Multilayer complex structures are widely used in the energy and power industries. However, due to the combined effects of multiple media layers and complex curved surfaces, using phased array ultrasonic inspection to check their internal structures and defects is still extremely challenging. This article proposed a two-stage array ultrasonic method for the inspection of internal structures. In the first stage, a low-frequency full waveform inversion (FWI) was used to characterize the complicated internal structure, overcoming the challenge of a priori velocity estimation while improving computational efficiency by 75% compared to full-spectrum FWI. In the second stage, a nonlinear synthetic focusing imaging method was utilized to achieve high-resolution imaging of internal defects. To further reduce the computation time for beam path estimation, an Eikonal equation-based method was introduced. The proposed method improves computational efficiency by approximately 96.85% and 93.93% compared to the traditional binary search and Fermat's principle-based shortest path algorithms, respectively. Experimental results demonstrated that the proposed method can effectively detect internal defects within multilayer complex structures. Compared with the conventional array ultrasonic full focusing method, the global contrast index (C-G) value increased by 2.87 times, while the array performance indicator (API) value decreased by 88.73%.

The aerospace industry extensively utilizes carbon fiber-reinforced plastic (CFRP) materials due to their high strength and low density. A reliable non-destructive testing technology that can efficiently measure and detect internal flaws, such as delamination, in the L-shaped structure of CFRP material is crucial to ensure the safety and reliability of aircraft structures. While conventional ultrasonic testing has limited efficiency, array ultrasonic full-focus imaging detection technology depends on precise sound propagation delay. To address the challenge of calculating sound wave delay caused by anisotropy and multi-layer refractive interfaces within the CFRP materials, a sound ray tracing technique employing the “Viterbi search algorithm” is proposed. This technique is employed to compute the time delay of array ultrasonic full-focus imaging detection. The heuristic delay-and-sum beamforming Total Focusing Method (TFM) is selected to generate a fully focused image of the L-shaped CFRP structure. The TFM imaging prerequisite is to compute ultrasonic ray paths that are challenging due to the multilayered structure, elastic anisotropy, and curved geometry. The results of this study would prove beneficial in enhancing testing methods and guiding accurate imaging procedures based on the TFM method.

A non-contact residual stress measurement method for thin composite laminates based on the phase velocity of the air-coupled ultrasonic guided wave has been proposed in the study. In the method, ultrasonic signals of the guided wave in composite have been captured through the variable distances between the transmitter and the receiver of air-coupled ultrasonic. Actual acquired ultrasonic signals at different positions have been processed by Butterworth bandpass filter and the interpolation algorithm using discrete Fourier transform method, followed by the acoustic time extraction. The guided wave acoustic time difference and the phase velocity have been calculated through the successive difference method to characterise residual stresses, which can avoid the effect of unknown difference of air gaps between transducers and composite laminates. Theoretical analysis and finite element models for ultrasonic wave fields of composites have been developed to acquire the whole guided wave propagation process. The effects of the excitation centre frequency of the transducer, incident angle, and in-plane propagation distance on the signal-to-noise ratio of the guided wave have been investigated and optimal parameters have been designed for residual stress measurement of thin-walled composite laminates according to the numerical results. Stress calibration experiments have been conducted by applying several known tensile stresses with tensile testing machine. Experimental results demonstrated strong linear correlations between phase velocities and applied stresses in the range of 0-90 MPa for composite specimens with different orientations. The standard deviation of acoustic time is less than 0.078 mu s. The mean absolute error of phase velocities versus applied stresses is within 2.7 m/s corresponding to the stress prediction deviation of 14 MPa, validating the feasibility of the proposed residual stress measurement method.

Power and aerospace industries widely utilised multilayered complex structures. However, ultrasonic phased array inspection of internal defects in such components remains a significant challenge due to the combined effects of multiple media and complex interfacial boundaries. This paper proposes an extended non-stationary phase shift method (ENPSM), which applies circular statistical vector factor (CSVF) weighting algorithm. The instantaneous phase of full matrix capture (FMC) data is obtained via the Hilbert transform, and cosine and sine components are used to construct CSVF in the frequency domain to evaluate phase consistency. The emission and reception wavefields were extended and extrapolated using a wave velocity distribution window. This process enabled the reconstruction of both the transmitted and received wavefields, including their cosine and sine components. The cross-correlation imaging condition is finally applied to convert the wavefields into a defect image. Experiments show improved performance over total focusing method (TFM), with 2.45 fold increase in global contrast index (CG), 73.66% array performance indicator (API) reduction, and 22.98% lower computation time.

The acoustic characteristics of coarse-grained metal materials are complex due to the coarse grain,anisotropy,and non-uniformity.Ultrasonic testing has a poor signal to noise ratio because of severe waveform distortion,energy attenuation,and structural scattering that occur when ultrasonic waves propagate inside it.To investigate the propagation law of ultrasonic waves in coarse-grained materials and provide theoretical guidance for the ultrasonic testing scheme,a finite element simulation modeling method for ultrasonic testing of coarse-grained materials was proposed.A two-dimensional grain model of the material was generated based on the Voronoi diagram algorithm.The anisotropic orientation of the grains was defined through the form of the material elasticity tensor.A finite element acoustic simulation method that enables parametric calculations was established.The simulation modeling research was carried out in terms of both acoustic attenuation and full matrix capture(FMC).A simulation model of the acoustic attenuation measurement of nickel-based high-temperature alloy GH4169 was established.A comprehensive matrix capture data acquisition simulation model was developed for titanium alloys using additive manufacturing,and the acoustic attenuation patterns of ultrasonic waves of various frequencies at various anisotropy indexes and grain sizes were simulated and examined.The signal-to-noise ratios of total focusing method(TFM)imaging at different anisotropy indexes and different detection directions were simulated and analyzed.The phase coherence factor(PCF)denoising imaging was performed on the TFM imaging results of flat bottom hole defects.The signal-to-noise ratio of simulated and experimental flat bottom hole defects is improved by 23.52 dB and 24.72 dB,respectively.GH4169 specimens with different average grain sizes were prepared by heat treatment.The simulation approach's validity is confirmed by the results of the acoustic attenuation measurement experiments conducted on GH4169 specimens and the TFM imaging studies conducted on a titanium alloy specimen employing additive manufacturing.

The growing use of multilayer components in manufacturing demands precise inspection methods. Ultrasonic phased array imaging with full matrix capture (FMC) offers effective structural characterization. However, its application to multilayer media is fundamentally constrained by the accuracy of sound velocity measurements. This paper introduces an ultrasonic phased array full matrix imaging method based on frequency domain full waveform inversion, which achieves precise reconstruction of the internal geometries characterization of multilayer structures by only utilizing the sound velocity of the outermost medium. Through an iterative optimization process, the initial sound velocity is progressively refined to minimize the discrepancy between simulated and experimental FMC datasets, thereby ensuring the simulated sound velocity closely approximates the actual conditions. This innovative method achieves robust reconstruction of internal geometries by eliminating the traditional requirement for accurate sound velocity measurements. The influence of unknown wavelets on internal geometries reconstruction was suppressed effectively by applying Green's function in the objective function. Furthermore, a novel pseudo-Hessian matrix incorporating Green's function correction is derived to enhance illumination compensation in deeper regions of the component. The experiments and simulations of different designs of three-layer medium complex structures were conducted, in which the proposed method provided substantially improved visualization of internal features. The structural similarity (SSIM) was increased 1.6 times higher than the conventional techniques, and the root mean square error (RMSE) of geometric dimensional measurements was reduced by more than 30 %.

The coarse columnar grain structure in titanium alloys processed by additive manufacturing leads to strong grain noise in ultrasonic testing, which affects the accurate detection and quantification of its defects. In this paper, a self-adaptive denoising imaging method for ultrasonic array testing is proposed based on variational mode decomposition (VMD). The proposed method uses VMD to decompose complex ultrasonic signals in full matrix capture (FMC) data collected by a linear ultrasonic array transducer. According to the particle swarm optimization (PSO) method, VMD parameters for FMC methods of the total focusing method (TFM), the plane wave imaging (PWI), and the Hadamard spatial encoding are self-adaptively determined. The evaluation parameters are set to select the intrinsic mode function components by VMD to complete the denoising reconstruction and imaging of FMC data. An additive-manufactured titanium alloy specimen was used to verify the improvement of defect detection capability by PSO-VMD denoising method. For a defect at large thickness in the specimen, compared with the conventional TFM and PWI methods, VMD denoising method based on the Hadamard spatial encoding can improve the signal-to-noise ratio by 7.7 dB and 9.0 dB, and reduce the quantitative error by 74 % and 68 %.

The adaptive ultrasonic array imaging can be used for defects detection with unknown sample profile. To solve the problems of low computational efficiency and difficult quantitative evaluation in detection, this paper presents a high efficiency adaptive ultrasonic array imaging method with sensitivity correction. For surface reconstruction, the vector coherence technique has been used to correct the plane wave imaging of sample surface with single emission, which improves the imaging quality and efficiency. A robust fitting method is proposed based on Random Sample Consensus algorithm to reconstruct the surface after the surface pixel recognition. To reduce the beam path calculation time, a prediction search method is developed, whose time consumption is reduced by 97.2 % compared with the global traversal method with the same results. The sensitivity correction algorithm is proposed based on the ultrasonic propagation model, which makes the amplitude difference of defects in different regions is less than 0.8 dB.

Abstract Carbon-fiber reinforced plastics (CFRP) are increasingly used in the aerospace industry. Wrinkles are common defects of complex curved CFRP parts, severely damaging the mechanical performance. The ultrasonic technique is an effective tool for detecting wrinkle defects in complex curved CFRP parts in the aerospace industry. We propose a Sobel-enhanced total focusing method using an ultrasonic linear array transducer for detecting wrinkles in multidirectional CFRPs. The total focusing method (TFM) imaging wrinkles loses some ply geometry information due to the non-zero local mean when extracting the cosine of the instantaneous phase of a synthetic depth trace from its associated analytic signal for amplitude normalization. The proposed Sobel-enhanced TFM method combines the aperture-angle limitation and the vertical Sobel operator to relieve the non-zero local mean in this paper. The proposed method can extract almost all ply geometry information of a 32-ply CFRP sample when the limited angle, θ max = 10° or 5°.

Abstract Metal materials with coarse-grained structures have the characteristics of coarse grain, acoustic anisotropy, and structural inhomogeneity. When the ultrasonic wave propagates in its interior, the above characteristics will cause strong waveform distortion, acoustic energy attenuation, and structural-acoustic scattering, resulting in a poor signal-to-noise ratio of the ultrasonic echo signal. The annular array ultrasonic transducer has a three-dimensional axisymmetric acoustic field, which is less affected by the grain structure than the linear array ultrasonic transducer. It can realize the focus within the detection range by the total focusing method (TFM) post-processing in the way of the full matrix capture (FMC) and is suitable for ultrasonic non-destructive testing of coarse-grained materials with high acoustic attenuation. In this paper, a TFM C-scan testing method based on the phase coherence factor (PCF) denoising is proposed. The C-scan imaging results of the coarse-grained GH4169 specimen verify the denoising effectiveness of the proposed method. Compared with the TFM of the annular array, the PCF can improve the signal-to-noise ratio of the flat bottom hole defect by up to 14.99 dB.

Dicentric chromosome analysis is the gold standard for biological dose assessment. To enhance the efficiency of biological dose assessment in large-scale radiation catastrophes, automatic identification of dicentric chromosome images is a promising and objective method. In this paper, an automatic identification method for dicentric chromosome images using two-stage convolutional neural network is proposed based on Giemsa-stained automatic microscopic imaging. To automatically segment the adhesive chromosome masses, a k-means based adaptive image segmentation and watershed segmentation algorithm is applied. The first-stage CNN is used to identify the dicentric chromosome images from all the images and the second-stage CNN works to specifically identify the dicentric chromosome images. This two-stage CNN identification method can effectively detects chromosome images with concealed centromeres, poorly expanded and long-armed entangled chromosomes, and tricentric chromosomes. The novel two-stage CNN method has a chromosome identification accuracy of 99.4%, a sensitivity of 85.8% sensitivity, and a specificity of 99.6%, effectively reducing the false positive rate of dicentric chromosome. The analysis speed of this automatic identification method can be 20 times quicker than manual detection, providing a valuable reference for other image identification situations with small target rates.

Carbon fiber-reinforced polymers (CFRP) are extensively used in aerospace applications. Out-of-plane wrinkles frequently occur in aerospace CFRP parts that are commonly large and complex. Wrinkles acting as failure initiators severely damage the mechanical performance of CFRP parts. Wrinkles have no significant acoustic impedance mismatch, reflecting weak echoes. The total focusing method (TFM) using weak reflection signals is vulnerable to noise, so our primary work is to design discrete-time filters to relieve the noise interference. Wrinkles in CFRP composites are geometric defects, and their direct detection requires high spatial precision. The TFM method is a time-domain delay-and-sum algorithm, and it requires that the time information of filtered signals has no change or can be corrected. A linear phase filter can avoid phase distortion, and its filtered signal can be corrected by shifting a constant time. We first propose a wrinkle detection method using linear phase FIR-filtered ultrasonic array data. Linear phase filters almost do not affect the wrinkle geometry of detection results and can relieve noise-induced dislocation. Four filters with different bandwidths have been designed and applied for wrinkle detection. The 2 MHz bandwidth filter is recommended as an optimum choice.

Ultrasonic testing is an important non-destructive testing method, which is sensitive to the defects in the diffusion bonding interface. Ultrasonic testing of diffusion bonding interfaces in complex-surface components is a challenge due to the geometry and the weak echo signal of the diffusion bonding defects. This paper proposes an interfacial stiffness characterization method based on the spring model for the ultrasonic testing of the diffusion bonding interface of titanium alloy complex-surface component. Finite element models for ultrasonic field are established to analyze the diffusion bonding defects response, the effect of complex surface, and the inconsistency of the bonding interface depth in ultrasonic testing of the titanium alloy complex-surface component. 15 MHz is recommended as the testing frequency of the diffusion bonding interface. Ultrasonic C-scan experiments are conducted using specimens with embedded artificial defects and a titanium alloy complex-surface component. The simulation and experimental results show that the novel interfacial stiffness characterization method can be applied to ultrasonic testing of the diffusion bonding interface (inclination angle less than 14°) in complex-surface components, and the ability to test defects at the diffusion bonding interface can be improved.

针对碳纤维增强树脂基复合材料层压板结构超声检测中存在的信噪比差、检测效率低等问题，设计基于线性阵列和环形阵列换能器的超声检测方法和工艺，研究分析这两种换能器对复合材料层压板的检测效果。首先，制备预置有不同埋深分层缺陷的复合材料梯度平板试样，并基于有限差分仿真模型探究了复合材料平板结构中的超声传播特性。然后，依据材料的声学各向异性特征，对采用线阵和环阵换能器的超声检测成像算法进行修正，并制订检测工艺。最后，利用线阵和环阵换能器对试样进行C扫描超声检测成像，并结合声场特征，定性和定量地分析其检测结果。试验结果表明，采用线阵换能器可在具有较高信噪比的同时，对厚度较小（≤10 mm）的复合材料平板试样实现高效率检测，而环阵换能器对厚度较大的平板试样具有更高的检测精度以及更小的成像畸变。研究成果可为复合材料检测的声学表征提供理论依据，并为阵列超声检测的工艺方法设计提供有效参考和指导。

Wrinkles in carbon fiber reinforced plastics (CFRP) degrade the mechanical performance. The numerical study on wrinkles requires internal structural point cloud for the meso-structure reconstruction. This paper explores the ultrasonic location estimation with the phase-shift reference pulse for the point-cloud acquisition. The point-cloud acquisition using pulse-echo signals is a time-delay estimation which is a multi-reflection and multi-delay problem. We theoretically simplify the multi-reflection problem as a single-reflection problem and propose a normalized-cross-correlation-peaks (NCCPeaks) method for the multi-delay problem. The proposed method can eliminate some amplitude decrease and balance the smearing and frequency-dependent effects. Simulation shows that the proposed method has the maximum detectable depth without missing inter-ply estimations and a stronger noise resistance than the instantaneous phase method. An experiment is implemented on the 32-ply CFRP sample with an induced wrinkle. The estimation results of the instantaneous phase and NCCPeaks methods are almost the same at the first thirteenth layers. After the thirteenth layer, the NCCPeaks method has a stabler estimation and lower false estimation index than the instantaneous phase method.

Accurate non-destructive testing and evaluation of cracks is important for the quality assurance and life-cycle management of key components in aerospace and energy industries. This paper presents a novel imaging method for cracks detection in complex curved structure , combining virtual source technique, multi-mode total focusing method and phase coherence imaging method. The virtual source on the sample surface is employed as the emitter and receiver for the ultrasonic array imaging. In this way, the calculation complexity of imaging algorithm due to beam path search can be reduced, and the detection sensitivity in the region of interest can be improved. In addition, the phase coherence factor is used to suppress the background noise and imaging artifacts, which significantly improves the quality of ultrasonic array imaging. A complex curved sample with variable thickness and non-developable surface was used to examine the effectiveness of the virtual source total focusing method. The signal-to-noise ratio of the crack defect is increased by more than 25 dB using the novel method compared with that of the conventional total focusing method, and the quantitative evaluation error of defect is less than 2.67%.

A novel dual array inspection method for detecting the diffusion bonding defects of superalloy turbine disk has been proposed in this study. The influence of relative position between the planar defect and acoustic source has been analysed, and based on which, the transmission and reception algorithm for the dual array method has been proposed. The time delay law of the dual array transducer for the complex turbine disk structure has been investigated. Finite-difference time-domain theory has been used to establish the numerical model of the dual array method. In the numerical simulations, the novel method has been applied for the superalloy turbine disk specimen with prefabricated defects at the depth of 18.3 m and 28.3 mm. Furthermore, the corresponding experiment has been conducted and verifies the reliability of the simulation. The novel method shows advantages in detecting small diffusion bonding defects in complex structure, assisting the manufacture of superalloy turbine disks, and ensuring the safety of aircrafts.

Cytokinesis block micronucleus (CBMN) assay is a widely used radiation biological dose estimation method. However, the subjectivity and the time-consuming nature of manual detection limits CBMN for rapid standard assay. The CBMN analysis is combined with a convolutional neural network to create a software for rapid standard automated detection of micronuclei in Giemsa stained binucleated lymphocytes images in this study. Cell acquisition, adhesive cell mass segmentation, cell type identification, and micronucleus counting are the four steps of the software's analysis workflow. Even when the cytoplasm is hazy, several micronuclei are joined to each other, or micronuclei are attached to the nucleus, this algorithm can swiftly and efficiently detect binucleated cells and micronuclei in a verification of 2000 images. In a test of 20 slides, the software reached a detection rate of 99.4% of manual detection in terms of binucleated cells, with a false positive rate of 14.7%. In terms of micronuclei detection, the software reached a detection rate of 115.1% of manual detection, with a 26.2% false positive rate. Each image analysis takes roughly 0.3 s, which is an order of magnitude faster than manual detection.

With the increase of personalized customization and collaborative production requirements, more and more manufacturing enterprises virtualize and publish their resources and capabilities as cloud services for sharing. However, due to the lack of a general modelling method in the sharing process, data cannot be interpenetrated among different life cycle stages. Also, models built in a lifecycle stage cannot be transformed and propagated to other stages. To alleviate these drawbacks, in this paper, a novel service model transformation method based on product lifecycle is designed and developed to model and transform manufacturing services among different life cycle stages efficiently and accurately. Specifically, based on the discussion of the business model of life cycle service in cloud manufacturing environment, a novel service model transformation method which includes general and view service transformation is proposed and elaborated. Then, the life cycle service model is established mathematically, and eight transformation operators are summarized and their mathematical definitions are given in detail. Meanwhile, the transformation logic process and change propagation are studied. The proposed method is superior to previous methods in that: 1) the model established in this paper is a generic model which can run through different life cycle stages, including both general and personalized data; 2) the eight operator definitions cover most of the operation types in the model transformation process, which greatly improves the operability of the model automatic transformation; 3) the establishment of change propagation mechanism ensures the accuracy of model synchronization when data changes. The successful application in an instrument enterprise demonstrates the rationality and effectiveness of the proposed methodology.

Revealing the interactions of sound waves with both SiC particles and internal defects is crucial for facilitating the detectability of internal defect features in SiCp/Al by using ultrasonic testing (UT). In the present work, we demonstrate the feasibility of UT of internal flat-bottom holes with diameters ranging from 0.2 mm to 2 mm in SiCp/Al composites through the combination of finite element (FE) simulations and experiments. Specially, a 2D FE model of UT of SiCp/Al with consistent geometrical features of SiC particles with experimental one is established, the accuracy of which is validated by theoretical and experimental characterizations of P-wave velocity and ultrasonic attenuation coefficient of SiCp/Al. Subsequently, the propagation behavior of sound waves in the SiCp/Al specimen with pre-existing defects under UT, in particular the impact of defect boundary on the scattering behavior of sound waves, is revealed in detail by FE simulations and also validated by corresponding experiments. Furthermore, the UT limit of detectable size of the internal defects is revealed jointly by FE simulations and experiments, based on which a correlation map between defect size and echo signal amplitude is established. Current study provides theoretical and practical guidance for the UT of internal defects in SiCp/Al composites.