The transient electromagnetic method can obtain resistivity and chargeability simultaneously in polarizable medium detection. Typically, we assume that the earth may contain a chargeable medium if the electromagnetic (EM) data appear negative values or sign reversals. Unfortunately, with barely perceptible characteristics, some EM responses with the induced polarization (IP) effects are considered to be non-polarizable responses. Insufficient understanding of features and inaccurate identification of the IP responses limits the use of the IP effects for broader purposes. For these reasons, we perform 1D forward modeling to discuss the degree of EM response affected by the IP effects and to extract polarization characteristics. To identify the IP effects, we combine partial mutual information (PMI) and the fuzzy support vector machine (FSVM) methods to complete the intelligent identification algorithm. We verify the efficiency and practicality of the algorithm by building Debye loops in field experiments. From the analysis, we distinguish the strong and weak IP effects by introducing the impact ratio. The strong IP responses manifest fast decays and sign reversals, and the weak IP responses primarily show fast decays or outward concavity. The identification algorithm validation results show that the recognition accuracy reaches 90.7%. In the field experiment verification, the Debye loop successfully simulates the IP effects of different intensity, and the identification results indicate that the algorithm has potential in the measured data. With this intelligent identification algorithm, the measurements can provide access to the weak polarizable medium when the impact ratio exceeds 30%.

The effect of magnetic viscosity (MV) has continued to be observed with the development and application of the time-domain electromagnetic method (TDEM). Field and laboratory data show that the MV effect is characterized by a −1 ± 0.4 scope power-law delay in the late stage of electromagnetic response. Research on the MV effect can improve the detection accuracy of TDEM and assist in prospecting for ferromagnetic minerals. Most of the studies are based on the Chikazumi susceptibility model and the 1-D modeling method. However, the late-stage electromagnetic response shows a −1 power-law delay, which is inconsistent with the measured data. The log-uniform distribution of relaxation time $\tau $ in the Chikazumi model is not always appropriate. This study considers the Cole–Cole susceptibility model with a log-normal distribution of relaxation time. The 3-D modeling method of the MV effect is raised based on the rational function approximation algorithm and recursive convolution technique; the control equations and iterative process were adjusted based on finite-different time-domain (FDTD) method. The effectiveness was verified via half-space and layered models; the effects of susceptibility parameters on the response were clarified; moreover, the MV effect of the 3-D anomalous model was analyzed. Our method can model the fractional propagation process of the MV effect more efficiently and help to improve the prospecting accuracy of the TDEM method under complex magnetic geological conditions.

Induced polarization (IP) effects in transient electromagnetic (TEM) measurement play a significant role in the detection of minerals, such as sulfide ore, clay ore, etc. However, due to the complex impacts caused by the polarization parameters, the structure of the earth, and the measurement system configuration, the IP effects cannot be easily measured and interpreted. We paid more attention to the vertical component of the ungrounded-TEM system in previous work; however, we will now attempt to utilize the horizontal component to enhance the precision of the measurement and interpretation. We quantitatively discussed the behavior of the horizontal and vertical magnetic fields of the towed-TEM (tTEM) system. We simultaneously introduced the vertical and horizontal components into the Jacobian matrix of the 1D laterally constrained inversion to build the joint inversion. Compared to the vertical component, the horizontal component always shows earlier and bigger sign reversals and contains more IP information. Inversion with the single horizontal or single vertical component showed poor accuracy in the deep and shallow layers, respectively. The joint inversion with both components could correct the errors. Including the horizontal component in the detection and interpretation facilitates an improved resolution for polarizable minerals.

High intensity of focused ultrasound (HIFU) is an effective tumor therapy, taking advantage of the thermal effect and cavitation effect to generate thermal damage to the target tissue. However, inaccurate ultrasonic dose control may result in ineffective or excessive treatment. Thus, real-time monitoring of the thermal damage formation process is critical. To evaluate the effectiveness of real-time monitoring of B-ultrasound, ex-vivo bovine livers were irradiated by 1.155 MHz focused ultrasound with emission time T1 of 200 ms and interval time T2 of 200 ms. For orthogonal experiments, ultrasound was irradiated at sound power of 100 W, 125 W, and 150 W for 10 s, 20 s, and 40 s, respectively. B-ultrasound image sequences are collected using a 7.5 MHz linear array and compared with backscattered echo signals and thermal damage slices, respectively, to build relationships between B-mode ultrasound monitoring and thermal effect or cavitation effect. The experimental results demonstrated that the tissue ablation process caused by thermal effect cannot be effectively monitored using B-ultrasound, but the process caused by the cavitation effect can. The analysis revealed a strong temporal correlation between the appearance of bright spots in B-ultrasound images and the sudden increase of the scattered echo power spectrum, which were caused by a large number of micro-bubbles from cavitation. The damaged cavity structure of the slices and the development trend of micro-bubbles showed a strong spatial correlation. Furthermore, the sudden increase in the scattered echo signal shows the potential of early warning of cavitation, as it is 1.2–2.0 s ahead of the bright spot in the B-ultrasound image, laying the experimental basis for improving the effectiveness of B-ultrasound monitoring in clinical HIFU surgery.

The detection and quantitative evaluation of internal defects in polymer materials are critical for practical engineering applications. This paper introduces a method for the quantitative evaluation of defects in polymer materials using the ultra-sound thermal effect. Initially, a heat generation model for polymer materials under ultrasonic excitation is developed, and based on heat conduction theory, the mechanism by which defect characteristics affect the temperature distribution in infrared images is examined. A hybrid simulation and experimental approach is employed to analyze the variation patterns of infrared images on the surfaces of materials with various defects under the ultrasound thermal effect. A method is proposed to accurately assess the size and location of defects by measuring the width of the opening and the deepest concave point in the anomalous regions of infrared images. Local image frequency variations are assessed through normalized local gradients and variance, while an adaptive fractional-order model is developed to enhance the images. Morphological operations are employed to reconstruct grayscale images, with the resulting images serving as foreground markers for subsequent segmentation using the watershed algorithm. The convex hull algorithm is utilized to compute the width of the opening and the location of the deepest concave point in the infrared images, thereby facilitating quantitative defect analysis. This approach offers a novel perspective for the quantitative evaluation of internal defects in polymer materials.

Magnetic induction tomography (MIT) has the advantages of being non-invasive, non-contact, and low-cost, and is widely used in multiple fields and the biomedical field. However, most traditional MIT systems use detection coils as magnetic field sensors, which have low detection sensitivity, magnetoelectric (ME) sensors composed of magnetostrictive materials and piezoelectric materials have the advantages of high sensitivity, wide bandwidth, and small volume. In this paper, a double excitation coil eddy current magnetic induction detection model used for MIT system is established. The variations of the excitation magnetic field, the induced magnetic field, and the phase shift with the thickness and conductivity of the saline are numerically calculated. A low conductivity medium detection module with a minimum magnetic field detection limit lower than 20 pT in the range of 15 MHz - 30 MHz is constructed using a ME sensor, its phase shift noise is lower than (6×10⁻⁵)°, the conductivity and volume changes of the saline are detected. This double excitation coil eddy current magnetic induction detection model based on ME sensors has high sensitivity, low phase shift noise, and small volume, providing a fresh perspective for MIT biomedical imaging.