Carbon fiber reinforced polymer (CFRP) materials have been widely used in aerospace and other fields because of their excellent properties such as high temperature resistance and corrosion resistance, so the nondestructive inspection technology for CFRP materials has become a hot research topic. In this paper, we propose a method based on infrared thermography and Attention U-Net algorithm to characterize the defect shape of CFRP material surface. Firstly, the CFRP surface is scanned by a line laser and the trend of its temperature distribution is recorded using an infrared thermography camera. Subsequently, temperature analysis and entropy value of image information are calculated for individual defect image blocks in order to select images with clear defect contours. Next, the Attention U-Net is used to segment the defect in the image blocks, and the defect shape is characterization. By calculating the evaluation indexes of image segmentation, the method in this paper can achieve 99.57% accuracy, 97.06% recall, 96.63% precision, and the processing time for a single image is 0.13s. Finally, the algorithm of this paper is compared with other algorithms to verify the advantages of this research in the task of detecting surface defects in CFRP materials with fast and high accuracy.

Eddy current testing (ECT) is an effective technique for evaluating depth of metal surface defects. However, in practice, evaluation primarily relies on the experience of an operator and is often carried out by manual inspection. In this article, we address the challenges of automatic depth evaluation of metal surface defects by virtual of state-of-the-art deep learning (DL) techniques. The main contributions are threefold. First, a highly integrated portable ECT device is developed, taking the advantage of an advanced field-programmable gate array (Zynq-7020 system on chip) and provides fast data acquisition and in-phase/quadrature demodulation. Second, a dataset, termed metal defects of different depths by ECT (MDDECT), is constructed using the ECT device by human operators and made openly available. It contains 48000 scans from 18 defects of different depths and liftoffs. Third, the depth evaluation problem is formulated as a time series classification problem, and various state-of-the-art 1-D residual convolutional neural networks are trained and evaluated on the MDDECT dataset. A 38-layer 1-D ResNeXt achieves an accuracy of 93.58% in discriminating the surface defects in a stainless steel sheet with depths from 0.3 to 2.0 mm in the resolution of 0.1 mm. In addition, the results show that the trained ResNeXt1D-38 model is immune to liftoff signals.

Eddy current (EC) testing has become one of the most common techniques for measuring metallic planar structures in various industrial scenarios such as infrastructures, automotive, manufacturing, and chemical engineering. There has been significant progress in measuring the geometry, electromagnetic properties, and defects of metallic planar structures based on electromagnetic principles. In this review, we summarize recent developments in EC computational models, systems, algorithms, and measurement approaches for planar structures. First, the computational models including analytical models, numerical methods, and plate property estimation algorithms are introduced. Subsequently, the impedance measurement system and probes are presented. In plate measurements, sensor signals are sensitive to probe lift-off, and various algorithms for reducing the lift-off effect are reviewed. These approaches can be used for measureing thickness and electromagnetic properties. Furthermore, defect detection for metallic plates is also discussed.

Aiming at the dynamic testing of the ignition temperature of micro-initiating explosives, a novel Pt-Rh10/Pt thin-film thermocouple was designed in this paper. The author carried out the preparation of the thermocouple by using a screen printing process on an Al₂O₃ ceramic substrate. The formed thermocouple was made of Pt-Rh10 wire and Pt wire as compensation wires, with a size of ≤ 1 mm and a thickness of about 6 μm. In the testing process, the static calibration of the thermocouple at 50~600 °C and 650~1500 °C was completed by a portable temperature verification furnace and a horizontal high temperature verification furnace, and the results showed that the Seebeck coefficient of the thermocouple was about 10.70 μV/°C, and its output voltage–temperature curve was similar to that of a standard S-type thermocouple, which achieved the effective temperature measurement up to 1500 °C. The dynamic response of Pt-Rh10/Pt thin-film thermocouple was then tested and studied using the pulsed laser method, and the results show that the time constant of the thermocouple prepared in this paper is about 535 μs, which has the characteristics of fast response and high precision high-temperature testing. Compared with the traditional thin-film thermocouple, the thermocouple has excellent electrical conductivity, more oxidation resistance, the surface layer is not easy to peel off and other advantages.

In dynamic temperature measurement, thermocouple sensors are widely used, and their dynamic characteristics directly affect the accuracy of the test results. So before applying thermocouple sensors to dynamic temperature measurement, their dynamic characteristics should be obtained, and their dynamic performance parameters should be analyzed. The time constant is the most important dynamic parameter, which reflects the response speed of a thermocouple sensor. Therefore, it is necessary to measure the time constant. The time constant is closely related to the heat transfer mode, so the heat transfer environment of the time constant measurement system should be similar to the application environment of thermocouple sensor. When using the thermocouple to measure the temperature in various kilns, the heat transfer is mainly through the radiative mode, and existing equipment, such as constant temperature water/oil tank, shock wave tube and other devices, cannot be used to measure the time constant to reflect scenarios in actual measurement applications. Therefore, this paper proposed a new method to measure the time constant of the thermocouple by improved high temperature furnace. In the system, the high temperature furnace was used to generate the stable temperature field, and the fast feed device was used to insert the thermocouple into the high temperature furnace and generates the ramp temperature excitation. The temperature can reach 1500 °C in the furnace, and the temperature error in uniform temperature field is ±1 °C. Finally, the time constant of a K-type thermocouple was measured, and the uncertainty of the measurement result was analyzed.