Temperature sensor tag based on supercavity mode of dielectric resonator

This paper presents a wireless temperature sensor design based on the excitation of a high-Q supercavity mode in a dielectric resonator. Narrow resonance bandwidth improves sensor performance enabling accurate temperature measurements. The sensor consists of a half split ceramic cylinder attached to a metal sheet. The resonator parameters which lead to the excitation of a supercavity mode were obtained numerically. When the ambient temperature increased continuously from 23 to 120°C the notable shift of the resonant frequency was experimentally demonstrated.

Depth Data Denoising in Optical Laser Based Sensors for Metal Sheet Flatness Measurement: A Deep Learning Approach

Surface flatness assessment is necessary for quality control of metal sheets manufactured from steel coils by roll leveling and cutting. Mechanical-contact-based flatness sensors are being replaced by modern laser-based optical sensors that deliver accurate and dense reconstruction of metal sheet surfaces for flatness index computation. However, the surface range images captured by these optical sensors are corrupted by very specific kinds of noise due to vibrations caused by mechanical processes like degreasing, cleaning, polishing, shearing, and transporting roll systems. Therefore, high-quality flatness optical measurement systems strongly depend on the quality of image denoising methods applied to extract the true surface height image. This paper presents a deep learning architecture for removing these specific kinds of noise from the range images obtained by a laser based range sensor installed in a rolling and shearing line, in order to allow accurate flatness measurements from the clean range images. The proposed convolutional blind residual denoising network (CBRDNet) is composed of a noise estimation module and a noise removal module implemented by specific adaptation of semantic convolutional neural networks. The CBRDNet is validated on both synthetic and real noisy range image data that exhibit the most critical kinds of noise that arise throughout the metal sheet production process. Real data were obtained from a single laser line triangulation flatness sensor installed in a roll leveling and cut to length line. Computational experiments over both synthetic and real datasets clearly demonstrate that CBRDNet achieves superior performance in comparison to traditional 1D and 2D filtering methods, and state-of-the-art CNN-based denoising techniques. The experimental validation results show a reduction in error than can be up to 15% relative to solutions based on traditional 1D and 2D filtering methods and between 10% and 3% relative to the other deep learning denoising architectures recently reported in the literature.

Contact interactions between soil and a corrugated metal sheet in soil-shell structures under construction

During the construction of soil-shell objects, large deformations of the shell, which is made of corrugated metal sheet, occur. This enables geodetic techniques to be used when monitoring such objects. On this basis, displacements of selected points of the shell are determined, and it is then possible to obtain bending moments, as shown in this paper. Based on measurements using strain gauges in the circumferential band of the shell, internal forces in steel are estimated. The algorithm given in the paper enables the impact of soil on the shell in the examined objects to be analysed. The proposed method of analysing forces in the contact layer becomes especially useful when the static conditions of the model of a shell, which is considered as a bar submerged unilaterally in the soil medium, are met. The paper indicates the possibility of using both measuring techniques. Calculations include a smaller share of axial forces on the contact impact during the laying phase of the backfill. The paper provides examples of the analysis of built shells and record-breaking objects, with an assessment of the effectiveness of the proposed algorithm. Good mapping of contact forces, which were calculated on the basis of bending moments, was indicated even when there was not a dense grid of measuring points. An important advantage of the algorithm involves reduction of the circumferential band that is separated from the soil-shell system to the bar, which is an element resulting from the division of the structure into subsystems.

Strain State in Metal Sheet Axisymmetric Stretching with Variable Initial Thickness: Numerical and Experimental Results

This work presents a finite element model to analyze the distribution of the strains due to an axisymmetric stretching of a metal sheet. The sheet is characterized by a variable initial thickness. The resulting strain state is compared with that of a sheet with a constant initial thickness. The results of the present study allow asserting that the distribution of strains in the sheet can be controlled by setting opportunely the trend of the sheet initial thickness. In this way, it is possible to see that, starting from a sheet with variable initial thickness, a lighter final product is obtained, whose final thickness distribution is more uniform than that of the product obtained from a classic stretching process that requires a sheet with constant initial thickness. Encouraging results from an experimental activity carried out on an AA6060 aluminum alloy sheet, whose trend of initial thicknesses was prepared by removing material from a commercial sheet with a constant thickness, allow us to note the good agreement with what was theoretically highlighted.