFT) was conducted. Transverse cracking and normal sections were processed by the optimized STFT algorithm, generating two ideal indicators. The maximum power spectral density and the relative power spectral density, which were extracted from 3D time–frequency maps, performed well. It was found that the power spectral density caused by transverse cracks was above 100 dB/Hz. The power spectral density at normal sections was below 80 dB/Hz. The distribution of the power spectral density for the cracked sections is more discrete than for normal sections. The classification model based on the above two indicators had an accuracy, true positive rate, and false positive rate of 94.96%, 92.86%, and 4.80%, respectively. The proposed vehicle-vibration-based method is capable of accurately detecting pavement transverse cracking. Full article

Surface electrical resistivity is a non-destructive technique that is sensitive to the microstructure of hydrated cement paste and the chemical composition of the pore solution in cement-based materials. In this study, a Wenner array was used to measure changes in mortar resistivity due to chloride ion diffusion as a function of electrode separation. Specimens were made from four mortar mixtures: 100% Ordinary Portland cement and 60% cement + 40% fly ash at two water/binder ratios of 0.55 and 0.40. The specimens were subjected to unidirectional chloride ion diffusion in a 2.8 M NaCl solution for 175 days. To determine the chloride penetration depth, three methods were used: silver nitrate spraying, chloride concentration profiles via potentiometric titration, and chloride concentration profiles via inversion of the resistivity data using the RES1D software (version 1.00.09 Beta). The results showed a linear relationship between the chloride ion penetration depth obtained via inversion of the surface electrical resistivity data versus the penetration depth from colorimetry and from chloride concentration profiling (both with R² = 0.8612). Chloride penetration changed the conductivity of the pore solution; therefore, the resistivity decreased when increasing both the chloride concentration and the penetration depth. Inversion of surface resistivity data obtained with a Wenner array permitted non-destructive determination of chloride penetration. However, these results were obtained under laboratory environmental conditions and other scenarios must be addressed for wider applications. Full article

This paper presents the development of the lock-in thermography system with an additional cooling system. System feasibility is tested by investigating a square-shaped glass fiber-reinforced polymer (GFRP) with artificially made outer flaws. The influence of heating mode and sinusoidal excitation period on the defect detectability is considered. Thus, the experiment is split into two modes: the sample is solely heated in the first mode or simultaneously heated and cooled in the second. In each mode, the temperature measurement is performed first with a shorter excitation signal period and second with a longer one. The signal-to-noise ratio (SNR) is used to assess defect detection quantitatively. The comparative analysis shows that employing a mixed heating–cooling mode improves the SNR compared to the conventional heating mode. The further enhancement of the SNR is obtained by extending the excitation period. The combination of simultaneous heating and cooling with longer periods of the excitation signal allows for the best SNR values for the most detected defects. Full article

A through-transmission ultrasonic method is proposed to address limitations in conventional ultrasonic reflection methods for non-destructive testing of ferrite tiles. The method utilizes a dual-probe configuration on both sides of the test piece to measure ultrasonic transmission signals, overcoming issues related to blind zones and orientation limitations in pulse-echo reflection methods. This method demonstrates excellent capabilities for full inspection of internal and external defects in ferrite tiles. Physical field finite element simulations were conducted to analyze detection capabilities and a transmissive testing system is developed based on the simulation results. Experimental validation was performed on artificially manufactured quantified defect samples in aluminum alloy, and the same testing system was applied to evaluate ferrite tile samples. The results confirmed the effectiveness of the system in distinguishing defective (NG) signals from normal defect-free (OK) signals, with a recall rate of at least 95% on samples of various sizes up to 0.1 mm. This research provides insights for quality control and defect detection technology in ferrite tiles. Full article

The impedance change in an induction coil surrounding a metal tube adapter is investigated using the truncated region eigenfunction expansion (TREE) method. The conventional TREE method is inapplicable to this problem as a consequence of the numerical overflow of the eigenfunctions of the air–metal multi-subdomain regions. The difficulty is surmounted by a normalization procedure for the numerical eigenfunctions obtained from the 1D finite element method (FEM). An efficient algorithm is devised by the Clenshaw–Curtis quadrature rule for integrals involving the numerical eigenfunctions. The numerical results of the TREE and FEM simulation coincide very well in all cases, and the efficiency of the proposed method is also confirmed. Full article