The line laser scanning thermography was applied for the defect detection and evaluation of composite material in this work, which was carried out by the following procedures. First, a novel contrast enhancement method by homomorphic technology was proposed and validated by a case study. Then, a specimen containing 12 prefabricated defects was detected using line laser scanning thermography and the obtained thermal image sequence and changeable temperature were analyzed. Finally, the defect area was obtained via such thermal image processing as contrast enhancement based on the proposed method, threshold segmentation and quantitative evaluation. The obtained results show that the composite material defects with a depth of less than 4 mm can be detected using line laser scanning thermography but that with a depth of less than 3 mm can be evaluated quantitatively with a small error less than 10%.

In order to extract and enhance the weak fault feature of rolling element bearings in strong noise conditions, the Empirical Wavelet Transform (EWT) is improved and a novel fault feature extraction and enhancement method is proposed by combining the Maximum Correlated Kurtosis Deconvolution (MCKD) and improved EWT method. At first, the MCKD method is conducted to de-noise the signal by eliminating the non-impact components. Then, the Fourier spectrum is segmented by local maxima or minima in the envelope of the amplitude spectrum with a pre-set threshold based on the noise level. By building up the wavelet filter banks based on the spectrum segmentation result, the signal is adaptively decomposed into several sub-signals. Finally, by choosing the most meaningful sub-signal with the maximum kurtosis, the fault feature can be extracted in the squared envelope spectrum and teager energy operator spectrum of the chosen component. Both simulations and experiments are performed to validate the effectiveness of the proposed method. It is shown that the spectrum segmentation result of improved EWT is more reasonable than the traditional EWT in strong noise conditions. Furthermore, compared with commonly used methods, such as the Fast Kurtogram (FK) and the Optimal Wavelet Packet Transform (OWPT) method, the proposed method is more effective in the fault feature extraction and enhancement of rolling element bearings.

Nonlinear vibration plays a vital role in ultrasonic infrared thermography testing due to contact-collision effect between a horn and sample, and the effects of contact roughness and sample mass on vibration characteristics of a horn-sample system are deeply investigated in this paper. A two-degree-of-freedom dynamic model based on GW contact model is proposed for exploring the vibration characteristics of a horn-sample system. Then, the vibration characteristics of the horn and sample are calculated under different contact roughness and different sample mass. The results demonstrate that the contact roughness does not influence vibration characteristic of horn, but there are mainly $2f$ and $3f$ except the first harmonic $f$ in velocity responses of the sample. Besides, the amplitude of sample velocity increases with the increase of real contact area as the contact interface is smoother, and there is a 1.8-fold approximate relation in the three amplitude of harmonic $f$ under different contact roughness. On the other hand, with the increase of sample mass, the harmonic $f$ becomes the main component and higher harmonics decreases little by little. This work will be extraordinarily meaningful to optimize testing parameters and evaluate surface quality of sample in ultrasonic infrared thermography testing.

This study develops a computational framework for evaluating the residual strength of tungsten-copper functionally graded materials following crack-arrest hole drilling. The proposed methodology features two pivotal innovations: First, a phase-field isoparametric gradient elements is established through representing the gradient effect within the finite element stiffness matrices, incorporating both Amor and Miehe elastic energy decomposition schemes to address tension-compression asymmetry in crack evolution. Second, a multi-fidelity neural network strategy is integrated with the gradient phase-field element to mitigate characteristic length dependency in residual strength predictions. Comparative analyses demonstrate that the gradient finite element achieves smoother field transitions at element interfaces compared to conventional homogeneous elements, as quantified in both stress and damage fields. The Miehe decomposition scheme outperforms the Amor model in capturing complex crack trajectories. Validation against the average strain energy criterion indicates the present approach enhances residual strength prediction accuracy by 39.07% to 44.05%, establishing a robust numerical tool for damage tolerance assessment in graded materials.

The internal thermal insulation structure serves as a vital subsystem within the thermal insulation system of high-temperature devices, playing a crucial role in effectively maintaining a high-temperature environment, reducing energy consumption, and enhancing testing efficiency. However, during the operation of these devices, the internal thermal insulation structure is inevitably subjected to high temperatures. Therefore, it is essential to focus on the heat transfer performance of this structure. Initially, the internal thermal insulation structure is designed, and the relative dimensions and materials of each component are determined. Subsequently, a finite element model of the internal thermal insulation structure is established, and numerical simulations of heat transfer are conducted under the device’s operating conditions to analyze the thermal insulation structure. This analysis is ultimately validated through high-temperature experiments conducted on specimens of the internal thermal insulation structure. The results indicate that the designed internal thermal insulation structure effectively maintains the high-temperature environment within the device and demonstrates excellent thermal insulation performance, with a maximum heat flux of 66.7 W/m² and an outer wall surface temperature of 25.98 °C. This work is significant as it lays the groundwork for the design and construction of such devices.