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As brown mushrooms are both delicious and beneficial to health, the global production and consumption of brown mushrooms have increased significantly in recent years. Currently, to ensure the quality of brown mushrooms, selective manual picking is required, and the delicate surface of the mushrooms must not be damaged during the picking process. The labor cost of picking accounts for 50–80% of the total labor cost in the entire production process, and the high-humidity, low-temperature plant environment poses a risk of rheumatism for the laborers. In this paper, we propose a novel underactuated gripper based on a lead screw and linear bearings, capable of operating with flexible force control while simultaneously measuring the diameter of the mushrooms. The gripper features three degrees of freedom: lifting, grasping, and rotation, and enabling it to approach, grasp, and detach the mushroom. A thin-film force sensor is installed on the inner side of the fingers to achieve accurate grip force measurement. The use of a PID algorithm ensures precise grip force control, thereby protecting the brown mushrooms from damage. Experimental results demonstrate that the proposed gripper has a static grasping force error of 0.195 N and an average detachment force overshoot of 1.31 N during the entire picking process. The in situ measurement of the mushroom diameter achieves 97.3% accuracy, with a success rate of 98.3%. These results indicate that the gripper achieves a high success rate in harvesting, a low damage rate, and accurate diameter measurement. [ABSTRACT FROM AUTHOR]

Wood is one of the energy sources for sustainable development, which is closely related to our life. In the wood production process, it will be sorted according to different diameter grade is an essential link, at present the wood sorting work mainly rely on manual completion, not only low efficiency, high cost, and cannot meet the automated era of production needs. In this paper, a wood diameter level automatic sorting system is designed, first of all, using computer vision technology to measure the diameter of the wood section in real time, then the diameter data is transmitted to the PLC control system, and finally the PLC control system pushes out the wood in the specified position, realizing the automated on-line sorting of wood. In addition, a wood diameter measurement method based on deep learning combined with binocular vision is proposed, which can quickly and accurately recognize the diameter of each piece of wood, and provides a solid foundation for the efficient performance of the automatic wood diameter grade sorting system. The experimental results show that the measurement method proposed in this paper has high robustness and the maximum error is within 5mm, which meets the accuracy requirements needed for sorting, and the sorting system can sort 10 pieces of wood per minute on average, which greatly improves the efficiency of wood sorting and reduces the labor workload and cost, and the research design is of great significance to the wood production and manufacturing industry.

Uncertainty about the geometry of jet grouting columns is a serious challenge to the efficiency of jet grouting technology. If this challenge can be met, jet grouting can become an efficient method of soil improvement. One proposed approach is measurement based on changes in the electrical resistivity between the column and surrounding soil. This approach is non-destructive, easy to use, fast and accurate. This paper reviews jet-grouting methods using the experimental research approach and reports on the design and construction of a probe equipped with ring electrodes that is suitable for measurement of the column diameter. The approach is based on the geoelectric method and Wenner theory. The probe was field tested on jet-grouting columns in a project in Bandar-e Gaz. The probe results were validated by visually observing the dimensions of the excavated column. The results showed that the probe performed well. The device measured a 90-cm column as being from 81 to 88 cm with an error of about 10%. The method of measuring the difference in electrical resistance was shown to be an accurate approach to solving the problem of uncertainty in the geometry of jet-grouting columns. [ABSTRACT FROM AUTHOR]

As brown mushrooms are both delicious and beneficial to health, the global production and consumption of brown mushrooms have increased significantly in recent years. Currently, to ensure the quality of brown mushrooms, selective manual picking is required, and the delicate surface of the mushrooms must not be damaged during the picking process. The labor cost of picking accounts for 50–80% of the total labor cost in the entire production process, and the high-humidity, low-temperature plant environment poses a risk of rheumatism for the laborers. In this paper, we propose a novel underactuated gripper based on a lead screw and linear bearings, capable of operating with flexible force control while simultaneously measuring the diameter of the mushrooms. The gripper features three degrees of freedom: lifting, grasping, and rotation, and enabling it to approach, grasp, and detach the mushroom. A thin-film force sensor is installed on the inner side of the fingers to achieve accurate grip force measurement. The use of a PID algorithm ensures precise grip force control, thereby protecting the brown mushrooms from damage. Experimental results demonstrate that the proposed gripper has a static grasping force error of 0.195 N and an average detachment force overshoot of 1.31 N during the entire picking process. The in situ measurement of the mushroom diameter achieves 97.3% accuracy, with a success rate of 98.3%. These results indicate that the gripper achieves a high success rate in harvesting, a low damage rate, and accurate diameter measurement.

We present a stereo image-based algorithm for tree stem diameter measurement and form analysis. The algorithm uses planar parametric curves to represent two-dimensional projections of tree stems in stereo images. The curves evolve according to an energy formulation based on the gradients of the images and inductive priors related to biomechanics and morphology of tree stems. After energy minimization, the curves are reconstructed to three dimensions, allowing for diameter measurements at any point along the height of the stem. We describe the algorithm and report the validation test results comparing predicted diameter measurements to external observations. Our findings demonstrate that the algorithm can automatically estimate diameters for trees within 20 m of the camera with an error of 5.52%. We highlight how this method can aid product value optimization through taper analysis and sweep or crook detection. A run-time analysis shows that the algorithm can estimate dendrometric variables for ten trees simultaneously at 15 frames per second on a consumer-grade computer. Furthermore, we discuss the opportunity to produce training data for machine learning algorithms that generalize across domains and eliminate the need to manually tune parameters. [ABSTRACT FROM AUTHOR]

This study aims to improve the Agaricus bisporus detection efficiency and performance of harvesting robots in the complex environment of the mushroom growing house. Based on deep learning networks, an improved YOLOv5s algorithm was proposed for accurate A. bisporus detection. First, A. bisporus images collected in situ from the mushroom growing house were preprocessed and augmented to construct a dataset containing 810 images, which were divided into the training and test sets in the ratio of 8:2. Then, by introducing the Convolutional Block Attention Module (CBAM) into the backbone network of YOLOv5s and adopting the Mosaic image augmentation technique in training, the detection accuracy and robustness of the algorithm were improved. The experimental results showed that the improved algorithm had a recognition accuracy of 98%, a single-image processing time of 18 ms, an A. bisporus center point locating error of 0.40%, and a diameter measuring error of 1.08%. Compared with YOLOv5s and YOLOv7, the YOLOv5s-CBAM has better performance in recognition accuracy, center positioning, and diameter measurement. Therefore, the proposed algorithm is capable of accurate A. bisporus detection in the complex environment of the mushroom growing house. [ABSTRACT FROM AUTHOR]

We present a stereo image-based algorithm for tree stem diameter measurement and form analysis. The algorithm uses planar parametric curves to represent two-dimensional projections of tree stems in stereo images. The curves evolve according to an energy formulation based on the gradients of the images and inductive priors related to biomechanics and morphology of tree stems. After energy minimization, the curves are reconstructed to three dimensions, allowing for diameter measurements at any point along the height of the stem. We describe the algorithm and report the validation test results comparing predicted diameter measurements to external observations. Our findings demonstrate that the algorithm can automatically estimate diameters for trees within 20 m of the camera with an error of 5.52%. We highlight how this method can aid product value optimization through taper analysis and sweep or crook detection. A run-time analysis shows that the algorithm can estimate dendrometric variables for ten trees simultaneously at 15 frames per second on a consumer-grade computer. Furthermore, we discuss the opportunity to produce training data for machine learning algorithms that generalize across domains and eliminate the need to manually tune parameters.

An optical strain gauge based on a balloon-like interferometer structure formed by a bent standard single-mode fiber combined with a 3D printer piece has been presented and demonstrated, which can be used to measure displacement. The interferometer has a simple and compact size, easy fabrication, low cost, and is repeatable. The sensor is based on the interference between the core and cladding modes. This is caused by the fiber's curvature because when light propagates through the curved balloon-shaped interferometer region, a portion of it will be released from the core limitation and coupled to the cladding. The balloon has an axial displacement as a result of how the artwork was constructed. The sensor head is sandwiched between two cantilevers such that when there is a displacement, the dimension associated with the micro bend is altered. The sensor response as a function of displacement can be determined using wavelength shift or intensity change interrogation techniques. Therefore, this optical strain gauge is a good option for applications where structure displacement needs to be examined. The sensor presents a sensitivity of 55.014 nm for displacement measurements ranging from 0 to 10 mm and a strain sensitivity of 500.13 pm/ μ ϵ . [ABSTRACT FROM AUTHOR]

Measurements of serial production workpieces in the industry are performed by camera-controlled systems thanks to the advantage of speed. The measurement success of camera systems largely depends on the measurement algorithm and ambient conditions. Area-based approaches are not preferred in industrial machine vision applications due to the undesired environmental conditions. In this paper, an area-based diameter measurement algorithm that can be used in industrial machine vision applications is proposed. The success of the proposed method is demonstrated based on the sub-computation metric. In the proposed method, firstly, the noise on the obtained image is cleaned according to the connected component analysis. Then, the inner and outer diameters of the largest component are determined according to the area calculation. In the designed experimental setup, a back lighting illumination has been preferred. According to 3 different positioning types in the field of view of the camera, a total of 40 stamps of 4 types were measured 20 times with 3 different lenses. According to the test results, it has been observed that the position of the part on the field of view greatly affects the repeatability measurements. Also, sub-computation metric (C) is measured 2 in random positioning. This value increases up to 5 in the limited positioning that meets the industrial conditions. Tests have shown that the proposed method can measure the diameters of workpieces with precise tolerances in an industrial setting. [ABSTRACT FROM AUTHOR]

This study aims to improve the Agaricus bisporus detection efficiency and performance of harvesting robots in the complex environment of the mushroom growing house. Based on deep learning networks, an improved YOLOv5s algorithm was proposed for accurate A. bisporus detection. First, A. bisporus images collected in situ from the mushroom growing house were preprocessed and augmented to construct a dataset containing 810 images, which were divided into the training and test sets in the ratio of 8:2. Then, by introducing the Convolutional Block Attention Module (CBAM) into the backbone network of YOLOv5s and adopting the Mosaic image augmentation technique in training, the detection accuracy and robustness of the algorithm were improved. The experimental results showed that the improved algorithm had a recognition accuracy of 98%, a single-image processing time of 18 ms, an A. bisporus center point locating error of 0.40%, and a diameter measuring error of 1.08%. Compared with YOLOv5s and YOLOv7, the YOLOv5s-CBAM has better performance in recognition accuracy, center positioning, and diameter measurement. Therefore, the proposed algorithm is capable of accurate A. bisporus detection in the complex environment of the mushroom growing house.

Automatic and accurate segmentation of renal arteriolar vessels from pathological whole slide images (WSI) is a prerequisite and plays an important role in renal diseases diagnosis. Most existing methods generally focus on the detection and segmentation of prominent glomerular, rare literature pays attention to segmentation of arteriolar vessels due to the challenge of its highly variable morphological appearances and unclear boundaries mixed with other renal tissues. To this end, we propose a cascaded detection and segmentation framework for accurate measurement and quantification analysis of renal arteriolar vessels. Specifically, we first construct renal artery detection network (RADNet) based on multi-window adaptively calibrated Swin Transformer for detecting the renal artery region, and then we design segmentation network by combining efficient channel spatial attention and vision Transformer into convolutional network (Unet) to accurately segment the renal artery wall and lumen. Finally, quantification analysis can be achieved by computing the correlation between the quantitative result and clinical information. The detection network can localize the artery regions due to utilizing multi-scale adaptively calibration method, and the segmentation network can better extract the artery wall and lumen with complex morphological appearances and unclear boundaries with the help of Transformer and efficient channel and spatial attention. Experimental results conducted on two private and one public cohorts show that the presented framework achieves significantly enhanced performance on detection and segmentation of arteriolar vessels when compared with previous state-of-the-art models. Furthermore, the proposed approach has great potential and clinical application value in the segmentation and quantification of small lesions in medical images. • Proposed pipeline optimizes detection and segmentation performance. • The proposed ECSA-SUNet achieves a powerful modeling capability. • The multidimensional quantitative analysis of renal arteries was realized. • Demonstrated that area ratio can depict the correlation with diseases. • The proposed method is proven to be superior to other methods. [ABSTRACT FROM AUTHOR]

ObjectivesManagement of abdominal aortic aneurysms (AAAs) is based on diameter. CT angiography (CTA) is commonly used, but requires radiation and iodinated contrast. Non-contrast MRI is an appealing alternative that may allow better characterization of intraluminal thrombus (ILT). This study aims to 1) validate non-contrast MRI for measuring AAA diameter, and 2) to assess ILT with CTA and MRI.Method28 patients with AAAs (diameter 50.7 ± 12.3 mm) underwent CTA and non-contrast MRI. MRI was acquired at 3 T using 1) a conventional 3D gradient echo (GRE) sequence and 2) a 3D T1-weighted black blood fast-spin-echo sequence. Two radiologists independently measured the AAA diameter. The ratio of signal of ILT and adjacent psoas muscle (ILTr = signalILT/signalMuscle) was quantified.ResultsStrong agreement between CTA and non-contrast MRI was shown for AAA diameter (intra-class coefficient > 0.99). Both approaches had excellent inter-observer reproducibility (ICC > 0.99). ILT appeared homogenous on CTA, whereas MRI revealed compositional variations. Patients with AAAs ≥5.5 cm and

A way of detecting the edge of cylindrical objects in an image with the use of the projection shadow method is proposed. The method involves the use of telecentric optics and an incoherent light source and is based on determining the object edge on the image by the position of the maximum of the derivative of the intensity dependence. The error of the proposed method is estimated theoretically and experimentally. The achieved error level in measurements of the diameter of cylindrical objects is . The result confirms the efficiency and prospects of the proposed method. [ABSTRACT FROM AUTHOR]

A new component diameter measurement system that uses a twin-hole fiber Bragg grating (THFBG) is proposed. The diameter is obtained by observing the distortion of the THFBG transmission spectrum. Furthermore, the wavelengths and the relative intensities of different troughs are extracted from the transmission spectrum to measure the diameter. It is experimentally found that the wavelengths of the troughs are independent of changes in the diameter, and the relative intensities of different troughs obtained via different calculation methods change monotonically with increasing diameter. The relative intensity ratio between different troughs is used to measure the sample diameter to eliminate the measurement interference caused by the difference in light source output intensity at different measuring points. The relationship between this relative intensity and the diameter is monotonic and nonlinear, and a maximum sensitivity of −0.5894 cm−1 is achieved when the sample diameter is 4 cm. [ABSTRACT FROM AUTHOR]

Cardiovascular disease is a severe threat to human health. The assessment of the degree of cardiovascular stenosis is very important for the diagnosis of cardiovascular disease. The segmentation of coronary angiographic images is the basis of analyzing the degree of stenosis. In this paper, a method that evaluates explicitly the degree of stenosis of blood vessels of interest is proposed. This method first extracts the vessels of interest by interactive segmentation, then thins it, and then calculates the diameter by edge intersection method. The average Dice Similarity Coefficient (DSC) value of the proposed segmentation method exceeds 92%, and the average Jaccard Similarity (JAC) value is over 86%. The area under the ROC curve value of the method is larger than the u-net method and the multiscale Hessian method. The results indicate that the interactive method can have good segmentation results and meet the general segmentation requirements. The qualitative and quantitative evaluation of the diameter measurement effect also shows that the effect of the corresponding diameter measurement method can reflect the change of the thickness of the blood vessel and basically meet the needs of clinical use.

In nuclear power plants, due to the special working environment, the status of the fuel rods will be changed by the influence of radiation. And these changes, such as diameter expansion, will cause damage to the fuel rods and even affect the safe operation of nuclear power plants. Therefore, it is necessary to accurate diameter measurement for nuclear fuel rods. This paper aims to solve the measurement problem of fuel rods, and proposes a measurement technique based on image processing. In the proposed scheme, based on Zhang's method, tangential distortion is considered to be an affecting factor at first to improve the accuracy of camera calibration. Then, a particle swarm algorithm with all-parameter adaptive mutation method is proposed for the optimization of camera parameters. Finally, a simple and convenient method to calculate pixel equivalent is designed by considering the feature extraction of corner coordinates of subpixel to accurately obtain pixel equivalents. The effectiveness of this measurement scheme is highlighted on a measuring platform. The relative error of the proposed method reaches 0.041%, and RMSE reaches 4.16 μm. Experimental results demonstrate that this approach is efficient for high-accuracy diameter measurement of fuel rods.

An optical strain gauge based on a balloon-like interferometer structure formed by a bent standard single-mode fiber combined with a 3D printer piece has been presented and demonstrated, which can be used to measure displacement. The interferometer has a simple and compact size, easy fabrication, low cost, and is repeatable. The sensor is based on the interference between the core and cladding modes. This is caused by the fiber’s curvature because when light propagates through the curved balloon-shaped interferometer region, a portion of it will be released from the core limitation and coupled to the cladding. The balloon has an axial displacement as a result of how the artwork was constructed. The sensor head is sandwiched between two cantilevers such that when there is a displacement, the dimension associated with the micro bend is altered. The sensor response as a function of displacement can be determined using wavelength shift or intensity change interrogation techniques. Therefore, this optical strain gauge is a good option for applications where structure displacement needs to be examined. The sensor presents a sensitivity of 55.014 nm for displacement measurements ranging from 0 to 10 mm and a strain sensitivity of 500.13 pm/μϵ.

High precision measurement is becoming an imperative requirement in many applications. A novel sub-pixel line-edged angle detection method based on convolutional neural network is proposed in this paper. The line edges of targets are accurately estimated by their geometric slope angles with an edge point located on the line. Specifically, the pixel level line-edged images are first obtained by image preprocessing. Then, two separate convolutional neural networks are effectively constructed to boost their discriminative capabilities for the sub-pixel line-edged angle classification. The pixel level line-shaped edge images are used as input and the final network outputs are the specific sub-pixel level line-edged angles. Finally, the sub-pixel level diameter measurements are precisely performed with the estimated angles. Compared with existing methods, the proposed method can estimate the sub-pixel line-edged angle with 0.1 degree accuracy in end-to-end way, even for the noisy images. Simulation results for angle measurement and the real-world experiment for diameter measurement reveal the validity of the proposed method. [ABSTRACT FROM AUTHOR]

• A novel area-based diameter measurement algorithm for industrial machine vision. • Calculating diameter using boundary pixel intensities. • Fast diameter measurement algorithm for machine vision applications. • Robust threshold selection to determine boundary gray level pixels. In recent years, there has been a notable surge in the utilization of industrial image processing applications across various sectors, including automotive, medical, and space industries. These applications rely on specialized camera systems and advanced image processing techniques to accurately measure working products with precise tolerances. This research presents a novel fast algorithm for measuring the diameter of a ring, employing a subpixel counting method. The algorithm classifies image pixels into two categories: full pixels and transition pixels. Full pixels reside entirely within the inner region of the workpiece, while transition pixels represent gray pixels that reside at the boundary between the workpiece and its background. To ensure accurate determination of the object area, the proposed method incorporates normalization to account for the contribution of transition pixels alongside full pixels. Subsequently, the circle area equation is employed to calculate the diameter. Moreover, a robust threshold selection method is introduced to effectively distinguish pixels with gray intensities. The experimental setup consists of an industrial camera equipped with telecentric lenses and appropriate illumination. The results demonstrate that the proposed algorithm achieves a 3–10 % improvement in accuracy compared to existing approaches. In terms of measuring sensitivity, the operational sensitivity of the proposed methodology is quantified as 1/20th of the pixel size, exhibiting an average uncertainty of 1 µm. Furthermore, the proposed method surpasses existing works by at least 12.5 % to 35 % in terms of benchmarking computing time. [ABSTRACT FROM AUTHOR]

Purpose: To investigate if imaging with intravascular ultrasound (IVUS) yields a more accurate estimate of vessel diameter and the presence of dissections than angiography after intervention in the infrapopliteal arteries.Materials and Methods: A prospective, single-center study enrolled 20 consecutive patients (mean age 74.1±12.4 years; 12 women) with infrapopliteal disease who were treated with percutaneous transluminal angioplasty (PTA; n=10) or orbital atherectomy (OA) followed by PTA (n=10). The majority of patients were hypertensive and half were diabetic. The overall lesion length was 7.3±6.3 cm, and the diameter stenosis was 80.3%±22.1%. The baseline characteristics did not differ between the groups. Vessel diameters were measured using IVUS from the internal elastic lamina (IEL) to the IEL. IVUS was performed at baseline, post PTA or OA, and post OA+PTA. Quantitative vascular angiography (QVA) and IVUS were analyzed by a core laboratory. Dissections on cine images were categorized based on the National Heart Lung and Blood Institute (NHLBI) classification, while the arc and depth were used to characterize dissections on IVUS images.Results: Mean vessel diameter by QVA was 2.9±0.6 vs 4.0±1.0 mm by IVUS according to the core laboratory (mean difference 1.1±0.9, p<0.001). On angiography, there were 7 dissections after PTA (6 C, 1 D), 1 dissection after OA (1 B), and 2 dissections after OA+PTA (1 A, 1 B; p=0.028 vs post PTA). IVUS uncovered 3.8 times more dissections than seen on angiography. There were 23 dissections after PTA (18 intima, 3 media, 2 adventitia), 12 dissections after OA (8 intima, 1 media, 3 adventitia), and 11 dissections following OA+PTA (7 intima, 1 media, 3 adventitia; p=0.425 vs PTA). Bailout stenting (all due to angiographic dissections ≥C) was necessary in 6 of the PTA cohort and none of the OA+PTA group.Conclusion: In addition to underestimating the infrapopliteal vessel diameter by ~25%, angiography underappreciated the presence and severity of post-intervention dissections vs IVUS, particularly in the OA+PTA group. [ABSTRACT FROM AUTHOR]

The features of far field diffraction phenomena on cylindrical (metal) objects of small diameters (0.01–0.5 mm) are investigated taking into account their reflective properties within the framework of the Kirchhoff–Fresnel scalar theory of light diffraction. The calculations used a screen-type cylinder model (of zero thickness). The reflected far field component was calculated by the stationary phase approximation. It is shown that when using standard information processing algorithms (valid for screen-type objects), the effect of the reflected light wave leads to a noticeable measurement error proportional to the amplitude coefficient of light reflection from the cylinder surface. To reduce its influence, we propose an algorithm for determining the diameters of such objects with increased accuracy by appropriate processing of the diffraction pattern near the angles , where is the light wavelength and is the cylinder radius. The obtained results can be used in the development of high-precision diffraction meters for thin cylindrical objects (wires, filaments, fibers). [ABSTRACT FROM AUTHOR]

OBJECTIVES Maximal aortic diameter is commonly used to assess aortic risk but poorly predicts the timing and location of dissection events in patients with connective tissue disease who undergo regular imaging surveillance. Hence, we aimed to use available surveillance computed tomography angiography (CTA) scans to investigate the correlation between 3-dimensional (3D) growth and cyclic transmural wall stress with the location of intimal tear formation. METHODS Three type B aortic dissection patients with 2 available electrocardiogram (ECG)-gated pre-dissection CTA scans and without surgical repair during the pre-dissection interval were retrospectively identified at our institution. Vascular deformation mapping was used to measure 3D aortic growth between 2 pre-dissection clinical CTA studies. In addition, we performed a computational analysis to estimate cyclic transmural wall stress in patient-specific baseline CTA geometries. RESULTS In all 3 connective tissue disease patients, the site of type B aortic intimal tear co-localized with areas of peak 3D aortic wall growth. Aortic growth was detected by clinical radiological assessment in only 1 case. Co-localization of peak transmural stress and the site of intimal tear formation were found in all cases. CONCLUSIONS Focal areas of growth and transmural wall stress co-localized with the site of intimal tear formation. These hypothesis-generating results suggest a possible new analytic pathway for a more sophisticated assessment of the factors leading to the initiation of dissection in patients with connective tissue disease. These methods could improve on current risk-stratification techniques. [ABSTRACT FROM AUTHOR]

Key comparison measurements serve as an ultimate tool of quality assurance of results. Whenever the inter-comparison results indicate inconsistency, the participating laboratory needs to take the corrective actions. Practically, the systematic errors involved in the measuring system confines the achievable accuracy. Therefore, the corrective action involves either empirically determine the influences afresh or intuitively reassigns these error values. Alternatively, an analytical method based on inter laboratory comparison results is proposed. The novelty of the proposal is considering task-specific errors in the model that is used for the analysis of interlaboratory comparison results. Without accounting the uncertainties of task-specific errors, the analysis grows complicated and even sometimes it is not feasible. To supplement the proposed method, task-specific errors due to the imperfect geometry of ring gauge, practical inability in implementing the measurement, and unattended environmental influences are explored. The proposed method is demonstrated using some internal diameter key comparison data. The systematic errors responsible for the outlier in the measurement comparison are clearly distinguished. [ABSTRACT FROM AUTHOR]

• The self-inductance variation of coil is linear to the of logarithm of rod diameter under high-frequency. • The peak frequency ω peak has the inverse relationship with conductivity. • The coefficient of peak frequency regarding diameter can be corrected by high-frequency response. • The radius and conductivity of rods is deduced using the peak-frequency and self-inductance of coil under high-frequency. The conductivity and radius are significant parameters for metallic rods, which are associated with metal composition, hardness and microstructure. Accurate conductivity and radius measurement can reflect internal structure status of metallic rod, so as to prevent accidents. The method in this paper aims at simultaneously estimating the conductivity and diameter using sweep-frequency eddy current testing (ECT). This method is an extension of the analytical solution we proposed previously. Specifically, the peak frequency of the imaginary part of the self-inductance variation has the inverse relationship with conductivity. However, the peak frequency is also affected by rod diameter. In order to decouple the conductivity and diameter of metallic, the real part of self-inductance variation have been proved to be only related to the diameter of the metallic rod under high frequency. Combining the peak frequency and real part of self-inductance variation under high frequency, the conductivity and radius can be simultaneously obtained. The experiments using standard specimen are implemented to- verify the feasibility of the method. Results illustrate the average relative errors are within 1.4%. [ABSTRACT FROM AUTHOR]

Here, it is aimed to measure and detect the iron mass of a concrete solid wall, column, floor by using of ultra-wide band radar. Electromagnetic waves boundary conditions, reflection, and refraction of waves that radiate in solid material are analysed. GPR imaging methodology and scanning types such as A, B, and C are analysed. Ultra-wide band radar imaging is used for detecting measuring the diameter of the iron material.

For a determination of the Avogadro constant by the X-ray crystal density method, the volume of a Si sphere manufactured from a Si crystal isotopically enriched in 28Si, named Si28-23Pr11, was measured at the National Metrology Institute of Japan (NMIJ). The volume was determined on the basis of diameter measurement in 2175 directions by an optical interferometer. The surface layers on the sphere were characterized by X-ray photoelectron spectroscopy and spectroscopic ellipsometry. Taking into account the effect of the surface layers on the diameter measurement, the volume of the Si core excluding the surface layers was determined with a relative uncertainty of $2.0\times 10^{\mathbf {-8}}$. The results were used to determine the Avogadro constant in 2017 by the International Avogadro Coordination project, which was used as an input datum to determine the CODATA 2017 adjusted value of the Planck constant $h$. This $h$ value will be used in the new definition of the kilogram. This paper provides details of the measurement apparatus and the uncertainty analysis of the Si core volume measurement. In addition, an approach to reduce the uncertainty in the Si core volume determination is proposed for the accurate realization of the kilogram based on the new definition at NMIJ. Details of the approach are also provided. [ABSTRACT FROM AUTHOR]

Riveted workpieces are widely used in manufacturing; however, current inspection sensors are mainly limited in nondestructive testing and obtaining the high-accuracy dimension automatically is difficult. We developed a 3-D sensor for rivet inspection using fringe projection profilometry (FPP) with texture constraint. We used multi-intensity high dynamic range (HDR) FPP method to address the varying reflectance of the metal surface then utilized an additional constraint calculated from the fused HDR texture to compensate for the artifacts caused by phase mixture around the stepwise edge. By combining the 2-D contours and 3-D FPP data, rivets can be easily segmented, and the edge points can be further refined for diameter measurement. We tested the performance on a sample of riveted aluminum frame and evaluated the accuracy using standard objects. Experiments show that denser 3-D data of a riveted metal workpiece can be acquired with high accuracy. Compared with the traditional FPP method, the diameter measurement accuracy can be improved by 50%.

Here, it is aimed to measure and detect the iron mass of a concrete solid wall, column, floor by using of ultra-wide band radar. Electromagnetic waves boundary conditions, reflection, and refraction of waves that radiate in solid material are analysed. GPR imaging methodology and scanning types such as A, B, and C are analysed. Ultra-wide band radar imaging is used for detecting measuring the diameter of the iron material. [ABSTRACT FROM AUTHOR]

Auto diameter measurement plays an important role in Czochralski method for silicon single crystals. In this paper, a novel approach based on concentric ellipses is proposed to measure the diameter of silicon single crystal. First, we analyze the concentric elliptical relationship between the heat shield and the meniscus in a captured image. Then, we further find the diameter of the crystal can be calculated by special geometric properties of concentric ellipses. According to this discovery, our approach is designed to measure the diameter of crystal in two stages. Compared to conventional techniques, our method doesn’t apply a complex circle/ellipse fitting algorithm to every image during diameter detection, which makes it suitable for real-time applications. In addition, an ellipse edge filtering algorithm is used to improve the robustness of our system. Experimental results on synthetic images and real images demonstrate that our method is efficient, accurate and robust. [ABSTRACT FROM AUTHOR]

Objectives: Dental implant failure and insufficient osseointegration are proven results of mechanical and thermal damage during the surgery process. We herein performed a comparative study of a less invasive single-step drilling preparation protocol and a conventional multiple drilling sequence. Accuracy of drilling holes was precisely analyzed and the influence of different levels of expertise of the handlers and additional use of drill template guidance was evaluated.Material and methods: Six experimental groups, deployed in an osseous study model, were representing template-guided and freehanded drilling actions in a stepwise drilling procedure in comparison to a single-drill protocol. Each experimental condition was studied by the drilling actions of respectively three persons without surgical knowledge as well as three highly experienced oral surgeons. Drilling actions were performed and diameters were recorded with a precision measuring instrument.Results: Less experienced operators were able to significantly increase the drilling accuracy using a guiding template, especially when multi-step preparations are performed. Improved accuracy without template guidance was observed when experienced operators were executing single-step versus multi-step technique.Conclusion: Single-step drilling protocols have shown to produce more accurate results than multi-step procedures. The outcome of any protocol can be further improved by use of guiding templates. Operator experience can be a contributing factor.Clinical relevance: Single-step preparations are less invasive and are promoting osseointegration. Even highly experienced surgeons are achieving higher levels of accuracy by combining this technique with template guidance. Hereby template guidance enables a reduction of hands-on time and side effects during surgery and lead to a more predictable clinical diameter. [ABSTRACT FROM AUTHOR]

In order to test the quality, to sort workpieces depending on their sizes, and to identify the different colors of workpieces and sort them, a software system of workpieces diameter measurement and color recognition based on Lab VIEW was designed. Images were collected and saved by the USB camera, the images were processed, the processing methods included image grayscale, contrast and brightness adjustment, various filtering function and so on; the workpiece diameter measurement and color recognition were implemented. Workpieces that the diameters were different from the sample can be filtrated. Through analyzing the colors of red, green and blue histograms of samples and workpieces to calculate comprehensive color difference, color recognition was realized. The screw was taken as an example, experimental results show that the system can quickly measure the workpiece diameters, has accurate recognition rate and high precision. The system has certain reference value for detecting the size of the objects and color sorting in industrial and agricultural production. [ABSTRACT FROM AUTHOR]