Hongwei Hu

Automatic ultrasonic inspection of flaws in a propeller-blade

Ultrasonic technique is very promising for non destructive inspection. In this paper, a method is presented on automatic ultrasonic inspection of defects in a propeller-blade without computer aided design (CAD) models. The 3D surface data are obtained by ultrasonic measurement, and then the inspection path is planned after the CAD model has been reconstructed. A C-scan image is obtained in real-time ultrasonic automatic inspection. Thereafter, defective area and sound area are separated through binarisation of the C-scan image, and an auxiliary table is used to segment defects in order that defects are disconnected to each other. Then, an algorithm based on edge element is proposed, simplifying the process of extracting edge. Finally, application of these procedures for inspecting a propeller-blade is demonstrated.

Modeling linear Rayleigh wave sound fields generated by angle beam wedge transducers

In this study, the reciprocity theorem for elastodynamics is transformed into integral representations, and the fundamental solutions of wave motion equations are obtained using Green’s function method that yields the integral expressions of sound beams of both bulk and Rayleigh waves. In addition to this, a novel surface integral expression for propagating Rayleigh waves generated by angle beam wedge transducers along the surface is developed. Simulation results show that the magnitudes of Rayleigh wave displacements predicted by this model are not dependent on the frequencies and sizes of transducers. Moreover, they are more numerically stable than those obtained by the 3-D Rayleigh wave model. This model is also applicable to calculation of Rayleigh wave beams under the wedge when sound sources are assumed to radiate waves in the forward direction. Because the proposed model takes into account the actual calculated sound sources under the wedge, it can be applied to Rayleigh wave transducers with diffe...

Acoustic emission detection for mass fractions of materials based on wavelet packet technology

Materials are often damaged during the process of detecting mass fractions by traditional methods. Acoustic emission (AE) technology combined with wavelet packet analysis is used to evaluate the mass fractions of microcrystalline graphite/polyvinyl alcohol (PVA) composites in this study. Attenuation characteristics of AE signals across the composites with different mass fractions are investigated. The AE signals are decomposed by wavelet packet technology to obtain the relationships between the energy and amplitude attenuation coefficients of feature wavelet packets and mass fractions as well. Furthermore, the relationship is validated by a sample. The larger proportion of microcrystalline graphite will correspond to the higher attenuation of energy and amplitude. The attenuation characteristics of feature wavelet packets with the frequency range from 125 kHz to 171.85 kHz are more suitable for the detection of mass fractions than those of the original AE signals. The error of the mass fraction of microcrystalline graphite calculated by the feature wavelet packet (1.8%) is lower than that of the original signal (3.9%). Therefore, AE detection base on wavelet packet analysis is an ideal NDT method for evaluate mass fractions of composite materials.

Evaluating grain size in polycrystals with rough surfaces by corrected ultrasonic attenuation

HIGHLIGHTSWe study the effects of diffraction and surface roughness on ultrasonic attenuation.The MGB model is used to formulate the diffraction correction coefficient.We develop an approximate inverse function of Weavers model.Grain size evaluation results reveal the better accuracy of the presented method. ABSTRACT Surface roughness of a sample has a great effect on the calculated grain size when measurements are based on ultrasonic attenuation. Combining modified transmission and reflection coefficients at the rough interface with a Multi‐Gaussian beam model of the transducer, a comprehensive correction scheme for the attenuation coefficient is developed. An approximate inverse model of the calculated attenuation, based on Weavers diffuse scattering theory, is established to evaluate grain size in polycrystals. The experimental results showed that for samples with varying surface roughness and matching microstructures, the fluctuation of evaluated average grain size was ±1.17 &mgr;m. For polished samples with different microstructures, the relative errors to optical microscopy were no more than ±3.61%. The presented method provides an effective nondestructive tool for evaluating the grain size in metals with rough surfaces.

Experimental investigation of material nonlinearity using the Rayleigh surface waves excited and detected by angle beam wedge transducers

HIGHLIGHTSNonlinear Rayleigh wave beams generated by ABW transducers is verified experimentally.The driving‐level dependence nonlinear wave distributions are observed and explained.A method to determine the source nonlinearity and attenuation coefficients is proposed.Material nonlinearity can be characterized using nonlinear Rayleigh waves. ABSTRACT Angle beam wedge transducers are widely used in nonlinear Rayleigh wave experiments as they can generate Rayleigh wave easily and produce high intensity nonlinear waves for detection. When such a transducer is used, the spurious harmonics (source nonlinearity) and wave diffraction may occur and will affect the measurement results, so it is essential to fully understand its acoustic nature. This paper experimentally investigates the nonlinear Rayleigh wave beam fields generated and received by angle beam wedge transducers, in which the theoretical predictions are based on the acoustic model developed previously for angle beam wedge transducers [S. Zhang, et al., Wave Motion, 67, 141–159, (2016)]. The source of the spurious harmonics is fully characterized by scrutinizing the nonlinear Rayleigh wave behavior in various materials with different driving voltages. Furthermore, it is shown that the attenuation coefficients for both fundamental and second harmonic Rayleigh waves can be extracted by comparing the measurements with the predictions when the experiments are conducted at many locations along the propagation path. A technique is developed to evaluate the material nonlinearity by making appropriate corrections for source nonlinearity, diffraction and attenuation. The nonlinear parameters of three aluminum alloy specimens – Al 2024, Al 6061 and Al 7075 – are measured, and the results indicate that the measurement results can be significantly improved using the proposed method.

Ultrasonic Phased Array Sparse-TFM Imaging Based on Sparse Array Optimization and New Edge-Directed Interpolation

The ultrasonic phased array total focusing method (TFM) has the advantages of full-range dynamic focusing and high imaging resolution, but the problem of long imaging time limits its practically industrial applications. To reduce the imaging calculation demand of TFM, the locations of active array elements in the sparse array are optimized by combining almost different sets with the genetic algorithm (ADSGA), and corrected based on the consistency of the effective aperture with the equivalent point diffusion function. At the same time, to further increase the imaging efficiency, a sparse-TFM image with lower resolution is obtained by reducing the number of focus points and then interpolated by the new edge-directed interpolation algorithm (NEDI) to obtain a high quality sparse-TFM image. Compared with TFM, the experimental results show that the quantitative accuracy of the proposed method is only decreased by 1.09% when the number of sparse transmitting elements reaches 8 for a 32-element transducer, and the imaging speed is improved by about 16 times with the same final pixel resolution.

Weld defect classification using 1-D LBP feature extraction of ultrasonic signals

Abstract A method based on the one-dimensional local binary pattern (1-D LBP) algorithm to extract features of ultrasonic defect signals and perform multi-class defect classification was proposed. The ultrasonic defect echo signals were first decomposed into wavelet coefficients by the wavelet packet decomposition. The 1-D LBP algorithm was employed to extract LBP features of components at low and high frequencies, respectively. Subsequently, these LBP statistical feature sets were regarded as feature vectors of defect classification. Weld defects were then classified automatically by using the radial basis function support vector machine. Defects of slag inclusion, porosity and incomplete penetration in a steel plate butt weld were used for experiments and feature extraction and defect classification were performed. The results show that the class separability of 1-D LBP features used for defect classification is superior to that of the traditional features. Moreover, the accuracy of defect classification reached 98.3%, providing an efficient tool for ultrasonic defect classification.

An Efficient Ultrasonic SAFT Imaging for Pulse-Echo Immersion Testing

An ultrasonic synthetic aperture focusing technique (SAFT) using a root mean square (RMS) velocity model is proposed for pulse-echo immersion testing to improve the computational efficiency. Considering the immersion ultrasonic testing of a steel block as an example, three kinds of imaging were studied (B-Scan, SAFT imaging based on ray tracing technology and RMS velocity). The experimental results show that two kinds of SAFT imaging have almost the same imaging performance, while the efficiency of RMS velocity SAFT imaging is almost 25 times greater than the SAFT based on Snell’s law.