Non-contact Measurement Research Articles

Research on the Visual Measurement Algorithm of Cam Base Circle Radius Based on Virtual Structured Light Plane

Abstract Using line structured light vision measurement technology, it is possible to perform non-contact measurement of the cam's base circle radius. To address the issue of the structured light plane not being perpendicular to the axis of the cam being measured, this paper obtains the axis equation of the cam being measured through calibration, and based on the axis equation, it obtains the spatial equation of a virtual light plane that is perpendicular to the axis. The point cloud on the surface of the cam is projected onto the virtual plane, and the base circle radius of the cam is obtained using the coordinates of the projected points. To improve the measurement accuracy of the cam's base circle radius, this paper designs a base revision model to address measurement errors caused by the non-coincidence of bases. The measurement results of the base circle radii of four cams on the engine camshaft show that the line structured light vision measurement technology meets the measurement requirements and is feasible for non-contact measurement.The innovation presented herein lies in the development of a cloud acquisition model predicated on line structured light vision technology, which effectively converts a complex spatial curve fitting challenge into a simpler planar curve fitting problem.This transformation not only streamlines the measurement process for the cam base circle radius but also significantly enhances the measurement precision of engine camshafts.

Method for Non-Contact Measuring the Weight of Sturgeon in Intensive Aquaculture

Weight information plays a pivotal role in sturgeon breeding and production management. However, manual measurement is time consuming and labor intensive due to the immense size of the sturgeon. Due to the unique body shape of the sturgeon, traditional image segmentation algorithms struggle to extract the necessary features from sturgeon images, which makes them unsuitable for this particular species. Moreover, accurately measuring weight in an occlusion environment is difficult. To address these challenges, an improved YOLOv5s model with a context augmentation module, focal-efficient intersection over union, and soft non-maximum suppression was proposed in this paper. To validate the model’s feasibility, the improved YOLOv5s model was first pre-trained using the sturgeon dataset, followed by further training on the occlusion dataset for segmentation tasks. Based on the phenotypic data obtained from the improved model, a multilayer perceptron method was used to estimate the sturgeon’s weight accurately. Experimental results demonstrated that the average precision of the improved YOLOv5s model reached 89.80% under occlusion conditions, and the correlation coefficient of noncontact weight measurement results reached 89.80%. The experimental results showed that the improved algorithm effectively performs segmentation of sturgeon in occlusion conditions and can accurately estimate the mass.

Potential damage area detection of bridges based on single-temporal point cloud

Abstract With advantages of 3D representation, non-contact measurements and intensive sampling capability, it has been a research hotspot to detect the potential damage area of bridges with point cloud by TLS. However, TLS is commonly used to detect a potential damage area by comparing multi-temporal point cloud data, which limits the timeliness of bridge inspection. Therefore, aiming to accurately detect the potential damage areas of bridges with single-temporal point cloud, this paper proposes a normalized normal vector constrained coordinate transformation method. First, the distribution of sharp features is revealed in a single-temporal point cloud at potential damage areas, and a neighborhood growth method constrained by the normal distance is proposed to eliminate the sharp features in point cloud, which is prone to cause incorrect or missing curvature values from point cloud. Second, a normalized normal vector constrained coordinate transformation method is proposed to construct Gaussian curvature model, which can improve the accuracy of point cloud curvature and accurately detect the potential damage areas in bridges. At last, an evaluation criterion is proposed to quantify the bridge condition by integrating the characteristics of small-span concrete bridges in urban areas with actual damage data from the experimental bridges. The experimental results show that the proposed method can effectively detect the potential damage areas of the measured bridges.

Full-field Modal Analysis of a Tensegrity Column Using a Three-dimensional Scanning Laser Doppler Vibrometer with a Mirror

Abstract Tensegrity structures become important components of various engineering structures due to their high stiffness, light weight, and deployable capability. Existing studies on their dynamic analyses mainly focus on responses of their nodal points while overlook deformations of their cable and strut members. This study proposes a non-contact approach for experimental modal analysis of a tensegrity structure to identify its three-dimensional (3D) natural frequencies and full-field mode shapes, which include modes with deformations of its cable and strut members. A 3D scanning laser Doppler vibrometer is used with a mirror for extending its field of view to measure full-field vibration of a novel three-strut metal tensegrity column with free boundaries. Tensions and axial stiffnesses of its cable members are determined using natural frequencies of their transverse and longitudinal modes, respectively, to build its theoretical model for dynamic analysis and model validation purposes. Modal assurance criterion (MAC) values between experimental and theoretical mode shapes are used to identify their paired modes. Modal parameters of the first 15 elastic modes of the tensegrity column identified from the experiment, including those of the overall structure and its cable members, can be classified into five mode groups depending on their types. Modes paired between experimental and theoretical results have MAC values larger than 78%. Differences between natural frequencies of paired modes of the tensegrity column are less than 15%. The proposed non-contact 3D vibration measurement approach allows accurate estimation of 3D full-field modal parameters of the tensegrity column.

A Study of the Effect of Temperature on the Capacitance Characteristics of a Metal-μhemisphere Resonant Gyroscope.

Metal-μhemispherical resonant gyros (M-μHRGs) are widely used in highly dynamic navigation systems in extreme environments due to their high accuracy and structural stability. However, the effect of temperature variations on the capacitance characteristics of M-μHRGs has not been fully investigated, which is crucial for optimizing the performance of the gyro. This study aims to systematically analyze the effect of temperature on the static and dynamic capacitances of M-μHRGs. In this study, an M-μHRG structure based on a 16-tooth metal oscillator is designed, and conducted simulation experiments using non-contact capacitance measurement method and COMSOL Multiphysics 6.2 finite element simulation software in the temperature range of 233.15 K to 343.15 K. The modeling analysis of the static capacitance takes into account the thermal expansion effect, and the results show that static capacitance remains stable across the measured temperature range, with minimal effect from temperature. The dynamic capacitance exhibits significant nonlinear variations under different temperature conditions, especially in the two end temperature intervals (below 273.15 K and above 313.15 K), where the capacitance values show local extremes and fluctuations. In order to capture this nonlinear behavior, the experimental data were smoothed and fitted using the LOESS method, revealing a complex trend of the capacitance variation with temperature. The results show that the M-μHRG has good capacitance stability in the mid-temperature range, but its dynamic performance is significantly affected at extreme temperatures. This study provides a theoretical reference for the optimal design of M-μHRGs in high- and low-temperature environments.

Novel fast full-wavefield modeling of air-coupled surface waves and its implications for non-contact pavement testing

We present a novel approach for deriving and modeling air-coupled surface waves with applications in non-contact non-destructive testing (NDT). It is based on the fast Fourier-Bessel series system in conjunction with the unconditionally stable dual-variable and position matrix method. Parametric studies, including sensitivity analysis, are conducted to assess the feasibility of using non-contact air-coupled measurements for pavement testing, focusing on Green's functions, time-domain waveforms, and experimental frequency-velocity spectra (FVS, i.e., the estimated Green's functions from acquired truncated wavefield). The predicted experimental FVS presented in this study are synthetic dispersion images, which are distinguished from the measured experimental FVS (i.e., measured dispersion images from multichannel analysis of surface wave (MASW) test). With the derived complete solution of air-coupled dynamic responses, we find that: (1) Striking similarities between the theoretical Green's functions of vertical displacement (on the pavement surface) and pressure (in the air), as well as in their corresponding experimental FVS. (2) The proposed accurate and efficient full-wave modeling of air-coupled surface waves avoids the need for good contact between geophones/accelerometers and pavement surface. This facilitates direct inversion of shear wave velocity profiles by fitting the predicted experimental FVS to the measured one. (3) Sensitivity analysis demonstrates no significant loss of information in the pressure measured in the air, supporting the feasibility of using non-contact measurement for non-destructive testing. These results suggest that non-contact air-coupled measurements hold great promise as a viable alternative to contact measurements in non-destructive testing.

Prominent cryogenic fluorescence temperature sensing and superior room-temperature photochromism in Bi/Eu codoped KNN transparent-ferroelectric ceramics

The growing demand for the miniaturization and multifunctionality of optoelectronic devices has promoted the development of transparent ferroelectrics. However, it is difficult for the superior multiple optical properties of these materials to be compatible with the excellent ferroelectricity and piezoelectricity in transparent ceramics. Here, we successfully synthesized Bi/Eu codoped eco-friendly K0.5Na0.5NbO3 transparent-ferroelectric ceramics with photoluminescence (PL) behavior, photochromic (PC) reactions and temperature-responsive PL. Based on the distinct optical properties of ceramics at different temperature ranges (room temperature and ultralow temperature), high utilization of multiple optical functions was realized. At room temperature, the PC behavior induced PL modulation contrast reaches 75.2% (at 592 nm), which can be applied in the optical information storage field. In the ultralow temperature range, the ceramics exhibit excellent sensitivity (with a maximum relative sensitivity of 26.32%/K) via fluorescence intensity ratio technology and exhibit great application potential in noncontact optical temperature measurements. Additionally, the change in the PL intensity at different wavelengths (I614/I592) can serve as a reliable indicator for detecting the occurrence of the phase transition from rhombohedral to orthorhombic at low temperature. This work provides a feasible paradigm for realizing the integration of ferroelectricity and multifarious optical properties in a single optoelectronic material.

Multicolor luminescence and high efficient optical thermometric performance of Eu3+ and Sm3+ in self-activated Na2LuMg2V3O12 garnet

To develop efficient luminescence and optical thermometry materials for color display and non-contact temperature measurement, novel RE3+ (RE = Eu, Sm) doped self-activated Na2LuMg2V3O12 phosphors were prepared by a typical solid-state reaction method. Their crystal structure, morphology, multi-color luminescence and temperature sensing properties were elaborately investigated. Under UV light excitation, an intense and broad green-yellow emission band from VO43– group is observed in the Na2LuMg2V3O12 matrix, indicating its potential application in solid state lighting. After the incorporation of Eu3+ and Sm3+ ions, efficient energy transfer (ET) from VO43– group to Eu3+/Sm3+ ions occurs and the emission color of the samples can be readily tuned among different color ranges. Besides, based on the change of luminescence intensity and lifetimes of VO43– group in Na2LuMg2V3O12:Eu3+ and Na2LuMg2V3O12:Sm3+, the ET efficiency was analyzed and the mechanism is illustrated. Finally, large discrepancy between the thermal stability of VO43– group and Eu3+/Sm3+ ions are observed in the temperature-dependent emission spectra of Na2LuMg2V3O12:Eu3+ and Na2LuMg2V3O12:Sm3+. By taking advantage of the luminescence intensity ratio (LIR) between VO43– group and Eu3+/Sm3+ ions in Na2LuMg2V3O12:0.01Eu3+ and Na2LuMg2V3O12:0.07Sm3+, two new types of optical thermometry mediums were designed and their basic temperature sensing parameters were calculated.

High-precision non-contact online measurement and predictive analysis of geometric parameters in large industrial components

High-precision non-contact online measurement and predictive analysis of geometric parameters in large industrial components

Optimized binarization algorithm-based method for the image recognition and characterization of explosion damage in rock masses

The quantitative analysis of rock mass damage is crucial in fields such as engineering geology, disaster prevention, mining, geotechnical engineering, and structural engineering. With the advancement and application of noncontact measurement technologies and fractal theory, image-based damage identification methods are gaining increasing importance. This paper presents an optimized binarization algorithm for identifying and characterizing damage zones in granite explosion images. The method involves filtering, mathematical morphology operations, and connectivity recognition to effectively remove background noise while preserving clear boundaries of the damaged areas. It accurately captures the explosion damage in granite, both in terms of damage morphology and characteristic parameters. Additionally, the coefficient of agreement (COA) is introduced to quantitatively assess the accuracy of different methods in identifying damaged areas. The experimental results show that, compared with commonly used methods such as Otsu's method, Bernsen's algorithm, Niblack's algorithm, Sauvola's algorithm, and the K-means image clustering algorithm, the proposed method performs better in terms of identification accuracy and parameter agreement, achieving COA values near 1 across diverse experimental environments. Furthermore, the proposed method excels in handling uneven lighting, mitigating interference from rock surface textures and explosion carbonization zones, and demonstrates significant robustness in complex scenarios. The findings of this paper provide insights into the integration of engineering geology and computer vision technology. They offer valuable references for damage identification in excavation damage zones (EDZs), geological disaster evaluation, and structural damage warning systems.

Rapid non-contact measurement of distance between two pins of flexspline in harmonic reducers based on standard/actual parts comparison

Rapid non-contact measurement of distance between two pins of flexspline in harmonic reducers based on standard/actual parts comparison

Noncontace Monitoring of Respiration and Heartbeat Based on Two-Wave Model Using a Millimeter-Wave MIMO FM-CW Radar

This paper deals with the non-contact measurement of heartbeat and respiration using a millimeter-wave multiple-input–multiple-output (MIMO) frequency-modulated continuous-wave (FM-CW) radar. Monitoring heartbeat and respiration is useful for detecting cardiac diseases and understanding stress levels. Contact sensors are not suitable for these sorts of long-term measurements due to the discomfort and skin irritation they cause. Therefore, the use of non-contact sensors, such as radars, is desirable. In this study, we obtained heartbeat and respiration information from phase data measured using a millimeter-wave MIMO FM-CW radar. We propose a two-wave model based on a Fourier series expansion and extract respiration and heartbeat information as a minimization problem. This model makes it possible to produce respiration and heartbeat waveforms. The produced heartbeat waveform can be used for estimating the interbeat interval (IBI). Experiments were conducted to confirm the usefulness of the proposed method. Moreover, the estimated results were compared with the contact sensor’s results. The results for both types of sensors were in good agreement.

An improved subpixel measurement method for piezoelectric ceramic driving characteristics based on particle filter

Microscopic vision displacement calculation is crucial for its high precision and non-contact nature in measuring piezoelectric ceramic displacement. However, the inefficient global search limits its effectiveness. This paper proposes an improved sub-pixel algorithm (GKF-PFBM) based on particle filtering. Firstly, particle filtering (PF) is combined with block matching (BM) to enhance matching efficiency and accuracy by replacing global search with particle state prediction and update. Then, subpixel interpolation using a Gaussian kernel function (GKF) is better adapted to nonlinear variations, handling high-frequency variations while preserving clear edges, thereby improving interpolation accuracy. Finally, a high-precision experimental platform is used to measure the driving characteristics of piezoelectric ceramics. Experimental results show that the mean errors of the GKF-PFBM algorithm and the bilinear interpolation algorithm (BI-BM) are 0.0032pixels and 0.1269pixels, respectively. The average hysteresis displacement error was measured to be approximately 12 nm by this method, verifying its precise non-contact measurement capability.

Methyl ricinoleate droplet impact on a high temperature stainless steel surface: Dynamic behavior and heat transfer

The rapid and uniform heating of the feedstock plays a key role in pyrolysis processes. Dispersing methyl ricinoleate (MR) into spray droplets can improve the heating speed and uniformity in the pyrolysis process, which is of great benefit to the yield of the target product. This article describes the results and mechanisms of single MR droplet impacting on a heated stainless steel surface at different temperatures (385 ∼ 520 °C). Two non-contact measurement techniques, including a high-speed camera and a thermal infrared imager, were used to record the dynamic behavior and heating effects of the MR droplet on the heated surface at different temperatures, respectively. Four representative impingement states were observed during droplet impact: adhesion rebound, adhesion rebound with breakup, bouncing, and bouncing with breakup. As a result, a comprehensive map was created, based on a dimensionless analysis, describing the relationships between the typical states. Regarding the quantitative analysis, the maximum spreading factor and the dimensionless droplet residence time were linearly related to the 0.336 and 0.389 powers of the Weber number, respectively. By calculating the average heat flux of a droplet, it was found that it is related to the stainless steel surface temperature, the droplet saturation temperature, and the Reynolds number. The transient temperature at the surface of the MR droplet was measured to quantify the effectiveness of the heating. This study could provide a theoretical basis for the regulation and optimization of MR pyrolysis conditions.

GMDIC: a digital image correlation measurement method based on global matching for large deformation displacement fields

The digital image correlation method is a non-contact optical measurement method, which has the advantages of full-field measurement, simple operation, and high measurement accuracy. The traditional DIC method can accurately measure displacement and strain fields, but there are still many limitations. (i) In the measurement of large displacement deformations, the calculation accuracy of the displacement field and strain field needs to be improved due to the unreasonable setting of parameters such as subset size and step size. (ii) It is difficult to avoid under-matching or over-matching when reconstructing smooth displacement or strain fields. (iii) When processing large-scale image data, the computational complexity will be very high, resulting in slow processing speeds. In recent years, deep-learning-based DIC has shown promising capabilities in addressing the aforementioned issues. We propose a new, to the best of our knowledge, DIC method based on deep learning, which is designed for measuring displacement fields of speckle images in complex large deformations. The network combines the multi-head attention Swin-Transformer and the high-efficient channel attention module ECA and adds positional information to the features to enhance feature representation capabilities. To train the model, we constructed a displacement field dataset that conformed to the real situation and contained various types of speckle images and complex deformations. The measurement results indicate that our model achieves consistent displacement prediction accuracy with traditional DIC methods in practical experiments. Moreover, our model outperforms traditional DIC methods in cases of large displacement scenarios.

3D shape measurement method for high-reflective surface based on a color camera

Fringe projection profilometry (FPP) has been widely utilized in many fields due to its non-contact, high accuracy, high resolution and full-field measurement capabilities. However, the limited dynamic range of the camera sensor can result in overexposure of high-reflective parts in industrial production measurement. To effectively solve the above issue, this paper proposes a 3D shape measurement method for the high-reflective surface based on a color camera. Firstly, the optimal exposure time for the low-reflective region is estimated using the relationship between the standard variance of the phase error and the modulation. Twelve blue phase-shifted fringe patterns and a uniform blue image are utilized to obtain 3D shape of high-reflective surface. Secondly, captured images are separated into red, green and blue components. The fused Gaussian low-pass filtering method with different cut-off frequencies is used to filter and denoise the green or red components and the true intensity of the blue component in the saturated regions is calculated by the unsaturated intensity of the green or red components based on the calibrated crosstalk matrix. Then the image in saturated regions is fused and normalized with the unsaturated region. The absolute phase obtained from the fused normalized fringe patterns is converted into 3D data. Finally, experiments have been carried out on measuring. The experimental results show that the proposed method is capable of obtaining the 3D shape of the surface of a high-reflective object with fewer patterns and high measurement accuracy.

Impact of adjacent thoracic structures in negative left atrial remodelling in atrial fibrillation

Abstract Background Previous work has suggested that compression from external structures can promote negative atrial remodelling in atrial fibrillation (AF) [1]. This is mechanistically plausible, with many recognised risk factors in developing AF (age, hypertension, obesity, obstructive sleep apnoea, etc.) related through activation of the autonomic nervous system with an associated increase in atrial pressure and chronic elevation in wall stress [2,3]. Such negative remodelling contributes to the existence of arrhythmogenic atrial substrate [4]. This is highly significant when we consider catheter ablation of extrapulmonary vein targets. Purpose This study aims to investigate the relationship between abnormal conduction patterns indicative of potential AF drivers and their proximity to structures adjacent to the left atrium (LA). Methods Eight patients with paroxysmal or persistent AF, scheduled for an elective catheter ablation procedure using a charge density mapping (CDM) system [5] underwent pre-procedural cardiac MRI. 3D surface mesh reconstructions of individuals’ LA and adjacent structures (ascending aorta [AoA], descending aorta [AoD], and spine) were produced from 2D MRI slices using a proprietary graphical interface tool developed in MATLAB (Figure 1A & B) [6]. MRI derived LA geometries were registered with their CDM counterparts by the Iterative Closest Point algorithm (Figure 1C); this enabled integration of MRI LA geometries into the CDM system. Subsequently, non-contact intrachamber voltage measurements from individuals’ procedures were used to derive cardiac activation directly onto MRI LA geometries. Abnormal conduction patterns representing possible AF drivers (focal firing, rotational propagation, and pivoting propagation) [5] were quantified as occurrences per second at each vertex of MRI LA geometries (Figure 1D). These conduction patterns could then be visualised and assessed in the context of adjacent structures (Figure 1E), with the Euclidean distance between each vertex of the MRI LA geometries and the closest point to their adjacent structures being calculated. Results Mean age was 65±9 years; 4 patients (50%) were male; AF was paroxysmal in 3 (37%) and persistent in 5 (63%); median time since AF diagnosis was 1 (1-3.8) years; ablation type was de novo in 5 (63%) and retreatment in 3 (38%). Frequencies of pivoting and rotational propagation were notably higher in regions of the LA closer to the AoA, and lower near the AoD and spine (Figure 2A & B). Conversely, focal firing showed a less prominent trend, being more frequent in LA regions nearer the AoD and distant from the AoA (Figure 2C). Conclusions Compression from the ascending aorta may promote anterior LA remodelling in AF, leading to increased pivoting and rotational AF drivers. Clinically, this suggests a potential target for ablation therapy with an anterior seatbelt line connecting the right superior pulmonary vein to the mitral annulus.

Infrared emissivity measurement methods considering target reflective characteristics

Emissivity measurements are of great significance for infrared thermal radiation and infrared remote sensing. However, traditional methods often face challenges such as difficulties in non-contact measurement, small measurement areas, and unsuitability for non-Lambertian surfaces. To address these issues, we propose the reflective distribution model integral method (RDMIM). This method is based on a reflective distribution model using the scattering-reflective deviation angle (SRDA). By regressing and integrating the object’s reflective distribution model, it achieves accurate non-contact measurement of non-Lambertian surfaces under normal temperature conditions. Additionally, the measurement scheme has been further optimized to improve measurement efficiency while ensuring the accuracy of the model regression. Finally, the proposed RDMIM method has been validated through experimental measurements. The results have shown that this method has advantages in non-contact and large-area measurements. Moreover, the systematic error is smaller when the reflective characteristics of the reference body and the target are relatively similar.

A Non-Contacted Height Measurement Method in Two-Dimensional Space.

Height is an important health parameter employed across domains, including healthcare, aesthetics, and athletics. Numerous non-contact methods for height measurement exist; however, most are limited to assessing height in an upright posture. This study presents a non-contact approach for measuring human height in 2D space across different postures. The proposed method utilizes computer vision techniques, specifically the MediaPipe library and the YOLOv8 model, to analyze images captured with a smartphone camera. The MediaPipe library identifies and marks joint points on the human body, while the YOLOv8 model facilitates the localization of these points. To determine the actual height of an individual, a multivariate linear regression model was trained using the ratios of distances between the identified joint points. Data from 166 subjects across four distinct postures: standing upright, rotated 45 degrees, rotated 90 degrees, and kneeling were used to train and validate the model. Results indicate that the proposed method yields height measurements with a minimal error margin of approximately 1.2%. Future research will extend this approach to accommodate additional positions, such as lying down, cross-legged, and bent-legged. Furthermore, the method will be improved to account for various distances and angles of capture, thereby enhancing the flexibility and accuracy of height measurement in diverse contexts.

Stable Au(111) Hexagonal Reconstruction Induced by Perchlorinated Nanographene Molecules.

Surface reconstructions play a crucial role in surface science because of their influence on the adsorption and arrangement of molecules or nanoparticles. On the Au(111) surface, the herringbone reconstruction presents favorable anchoring at the elbow sites, where the highest reactivity is found. In this work, we deposited large organic perchlorinated molecules on a Au(111) surface via high-vacuum electrospray deposition. With noncontact atomic force microscopy measurements at room temperature, we studied the molecular structures formed on the surface before and after annealing at different temperatures. We found that a supramolecular layer is formed and that a hexagonal reconstruction of the Au(111) surface is induced. After high-temperature annealing, the molecules are removed, but the hexagonal Au(111) surface reconstruction is preserved. With the hexagonal Au(111) surface reconstruction, a periodic lattice of anchoring sites is formed.