Numerical and analytical study for ultrasonic testing of internal delamination defects considering surface roughness

Analytical and numerical modeling of nonlinear lamb wave interaction with a breathing crack with low-frequency modulation

To characterize fatigue crack, an analytical calculation and finite element (FE) simulation of Lamb wave propagating through the region of a breathing crack in a two-dimensional(2D) isotropic plate were studied. Contact surface boundary conditions between the two surfaces of the vertical crack were considered to study contact acoustic nonlinearity (CAN) from the breathing contact crack in conjunction with the modal decomposition method, Fourier transform, and variational principle-based algorithm. Reflection and transmission coefficients in the fundamental frequency and second harmonic frequency were calculated and analyzed quantitatively. Different ratios of incident wave amplitude to crack width were studied to calculate CAN results related to micro-crack width. In addition, a low-frequency (LF) vibration(10 Hz) excitation was introduced to perturb the free surface vertical crack to close, and an interrogating Lamb wave(1 MHz) was used to study crack-related CAN in different conditions for interpreting the modulation mechanism. The contact boundary conditions between two surfaces of vertical crack were set which were dynamically changed due to the low frequency modulation. The clapping effects when the crack closed due to the modulation of the contact boundary conditions between the crack surfaces were studied and analyzed to get the quantitative correlation between CAN and LF modulation. The results obtained from the analytical model were compared with those from the FE simulation, showing good consistency. Knowledge of these effects is essential to correctly gauge the severity of surface cracks in the plate, which can be spotlighted in its application to quantitative evaluation of micro fatigue cracks in structural health monitoring(SHM).

Perioperative Nursing Management of Patients Undergoing Laparoscopic Ovarian Cystectomy Guided by Ultrasound Imaging under Intelligent Algorithm

This study was aimed at exploring the application value of ultrasonic imaging-guided laparoscopic ovarian cystectomy after denoising by intelligent algorithms in perioperative nursing intervention of patients. In this study, convolutional downsampling was introduced to the UNet model, based on which the residual structure and Recon module were added to improve the UNet denoising model, which was applied to 100 patients who underwent ultrasound imaging-guided laparoscopic ovarian cystectomy. The patients were grouped into a control group receiving conventional nursing and an experimental group receiving perioperative nursing management. The various experimental indicators were comprehensively evaluated. The results revealed that after denoising using the improved UNet model, the ultrasound image showed no unnecessary interference noise, and the image clarity was significantly improved. In the experimental group, the operation time was 55.45 ± 6.13 days, the intraoperative blood loss was 71.52 ± 9.87 days, the postoperative exhaust time was 1.9 ± 0.73 days, the time to get out of bed was 1.2 ± 0.85 days, the complication rate was 8%, the hospitalization time was 7.3 ± 2.6 days, and the nursing satisfaction rate reached 98%. All above aspects were significantly better than those of the control group, and the differences were statistically significant (P < 0.05). In short, the improved UNet denoising model can effectively eliminate the interference noise in ultrasound and restore high-quality ultrasound images. Perioperative nursing intervention can accelerate the recovery speed of patients, reduce the complication rate, and shorten the length of stay in hospital. Therefore, it was worthy of being widely used in clinical nursing.

Non-invasive ultrasonic inspection of sludge accumulation in a pipe

Sludge accumulated inside a fluid-flowing pipe used in a chemical or semiconductor processing factory should be periodically removed to avoid flow blockage that increases undesirable pressure inside the pipe. Accordingly, it is common practice to periodically dismantle a pipe system, clean up the accumulate sludge, and reassemble. Therefore, an accurate estimation of sludge accumulation in the pipe is important to minimize the halting time of a chemical process using the system. Considering the lack of a practically efficient, non-invasive method to estimate the severity of sludge accumulation without interrupting the on-going chemical process, we propose an ultrasonic, non-invasive, real-time inspection method using a pair of ultrasonic wedge transducers installed circumferentially on the outer wall of a pipe at the same axial coordinate. To detect lowly accumulated sludge, an ultrasonic wave path from a transmitting transducer via a test pipe with accumulated sludge to a receiving transducer is carefully designed. The severity of sludge accumulation can then be determined by the amplitude of the longitudinal wave picked up by another transducer installed on the other side of the wall. We performed a series of experiments with steel and PVC pipes that are partially filled with water and sludge of different heights. The experimental results confirmed the effectiveness and practical viability of the proposed inspection method.

Numerical Study on Surface Roughness Measurement Based on Nonlinear Ultrasonics in Through-Transmission and Pulse-Echo Modes

Ultrasonic is one of the well-known methods for surface roughness measurement, but small roughness will only lead to a subtle variation of transmission or reflection. To explore sensitive techniques for surfaces with small roughness, nonlinear ultrasonic measurement in through-transmission and pulse-echo modes was proposed and studied based on an effective unit-cell finite element (FE) model. Higher harmonic generation in solids was realized by applying the Murnaghan hyperelastic material model. This FE model was verified by comparing the absolute value of the nonlinearity parameter with the analytical solution. Then, random surfaces with different roughness values ranging from 0 μm to 200 μm were repeatedly generated and studied in the two modes. The through-transmission mode is very suitable to measure the surfaces with roughness as small as 3% of the wavelength. The pulse-echo mode is sensitive and effective to measure the surface roughness ranging from 0.78% to 5.47% of the wavelength. This study offers a potential nondestructive testing and monitoring method for the interfaces or inner surfaces of the in-service structures.