Laser Ultrasonic Method Research Articles

Characterization of internal defects in cylindrical components using laser ultrasonic method with a modified SAFT algorithm

The health monitoring of cylindrical elements is particularly important for the safe operation of industrial production, because cylinders bear a lot of support and transmission work. Normal non-destructive evaluation techniques need special designs to suit high curvature surfaces of cylinders. Laser ultrasonic (LU) method can provide a remote and non-destructive inspection solution to solid cylinders due to its flexible adaptability to complex structures and strong penetration depth. However, constrained by the common problems of optical detection systems, the detected ultrasonic signals will suffer low signal-to-noise ratio and bad resolution from poor sample surface quality. Thus, a modified synthetic aperture focusing technique (SAFT) optimized for cylindrical components is proposed to improve the detectability of LU on small and buried defects. Mode conversion wave signals obtained by multiple separate excitations are used in SAFT imaging for the reconstruction of the defects under surface profile correction. To reduce the influence of incident waves such as direct surface acoustic wave, besides common difference method, adjacent wave subtraction algorithm based on cross-correlation is used for signal preprocessing, suppressing the incident waves and exaggerating the mode conversion waves. In numerical simulation, internal defects with diameters from 0.6 to 0.2 mm with various buried depths are visualized and accurately located via the optimized SAFT algorithm using mode conversion waves. For validation, a circumferential scanning system is established in LU experiment and internal defects from 0.8 to 0.4 mm in diameter inside solid cylinders are successfully detected with precise location. The results elucidate the reliability of characterizing the location of small internal buried defects in solid cylinder structures through LU-SAFT imaging.

Simulation and Experimental Research of V-Crack Testing of Rail Surfaces Based on Laser Ultrasound

Rail surface cracks are widespread damage that can lead to uneven surfaces of railheads and affect traveling safety. Non-destructive testing is needed to inspect rails regularly to ensure the normal operation of railroads. This paper proposes a laser ultrasonic testing method combining variational mode decomposition and diffractive Rayleigh wave time-of-flight to detect tiny cracks on the rail surface quantitatively. The finite element method was combined with experiments to simulate and experimentally investigate cracks of different sizes numerically. In the numerical simulation, the location of the crack was determined by B-scan. Afterward, the interaction between various types of ultrasound and cracks was comparatively analyzed, and the crack size was quantitatively characterized using useful information from the ultrasound signals. The results show that the time-of-flight method can detect arbitrary cracks with low error. Therefore, the experimentally acquired ultrasound signals used the time difference between the diffracted Rayleigh wave and other ultrasound waves to detect the crack information quantitatively. The variational mode decomposition method was used to separate the ultrasonic signals and extract the best surface wave modes to improve the signal-to-noise ratio. The results show that the combination of variational mode decomposition and time-of-flight method can effectively detect the size of cracks.

A fast laser ultrasonic SAFT method with sparse scanning data and F-K based interpolation

ABSTRACT Laser ultrasonic SAFT can be applied for noncontact testing and imaging of defects in structures. However, due to the large demand for signal data by laser scanning, the time consumption of this method would be relatively long. To address this problem, this paper proposes a fast LU-SAFT method with sparse scanning data and F-K based interpolation. It aims to reduce the inspection time but without decreasing the imaging resolution. First, the method determines the minimum number of scanning sparse points using simulation. Then the F-K interpolation method is utilised to recover the full-field unscanned point signal from the sparse scan data. Finally, the reconstructed signal is used for SAFT image reconstruction of the defect. The experimental results show that, for the same scanning area, the proposed method in this paper reduces the number of scanning points by 87.5% and shortens the scanning time by 86.0% compared to conventional LU-SAFT point-by-point scanning. Additionally, the signal-to-noise ratio of the defective SAFT imaging decreases by only about 7.9%.

Laser ultrasonic testing of defects in milling groove brazed joints of thrust chamber

This paper presented a new approach for noncontact inspection of defects in milling groove brazed joints of thrust chamber with laser ultrasonic testing method and synthetic aperture focusing technique (SAFT). Firstly, laser ultrasonic testing methods for milling groove brazed joints of thrust chamber was studied. Subsequently, numerical models were constructed to analyze the influence of defects on laser-excited signals. The analysis revealed that the brazed defects caused internal waves to reflect on the rib surface, manifesting as defect echo signals preceding the outer wall echo. Through scanning setting, the obtained SAFT images illustrate the presence of the defect directly and clearly. Furthermore, an experimental system was established to detect and image artificial defects with different degrees of weld leakage. The experimental results are consistent with simulation results, validating the capability and effectiveness of the testing and imaging method. In general, the proposed laser ultrasound method offers inherent advantages of non-contact detection with high resolution and precision, and it is easy to achieve fast and automated scanning of large and complex structures like thrust chambers, demonstrating its potential for enhancing the safety and reliability of liquid rocket engines.

A laser ultrasonic intelligent inspection method for metal surface defects based on digital twin model

To enhance the efficiency and intelligence of laser ultrasonic detection of metal surface defects, a detection method based on digital twins is proposed. Given the scarcity of defect samples and the difficulty of obtaining labeled data in practical applications, the finite element method is used to construct a laser ultrasonic metal defect detection model, effectively generating twin data for defect detection. With the help of generative adversarial networks, the distribution difference between twin data and real data is minimized. Additionally, by using continuous wavelet transform, one-dimensional ultrasonic signals are converted into two-dimensional time–frequency images for detection input. In terms of detection algorithm development, a residual network with an optimized global attention mechanism is introduced to ensure real-time synchronization and updates between the digital twin model and the actual laser ultrasonic detection equipment. Finally, experimental validation of the proposed method shows that it effectively addresses the issue of small sample sizes in defect detection and achieves high detection accuracy. Moreover, comparative experiments on crack defect migration tasks under different settings demonstrate the method’s good generalization ability.

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens with known, unchangeable defect properties, which are usually complicated to fabricate. It consist of a shape memory polymer foil with temperature-dependent Young’s modulus and ultrasound attenuation. This open a possibility to generate a reconfigurable defect by projecting a heating laser in the form of a short line on the specimen surface. Ultrasound is generated by a laser pulse at one fixed position and detected by a laser vibrometer at another fixed position for 64 different defect positions and 3 different configurations of the specimen. The obtained diversified datasets are used to optimize the neural network architecture for the interpretation of ultrasound signals. We study the performance of the model in cases of reduced and dissimilar training datasets. In our first study, we classify the specimen configurations with the defect position being the disturbing parameter. The model shows high performance on a dataset of signals obtained at all the defect positions, even if trained on a completely different dataset containing signals obtained at only few defect positions. In our second study, we perform precise defect localization. The model becomes robust to the changes in the specimen configuration when a reduced dataset, containing signals obtained at two different specimen configurations, is used for the training process. This work highlights the potential of the demonstrated machine learning algorithm for industrial quality control. High-volume products (simulated by a reconfigurable specimen in our work) can be rapidly tested on the production line using this single-point and contact-free laser ultrasonic method.

Evaluation of the Bond Quality of Metal-Clad Plates Using Laser Ultrasonic Local Resonance

The effective detection of delamination defects, especially sub-millimeter delamination defects, in metal-clad plates is of great significance in improving product quality. In this work, the laser ultrasonic (LU) local resonance method is used to locate and characterize the sub-millimeter defects in stainless/carbon steel-clad plates. The influence of the delamination radius on the amplitude and resonant frequency of the laser ultrasound was investigated using 2D axisymmetric finite element (FE) simulations. The simulation results show that both the amplitude and the first resonance frequency (FRF) are effective features for detecting large-scale delamination defects, but the FRF is a better feature for detecting tiny delamination defects. A 304/Q235/304-clad plate specimen was made through a hot rolling bonding process, which contained a large number of self-forming delamination defects. The laser ultrasonic signals of different composite states collected in the experiment have good consistency with the simulated waveforms. The experimental results show that the laser ultrasonic local resonance method is a high-resolution imaging method, which can locate and characterize the sub-millimeter delamination defects in stainless/carbon steel-clad plates.

Nondestructive detection of laser-cladding coating interface defects: a deep learning-enhanced laser ultrasonics approach

ABSTRACT Laser-cladding technology is now widely used in repairing mechanical parts and creating functional coatings. However, interface defects are commonly found in laser-cladding coatings, significantly impacting the fatigue and mechanical properties of these coatings. Therefore, it is necessary to detect interface defects in laser-cladding coatings. In this study, we utilised laser ultrasonics (LU) method to test interface defects non-destructively. However, the signal-to-noise ratio (SNR) of LU signals was poor. To address this issue, an unsupervised deep learning method was used to enhance the SNR. The results showed that the noises were suppressed by the deep learning method. Based on the deep learning-enhanced LU method, surface acoustic waves were used to present B-scan and C-scan images. The artificial defects with a 0.5 mm diameter were detected. Consequently, the deep learning-enhanced LU method proves to be a viable approach for the contactless, online, and non-destructive testing of interface defects in laser-cladding coatings.

Predictive maintenance on ball mill liner using 3D scanner and its analysis in the mining industry of Papua Indonesia

In the mining industry, the primary production process entails transforming large ore deposits into valuable concentrates. To get minerals from large ores, a grinding machine is needed to reduce the size of the ore, and then the minerals can be extracted. The ball mill is an important part of the grinder in the mining industry. Maintenance is required for the machine to continue to work effectively and optimally. One method of preventing ball mill failures and minimizing company losses on a large scale is to predict the life of ball mill liners or predictive maintenance. Using a 3D laser scan, it is possible to determine the ball mill liner's wear and tear. On the basis of liner wear analysis, this information can then be used to generate a liner replacement schedule or estimate the remaining life of the ball mill liner or relining and lifetime forecast. This study aims to compare the 3D laser scan method and ultrasonic testing method in terms of liner wear analysis and forecasting. This study also demonstrates that the laser scanning method will be more effective and efficient than ultrasonic testing.

Study on Detecting Method of Internal Defects by Laser Ultrasonics in Lap Joint Welding of Galvanized Steel Sheet and Finite Element Analysis of Its Detectability

Blowholes caused by vaporization of the galvanized layer are a problem with galvanized steel sheets, which use lap joint welding. The laser ultrasonic method is the possible solution to realize the desirable 100% inspection instead of the conventional sampling inspection. We have previously proposed a method to detect blowholes by capturing the reduction in ultrasonic intensity when it passes through internal defects through signal processing. However, there was a problem that the detection indicator devised varied. In this study, we investigated the causes and trends of detectability using finite element analysis. To efficiently calculate the results obtained by scanning measurement, we proposed and established a method to reproduce the results by taking the results from static measurements, which were shifted in the direction of the weld line little by little. As a result, it was found that one of the reasons for the detection indicator variation with scanning by the lasers is the three-dimensional positional relationship between the blowhole and the scanning measurement line. In addition, it was possible to propose the performance required for the ultrasonic generation laser such as the traveling speed and the repetition frequency by back-calculating the spatial resolution from the rate of detection needed.

Non-contact measurements of residual stress distribution and grain size in titanium alloys with laser ultrasonic system

In this study, a laser ultrasonic method is proposed for nondestructive non-contact measurement of both the residual stress depth profile and grain size in Ti-6Al-4 V alloy processed by warm shot peening (WSP). The method utilizes a pulsed laser to generate a surface acoustic wave (SAW) along the cross-section of the sample, and a laser interferometer to detect SAW signals. Laser ultrasonic measurements were performed on the samples treated by WSP at different temperatures (32, 100, 200 and 300 °C). A theoretical model for calculating the residual stress profile and a model to correlate the center frequency shift and the mean grain size of the sample were presented. The results obtained by the laser ultrasonic method were compared with those obtained by X-ray stress measurement, center-hole drilling (CHD), and electron backscattering diffraction (EBSD). The proposed method can measure and locate the maximum compressive residual stress (CRS) in a peened surface layer with a high spatial resolution of approximately 30 µm, allowing for precise extraction of the residual stress profile. This method can also provide an estimation of the grain size through the same experiment. The developed method is promising for the quick and nondestructive measurement of the residual stress profiles and grain size of surface treated metallic materials.

A modified synthetic aperture focusing algorithm used for transmission detection based on laser ultrasonics method

Compared with traditional ultrasonic nondestructive testing technology, the laser ultrasonics method (LU) has the advantages of high precision, non-contact, wide-band response, suitable for non-destructive testing (NDT) of materials having complex shapes or working in extreme environments such as the additive manufacturing (AM) process, etc. However, for a purely optical LU system, it is still limited by the poor reflection of rough/absorption surface of the material. In order to increase the signal-to-noise ratio (SNR) of the signal detected on the rough surface of a sample, and to overcome the limitation of the resolution restricted by half wavelength, a modified Synthetic Aperture Focusing Technique (SAFT) that can be used for internal defect detection of the material is proposed. The modified SAFT is based on LU centering transmission detection and it improves the resolution of the detection system by using the characteristics of ultrasonic propagation and its mode conversion. It is firstly studied in theory with a numerical model based on finite element method (FEM), and then it is applied in experiments to reconstruct the defect according to the signals detected by LU method. In our experiment, the artificial defects buried in an AM sample with diameter from 0.2 mm to 0.75 mm are successfully characterized by the SAFT imaging of ultrasonic signals. The results prove that the position of the defect in 3D and its size can be successfully obtained by the proposed SAFT.

LASER-ULTRASOUND DIAGNOSTICS OF PLASTIC PRODUCTS MANUFACTURED BY LASER STEREOLITHOGRAPHY

Abstract. This paper discusses the application of methods of non-destructive testing and flaw detection of plastic products manufactured by additive technologies. The modern development of additive technologies associated with the active transition from the manufacture of prototypes and test samples to the manufacture of functional products increases the requirements for improving the quality of manufacturing and conducting non-destructive diagnostics of finished products, including plastic materials. The overall productivity of the production process can be increased by increasing the yield due to a decrease in the number of defects, which is ensured by process control and the quality of finished products. The method of laser-ultrasound diagnostics allows monitoring and flaw detection of products made of different materials with good spatial resolution, which is not always possible, for example, by tomographic scanning. Thus, the main purpose of this work is to evaluate the possibility of using laser-ultrasonic methods to detect potential defects and to track the impact of the additive manufacturing process on the quality of plastic products.

A Review of Laser Ultrasonic Lamb Wave Damage Detection Methods for Thin-Walled Structures.

Thin-walled structures, like aircraft skins and ship shells, are often several meters in size but only a few millimeters thick. By utilizing the laser ultrasonic Lamb wave detection method (LU-LDM), signals can be detected over long distances without physical contact. Additionally, this technology offers excellent flexibility in designing the measurement point distribution. The characteristics of LU-LDM are first analyzed in this review, specifically in terms of laser ultrasound and hardware configuration. Next, the methods are categorized based on three criteria: the quantity of collected wavefield data, the spectral domain, and the distribution of measurement points. The advantages and disadvantages of multiple methods are compared, and the suitable conditions for each method are summarized. Thirdly, we summarize four combined methods that balance detection efficiency and accuracy. Finally, several future development trends are suggested, and the current gaps and shortcomings in LU-LDM are highlighted. This review builds a comprehensive framework for LU-LDM for the first time, which is expected to serve as a technical reference for applying this technology in large, thin-walled structures.

Estimation of stresses in a massive granite using laser ultra-sonic testing and stress memory effect

This paper addresses in-situ stress-estimation methods based on the Kaiser effect. The physical and mechanical properties of granite, diorite, and granodiorite samples selected at different depth intervals of the core obtained from a wellbore were examined. The ultimate uniaxial compressive strength, modulus of elasticity, and Poisson’s ratio of the rock samples were determined using presses and strain gauges. Also, local longitudinal and shear wave velocities were measured using a high-accuracy laser-ultrasonic system with a view to assessing the structure of the samples. Based on the resulting elastic wave velocity maps, samples with no obvious discontinuities were chosen. These undisturbed samples were subjected to uniaxial compression and their acoustic emission was simultaneously measured. In-situ stresses were estimated from the results of the interpretation of acoustic emission measurements. The experimental in-situ stresses were compared with the results of a numerical simulation. The ratio of the estimated in-situ stresses to the calculated ones is within the range from 0.81 to 1.11. This means that the laser ultrasonic and acoustic emission methods make it possible to effectively estimate in-situ stresses in a rock mass and assess the degree of rock mass damage.

Research on Laser Ultrasonic Total Focusing Imaging Method Based on ZYNQ Acceleration

Research on Laser Ultrasonic Total Focusing Imaging Method Based on ZYNQ Acceleration

Application of Laser Scanning in Internal Surveying of Premises and Development of 3D Model of Building

Nowadays, along with the classical and experienced surveying methods, modern technologies are rapidly developing and entering into the economy. Laser scanning has many benefits and uses. Application of this technology results in a point cloud from which it is possible to create three-dimensional models which can represent topographic properties, structure dimensions, and spatial relationships. The aim of the research is to investigate the application of three-dimensional laser scanning in the internal surveying of premises and in the development of the 3D model buildings. The task of the research is to apply the application of laser rangefinder and ultrasonic rangefinder method in the scanning of a building that is characterized by complex architecture, an interior garden, many protrusions, and a special layout of windows and doors. The use of the Stonex X300 laser scanner and Stonex M6 laser rangefinder has been described as well. To achieve the goals and objectives of the research, laser telemetry and ultrasonic telemetry method, method of three-dimensional modeling, as well as analysis of scientific literature, mathematical calculation methods, and analysis of documents and factual materials have been used. As the result of the investigation 3D model of a building consisting of 47 individual point clouds was developed. The main conclusion is that three-dimensional modeling as a computer graphics method for the three-dimensional representation of any object or surface can be used.

Research on laser ultrasonic propagation characteristics and quantitative detection of delamination of carbon fiber composite

Aiming at the problems of low signal-to-noise ratio (SNR) and low detection accuracy in the non-destructive testing of composites with anisotropic and multilayer structure, the delamination detection of composite materials is studied by using the advantages of laser ultrasonic micro defect detection combined with phased array technology. Firstly, through finite element simulation, the propagation characteristics of laser ultrasound when the delamination evolves are obtained, and a time-modulated phased array laser ultrasound test platform is designed to improve the SNR and detection efficiency of the delamination signal. Then, a laser ultrasonic feature extraction method based on the improved Hilbert-Huang transform is proposed. It includes optimizing the decomposition process of CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise), searching for the sensitive IMF components through correlation coefficient between the decomposed signal and the original signal, and extracting the feature parameters by Hilbert transform. Finally, the maximum amplitude imaging of the delamination defects is performed using the extracted feature parameters. Experiments show that the proposed method can characterize the delamination characteristics with high accuracy, effectively solve the interference of resin layer on the delamination characteristic signal, and can visualize the delamination in composites.

Ultra-Rapid, Physics-Based Development Pathway for Reactor-Relevant RF Antenna Materials

This article presents a rapid, atomistically informed, experimental development pathway for fusion reactor-relevant radio-frequency (RF) antenna materials in the Cu-Cr-(Nb,Al,Zr) composition system, with the goal of improving upon GRCop-84. RF antennas in a tokamak fusion reactor will face a unique set of challenges as both structural and functional materials. The desired material must simultaneously achieve and maintain high electrical conductivity, high strength, high thermal conductivity, resist high temperatures, possess low nuclear activation, and incur low damage due to neutron bombardment. The GRCop-84 alloy serves as a starting point for iterative improvement, with the desire to reduce or eliminate Nb from the material to minimize nuclear activation. The rapid development pathway makes use of a multi-target combinatorial thick-film sputtering process to produce full ternary phase diagrams on a Si wafer substrate. Transient grating spectroscopy (TGS), a laser-ultrasonic method, will determine spatially varying thermoelastic properties, while four terminal electrical conductivity measurements will map out the best performing regions of the sample for in-depth study at larger length scales. High-energy proton and self-ion irradiation emulates the effects of neutron damage on the thermal/electric properties. With rapid turnaround time (~days) in terms of mapping radiation damage-induced material property changes in the full ternary system, these techniques allow rapid iteration toward an optimal material, testing hundreds of nearby compositions in the time it took to test one. Focused testing of larger, single composition samples (produced in an arc furnace or by laser sintering) provides data on structural and high-power RF properties and validates our thick-film-based workflow.

Research on classification and recognition of the skin tumors by laser ultrasound using support vector machine based on particle swarm optimization

As a common disease endangering human health, skin tumor causes millions of deaths every year. In order to effectively detect skin tumors, a laser ultrasonic detection method based on the PSO-SVM algorithm is proposed to identify and detect human skin tumors. The physical model of laser ultrasound in human skin tumors is established by FEM (finite element method), and the ultrasonic wave generated by laser in different tumor locations (the skin epidemis, the dermis and between the two layers) are analyzed in detail. The minimum value, the sample entropy, the permutation entropy and the shannon entropy of laser ultrasound are extracted as the sensitive features, and the three types of tumors are classified and identified by the SVM (support vector machine). The penalty factor C and kernel function parameters γ in SVM are optimized by the PSO(particle swarm optimization) algorithm. The simulation results show that the proposed PSO-SVM algorithm has a good classification effect on skin tumor prediction, which provides a new detection method for laser ultrasound to detect skin tumors.