Non-contact Method Research Articles

Thermal diffusion in cement mortar exposed to continuous wave point laser

ABSTRACT .Laser Spot Thermography (LST) is a rapid, non-contact defect detection method, but its application to porous, heterogeneous materials like cement mortar is challenging due to complex heat diffusion. This study explores LST for cement mortar by capturing thermal images of both surfaces under continuous wave (CW) laser exposure. COMSOL simulations analyze three-dimensional heat diffusion, considering aggregate content, particle size, and laser power. A correction coefficient for composite thermal conductivity, derived using the Maxwell–Eucken model, is validated under varying conditions. Results show that increasing aggregate content reduces the front surface temperature difference (ΔT) by 6.5% at 20% and 11% at 30%, while ΔT at the back surface increases by 3.5% and 5.7%, respectively. The correction coefficient (μ) remains stable at 0.932 for aggregate fractions of 0.1–0.2 but decreases linearly beyond this range. These findings provide insights into optimizing LST for structural health monitoring of heterogeneous materials.

Estimating depth-directional thermal conductivity profiles using neural network with dropout in frequency-domain thermoreflectance

Non-contact and non-destructive methods are essential for accurately determining the thermophysical properties necessary for the optimal thermal design of semiconductor devices and for assessing the properties of materials with varying crystallinity across their thickness. Among these methods, frequency-domain thermoreflectance (FDTR) stands out as an effective technique for evaluating the thermal characteristics of nano/microscale specimens. FDTR varies the thermal penetration depth by modifying the heating frequency, enabling a detailed analysis of the thermophysical properties at different depths. This study introduces a machine learning approach that employs FDTR to examine the thermal conductivity profile along the depth of a specimen. A neural network model incorporating dropout techniques was adapted to estimate the posterior probability distribution of depth-wise thermal conductivity. Analytical databases for both uniform and non-uniform thermal conductivity profiles were generated, and the machine learning model was trained using these databases. The effectiveness of the predictive model was confirmed through assessments of both uniform and non-uniform thermal conductivity profiles, achieving a coefficient of determination between 0.96 and 0.99. For uniform thermal conductivity, the method attained mean absolute percentage errors of 1.362% for thermal conductivity and 3.466% for thermal boundary conductance (compared to actual values in the analytically calculated database). In cases of non-uniform thermal conductivity, the prediction accuracy decreased, particularly near the sample's surface, primarily due to the limited availability of machine learning data at higher heating frequencies.

A non-contact calibration method of workpiece coordinate system for aero-engine blade-robotic grinding system

Mounting error of the blade is an important factor that affects the grinding quality in aero-engine blade-robotic grinding system. In order to compensate for the mounting error, it is necessary to calibrate the pose of the workpiece coordinate system. However, most of the current workpiece calibration methods cannot meet the high accuracy requirements in the scenario of aero-engine blade grinding. Therefore, this paper proposes a new non-contact calibration method of workpiece coordinate system using scanner measurement, to solve the workpiece calibration problem in aero-engine blade-robotic grinding system. The method first calibrates the scanner based on the criterion sphere hand-eye calibration method and employs the Random Sample Consensus (RANSAC) algorithm to ensure the accuracy of the fitted sphere center coordinates. Then, the point cloud registration algorithms are used to align the scanned point cloud of the blade with the model point cloud. Finally, the space transformation matrix between the workpiece coordinate system and the base coordinate system is obtained through matrix calculation, achieving the accurate calibration of the workpiece coordinate system. The experimental validation of the proposed calibration method in this paper can maintain tiny and acceptable errors for grinding applications. Specifically, the hand-eye calibration error is less than 0.2 mm, and the point cloud registration error is less than 0.06 mm. Moreover, the calibrated blade exhibits excellent machining consistency after grinding, which can perfectly meet the requirements of actual machining accuracy.

Contact and Non-Contact Measurements of Chlorophyll-a in Water Based on Laser Spectroscopy

Chlorophyll-a fluorescence detection is an important technique for monitoring water quality. In this paper, we proposed an approach that employs the ratio of fluorescence to Raman obtained from contact and non-contact laser-induced fluorescence detection methods as the key for the detection of Chlorophyll-a in water. At first, extracted Chlorophyll-a solutions were prepared, and each sample was tested using two detection methods. The true values of the samples were measured in the laboratory using spectrophotometry. Then, the detection system was calibrated through the linear fitting of Chlorophyll-a and the fluorescence–Raman ratio. The linear correlation coefficients of contact and non-contact detection were 0.9453 and 0.9401, respectively. Finally, we tested the actual water samples in two ways, and compared the test results with the value measured using the national standard method. The root mean square error (RMSE) of contact and non-contact detection was 0.16 and 0.23, respectively. The results show that the two detection methods have high accuracy and sensitivity, and preliminary preparation of samples is not required. Compared with contact detection, the non-contact detection results had higher accuracy and stronger anti-interference, but the maintenance cost was higher because the probe is vulnerable to wear. The advantage of non-contact detection is that it avoids sample contamination and is easy to apply over large areas of water. In the future, it can be used for the real-time monitoring of algal biomass in water by selecting the appropriate detection method according to the requirements of the application.

Multiphase flow simulations and experiments on electrochemical jet machining of rough surfaces of high-speed additive manufactured titanium alloys

ABSTRACT The application of titanium alloy parts manufactured by high-speed additive manufacturing in industry is currently constrained by the low surface accuracy. This severely constrains the potential of high-speed additive manufacturing for processing aerospace titanium alloy components. To address this issue, it is crucial to address the high-speed additive manufactured rough surface in order to enhance surface accuracy. As a highly flexible non-contact machining method, electrochemical jet machining is well-suited for surface post-treatment of additive manufactured titanium alloy parts due to its distinctive advantages, including the absence of tool loss, no cutting force, and no thermal effects. This paper examines the electrochemical jet machining of rough low-precision surfaces produced by high-speed additive manufacturing. The distribution characteristics of the machining electric field and machining flow field on extremely rough additive manufactured surfaces were investigated through simulation. A series of experiments were conducted to verify the effectiveness of the simulation. The research findings indicated that the cut-in electrochemical jet machining method effectively circumvented the adverse effects of rough surfaces on electrolyte flow, thereby allowing for high-quality machining. The surface roughness of titanium alloy samples produced by high-speed additive manufacturing was reduced from Ra 21.179–1.838 um, representing a 90% reduction.

A novel insulation space charge non-contact measurement method based on elasto-optical sensing and ellipsometric detection

A novel insulation space charge non-contact measurement method based on elasto-optical sensing and ellipsometric detection

3D scanner's potential as a novel tool for lymphedema measurement in mouse hindlimb models.

Lymphedema is characterized by persistent swelling due to impaired lymphatic function and presents significant challenges in both research and clinical settings. Traditional contact-based measurement techniques such as paw thickness and circumferential measurements using calipers or silk thread are useful but limited by observer variability and measurement accuracy. Non-contact methods, including various imaging techniques, offer improvements but often at higher cost and complexity. In this study, we address the need for a more reliable, cost-effective, and non-invasive method for assessing lymphedema in mouse models. Here we show that 3D scanning technology can enhance the measurement of lymphedema in a mouse hindlimb model. Our results indicate that 3D scanners provide more consistent measurements with lower variability compared with conventional methods and without the need for direct contact, which could potentially alter the measurement outcomes. The findings of this study suggest that 3D scanning could replace traditional methods, offering a more standardized and less subjective tool for lymphedema research in the near future. This technology would not only improve upon conventional methods but also extend the capabilities for detailed anatomical analyses in small animal models, which could have implications for other areas of biomedical research.

Non-contact estimation of equivalent mechanical properties using the transient vibration response induced by an acoustic radiation force

Abstract This study aimed to verify a non-contact method for estimating equivalent mechanical parameters using the transient vibration response induced by the step-functional acoustic radiation force of focused ultrasound. First, the vibration distribution of a silicone rubber plate excited by an acoustic radiation force was measured. The results revealed that the vibration-excited area was larger than the beam size and dependent on the characteristics of the material. The equivalent mass, mechanical compliance, and mechanical resistance were estimated based on the mode frequencies, time constants of vibration decay, and maximum velocity amplitudes obtained from the transient vibration response. The estimation showed qualitative agreement with the predicted trends corresponding to changes in the thickness of the rubber plate. These findings suggest that our method is effective for estimating equivalent mechanical parameters of objects, although challenges remain regarding spatial resolution.

Neural Network-Based Evaluation of Hardness in Cold-Rolled Austenitic Stainless Steel Under Various Heat Treatment Conditions

This study introduces an innovative, non-contact method for classifying the hardness of austenitic stainless steels (grade AISI 304) based on their intrinsic magnetic fields. Utilizing a 3 × 3 matrix sensor system, this research captures weak magnetic fields to produce precise 2D magnetic field maps of the samples. A key advancement is the application of a modified GoogleNet convolutional neural network, optimized with the stochastic gradient descent with momentum algorithm, which achieves exceptional classification accuracy, ranging from 95% to 100%, and median accuracies of 97.5% to 99%. This method stands out by revealing a novel correlation between annealing temperature and magnetic field strength, particularly a pronounced decline in magnetic properties at temperatures near 1000 °C. This observation underscores the sensitivity of magnetic profiles to heat treatments, offering a groundbreaking approach to material characterization. By enabling reliable, efficient, and fully automated hardness evaluation based on magnetic signatures, this work has the potential to transform materials engineering and manufacturing, setting a new benchmark for non-destructive material analysis techniques.

Solvent‐Free, Degradable Resins for 3D Inkjet Printing Based on Silyl Ether and Amino Acid Phosphoramide Photomonomers

AbstractInkjet 3D printing is a fast, reliable and noncontact method, capable of producing small and large structures and enabling multi‐material printing. These characteristics make inkjet an excellent printing technique for additive manufacturing of biomaterials, such as scaffolds for tissue engineering. However, the technology is restricted by the limited number of suitable photopolymers which hitherto are limited to acrylate‐based chemistries, which are not only toxic but nondegradable, thus of limited use in many biomaterials‐based applications. Herein, a unique and innovative approach is described looking beyond traditional carbon‐based chemistry to design and synthesize novel photomonomers based on amino acid phosphoramides (APA) with silyl ethers utilizing thiol‐yne click chemistry. The novel inks are specifically designed for use in solventless 3D inkjet printing of biomaterials and are shown to be biocompatible and having fast and tunable degradation rates. This makes these innovative inks a promising material for biomedical 3D printing applications, such as tissue regeneration.

Design and Analysis of Non-Contact Power Supply System for Wireless Monitoring Node of Ship's Water Lubricated Bearing

The wireless sensor monitoring node for the online monitoring of various parameters of the ship's water-lubricated bearing rotates with the shaft during its operation. Therefore, how to ensure a continuous power supply to the node under the rotating working condition is an urgent problem to be solved. In this paper, a non-contact power supply method is adopted to design a magnetically coupled inductive non-contact power supply system, and experimental verification is carried out. Firstly, the non-contact power supply method is described, a node energy consumption model is established for the existing wireless monitoring nodes, and the energy consumption test is conducted. Then, a magnetically coupled inductive non-contact power supply system is designed, and the output of the system circuit is simulated and analyzed. Finally, the experimental test of the power supply system is carried out to study various factors that affect the performance of the power supply system. The research results show that the rotational speed is not the key factor affecting the power supply effect of the system, and the air gap of the coupling mechanism is the key factor affecting the power of the power supply system. The output power of the power supply system increases with the increase of the air gap, and the output efficiency decreases with the increase of the air gap. Considering the influence of the efficiency factor of the power supply system, the 5mm air gap is the optimal working air gap of the power supply system, and the system output power can reach 15.9 W at this time.

Machining Path Optimization of Inductively Coupled Plasma Based on Surface Heat Transfer Model.

Inductively coupled plasma (ICP), a non-contact optical processing method, has been widely used in the preparation of fused quartz. However, the thermal effect during processing inevitably affects the stability of the removal rate, reduces the processing accuracy, and restricts the further development of plasma processing. This paper analyzes the critical temperature that affects the changes in plasma removal depth, establishes a heat transfer model for plasma jet processing through simulations, derives the heat conduction equation during processing, and obtains the critical radius corresponding to the critical temperature related to the processing speed. Additionally, this work analyzes the path temperature of the grating track used in processing and obtains the path temperature variation curve. Based on the critical radius, a staggered grating track was proposed, which verified that this track can effectively control the path temperature, thereby suppressing the error caused by the thermal effect of processing. This study not only helps to gain a deeper understanding of the heat transfer process in plasma machining, but also provides a basis for achieving high-precision plasma machining path optimization schemes.

Immediate Effects of Goldmann Applanation Tonometry on Central Corneal Thickness Measurements Using Contact and Non-contact Pachymetry Methods.

The objective was to evaluate the immediate impact of Goldmann Applanation Tonometry (GAT), a gold-standard intraocular pressure measurement technique, on the reliability of central corneal thickness (CCT) measurements and to compare the outcomes between contact and non-contact pachymetry methods. Fifty-one adult participants without ocular pathology were enrolled. Serial CCT measurements were conducted using three different pachymetry modalities across three days, both at baseline and post-GAT: Day 1 with an ultrasound pachymeter (USP), Day 2 using optical low-coherence reflectometry (OLCR), and Day 3 via anterior segment optical coherence tomography (AS-OCT). The study involved comparing mean CCT and CCT standard deviation at baseline and post-GAT using one-way analysis of variance (ANOVA) and paired t-tests. In the 610 CCT measurements performed, mean CCT did not show significant changes post-GAT overall or by modality (USP: +2.20 microns, p=0.63;OLCR: +1.0 microns, p=0.93;AS-OCT: +0.40 microns, p=0.95). However, contact USP consistently produced thicker corneal readings than non-contact OLCR and AS-OCT both at baseline and post-GAT (p < 0.0001). Notably, there was a significant increase in CCT standard deviation (+51.1%) and a decrease in adherence to technical repeatability specifications with contact USP following GAT (from 55% to 33%, p < 0.05). The study suggests that contact intraocular pressure measurement methods like GAT may influence the reliability and repeatability of CCT measurements, as observed in our increased CCT measurement standard deviations. This could have important implications for accurate diagnosis and treatment planning for various ocular conditions. Given the study's limited sample size, further research may be warranted.

The PSO-IFAH optimization algorithm for transient electromagnetic inversion.

As a non-contact method, the transient electromagnetic (TEM) method has the characteristics of high efficiency, small impact of device, no limitation of site range, and high resolution, and is a hot topic in current research. However, the research on the refined data processing method of TEM is lag, which seriously restricts the application in superficial engineering investigation and is a key problem that needs to be solved urgently. The particle swarm optimization (PSO) algorithm and firefly algorithm (FA) were successful swarm intelligence algorithms inspired by nature. However, the accuracy and efficiency of the algorithm restrict its further development. In this paper, the particle moving velocity of FA algorithm is defined according to the concept of particle moving velocity in PSO algorithm, so as to improve the local fast convergence ability of FA algorithm. On this basis, the appropriate velocity of particle movement is improved, so that the improved algorithm can overcome the oscillation problem around the optimal solution and improve the computational efficiency. And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. The proposed algorithm can exploit the strong points of both PSO and FA algorithm mechanisms. A typical layered model was established, and the PSO algorithm, FA algorithm, and PSO-IFAH algorithm were applied to inversion calculations. The results show that the PSO-IFAH algorithm improves calculation accuracy by more than 80% and efficiency by over 60% compared to the PSO and FA algorithms, respectively. The PSO-IFAH algorithm also exhibits high inversion accuracy and stability, with superior anti-noise properties compared to the other algorithms. When implemented in ground TEM measurement data processing, the PSO-IFAH algorithm enhances the resolution of anomalies and low-resistance details, aligning well with actual excavation results. This highlights the algorithm's capability to depict underground electrical structures and karst developments accurately, thereby improving the precision of TEM data processing and interpretation.

A Novel Non-contact Temperature Field Measurement Method Based on Transmittance Field Estimation under Dynamic Water Mist Interference

A Novel Non-contact Temperature Field Measurement Method Based on Transmittance Field Estimation under Dynamic Water Mist Interference

Pearling of cylindrical vesicles induced by acoustofluidics

The mechanical transformation of lipid membranes in biological structures plays a key role in the morphogenesis of cells and tissues. However, the mechanism by which active forces influence the shape transition of lipid vesicles remains unclear. Herein, we propose an acoustofluidics method to deform the cylindrical vesicles. The study combines theoretical and experimental approaches to investigate the shape behavior of cylindrical vesicles in an acoustic field. Analytical equations are established to describe the manipulation of radial deformation and elongation in cylindrical vesicles. Pearling of these vesicles is induced by the competition between membrane tension and drag force. In conditions of weak drag force, cylindrical vesicles under tension minimize their free energy through surface fluctuations, resulting in a beaded structure. This transformation creates a beads-on-a-string formation, consisting of uniformly sized spherical vesicles connected by fine lipid nanotubes. The findings offer a non-contact method to enhance the understanding and control of the shape dynamics in membranes within active matter systems.

Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models

The stable physiological structure and rich vascular network of pig ears contribute to distinct thermal characteristics, which can reflect temperature variations. While the temperature of the pig ear does not directly represent core body temperature due to the ear’s role in thermoregulation, thermal infrared imaging offers a feasible approach to analyzing individual pig status. Based on this background, a dataset comprising 23,189 thermal infrared images of pig ears (TIRPigEar) was established. The TIRPigEar dataset was obtained through a pig house inspection robot equipped with an infrared thermal imaging device, with post-processing conducted via manual annotation. By labeling pig ears within these images, a total of 69,567 labeled files were generated, which can be directly used for training pig ear detection models and enabling the analysis of pig temperature information by integrating the corresponding thermal imaging data. To validate the dataset’s utility, it was evaluated across various object detection algorithms. Experimental results show that the dataset achieves the highest precision, recall, and mAP50 on the YOLOv9m model, reaching 97.35%, 98.1%, and 98.6%, respectively. Overall, the TIRPigEar dataset demonstrates optimal performance when applied to the YOLOv9m algorithm. Utilizing thermal infrared imaging technology to detect pig ear information provides a non-contact, rapid, and effective method. Establishing the TIRPigEar dataset is highly significant, as it allows for a valuable resource for AI and precision livestock farming researchers to validate and improve their algorithms. This dataset will support many researchers in advancing precision livestock farming by enabling an efficient way for pig ear temperature analysis.

Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision

Icing on wind turbine blades in cold and humid weather has become a detrimental factor limiting their efficient operation, and traditional methods for detecting blade icing have various limitations. Therefore, this paper proposes a non-contact ice volume estimation method based on binocular vision and improved image processing algorithms. The method employs a stereo matching algorithm that combines dynamic windows, multi-feature fusion, and reordering, integrating gradient, color, and other information to generate matching costs. It utilizes a cross-based support region for cost aggregation and generates the final disparity map through a Winner-Take-All (WTA) strategy and multi-step optimization. Subsequently, combining image processing techniques and three-dimensional reconstruction methods, the geometric shape of the ice is modeled, and its volume is estimated using numerical integration methods. Experimental results on volume estimation show that for ice blocks with regular shapes, the errors between the measured and actual volumes are 5.28%, 8.35%, and 4.85%, respectively; for simulated icing on wind turbine blades, the errors are 5.06%, 6.45%, and 9.54%, respectively. The results indicate that the volume measurement errors under various conditions are all within 10%, meeting the experimental accuracy requirements for measuring the volume of ice accumulation on wind turbine blades. This method provides an accurate and efficient solution for detecting blade icing without the need to modify the blades, making it suitable for wind turbines already in operation. However, in practical applications, it may be necessary to consider the impact of illumination and environmental changes on visual measurements.

Landslide Thickness Estimated from InSAR-Derived 2D Deformation: Application to the Xiongba Ancient Landslide, China

The thickness estimation of landslides is crucial for better landslide evaluation. Traditional non-contact mass conservation methods using 3D deformation may be unsuitable due to observation limitations. This study proposes a more feasible approach based on 2D deformation from two-track Interferometric Synthetic Aperture Radar (InSAR) observations, applied to the Xiongba landslide. The comparison with geological and drilling measurements confirms the reliability of this method. The mapped InSAR LOS deformation rate fields reveal two regions: a significantly deformed frontal zone and a relatively stable zone. Analysis suggests that surface uplift at the Xiongba-H2 landslide’s front edge results from rock–soil mass pushing in high-deformation areas. The estimated thickness ranges from 10 to 100 m, with an active volume of 6.17 × 107 m3. A thicker region is identified at the front edge along the Jinsha River, posing the potential for further failure. This low-cost, easily implemented approach enhances InSAR’s applicability for landslide analysis and hazard assessment.

Anterior segment OCT for imaging PAUL® glaucoma implant patch grafts:a useful method for follow-up and risk management.

To evaluate a useful, non-contact method for the follow-up of pericardium patch graft changes in patients undergoing PAUL® Glaucoma Implant (PGI) surgery using high-resolution anterior segment optical coherence tomography (OCT) to predict tube erosions. Prospective analysis over six months of tube pericardium patch graft thickness of PGI surgical cases at the University Eye Hospital Bonn, Germany, from November 2021 to August 2022. In all eyes, Tutopatch® (RTI Surgical, United States) pericardium was used to cover the implant intra-operatively. Anterior segment OCT (AS-OCT, Heidelberg ANTERION® Swept-Source-OCT) examinations were performed following a standardized protocol to measure quantitative and qualitative aspects of the patch grafts before surgery, and at three and six months after surgery. Twenty-six eyes of 26 patients were included. Thickness of the patch material was 1188µm (IQR 415µm) directly after implantation and decreased over time to 1068µm (IQR 478µm) at 3months and 846µm (IQR 677µm) at 6months. No significant differences between groups were shown concerning gender (p = 0.128), ethnicity (p = 1.000), age (p = 0.741), glaucoma type (p = 0.173), other concurrent diseases (p = 0.302), former glaucoma surgeries (p = 1.000) and the quadrant of implantation (p = 0.555). Five eyes developed implant exposure. When comparing eyes with and without tube exposure, no significant differences were shown in average patch thickness above the tube directly after implantation (p = 0.476). However, significant differences in average thickness were observed at 3months (p = 0.013) and 6months (p = 0.005). Pericardial patch grafts tend to thin over time which can be assessed by AS-OCT, the latter proving to be a useful method to follow-up patients who undergo patch graft implantation during PGI surgery. This investigation could potentially help identify patients at risk of tube exposure which in turn could lead to modification of patient management. It could also possibly be used in future studies to find more suitable patch materials.