Geometric Measurements Research Articles

Incorporating vertical dimensionality improves biological interpretation of hidden Markov model outputs

Quantifying animal movement is a central component of ecological inquiry. Movement patterns provide insights into how animals make habitat decisions in pursuit of their life‐history requirements. Within this context, animals are expected to modulate their movement when navigating landscape complexities like steep or uneven slopes. However, the analytical tendency to predict animal movement as a function of bivariate (x, y) telemetry data (i.e. 2D methods) excludes such complexities and presumes that the landscapes over which this movement occurs are completely flat. Failure to consider vertical dimensionality may inhibit quantification and interpretation of animal behaviors, such as outputs of hidden Markov models (HMMs) built upon geometric measurements of animal movement like step length and turning angle. To explore the analytical consequences of this assumption, we utilized a dataset of GPS collared pumas Puma concolor in the Santa Cruz mountains of central California. We fit HMMs using traditional 2D step lengths and turning angles and compared them to HMMs built upon movement geometries in which we incorporated vertical dimensionality (i.e. 2D+). We then used a combination of quantitative inspection of model outputs and visual evaluation in 3D rendering software to understand what new states and biological interpretations can be facilitated by using 2D+ data. We found that 2D+ HMMs outperformed 2D HMMs in their ability to explain variation in vertical dimensionality. Furthermore, 2D+ models were able to isolate distinctive behavioral states associated with vertical dimensionality, such as movements on and off ridgelines. Our results show that 2D+ techniques enable researchers to directly investigate variation in animal movement and behavioral states across complex landscapes. We discuss the implications of our results for future study of animal behavior and energetics as well as illustrate how our methods can be tractably incorporated into HMMs to enable researchers to gain greater insights into animal movement ecology.

Geometric parameters measurement for the cooling holes of turbine blade based on microscopic image sequence topographical reconstruction

The accurate analysis of the geometric parameters of the cooling holes is essential for evaluating the processing quality of the holes. However, due to the complicated structure of cooling holes, typical measuring techniques suffer from low precision, low efficiency and high cost. With the microscopic image sequence topographical reconstruction, the three-dimensional (3D) topography of realistic cooling hole samples was acquired, and its geometrical characteristics were analyzed. This work presents a focus measure operator and an adaptive window fitting approach to recovering cooling hole topography well. Compared to the standard model obtained by X-ray microscopy, the standard deviation of the profile error is less than 0.018 mm; The measured geometric parameters are nearly identical to the standard value. The results validate the precision and efficacy of the proposed method, which has the potential to replace alternative techniques for determining the geometrical parameters of cooling holes.

Characterization of the electrical properties of mammalian peripheral nerve laminae.

The intrinsic electrical material properties of the laminar components of the mammalian peripheral nerve bundle are important parameters necessary for the accurate simulation of the electrical interaction between nerve fibers and neural interfaces. Improvements in the accuracy of these parameters improve the realism of the simulation and enables realistic screening of novel devices used for extracellular recording and stimulation of mammalian peripheral nerves. This work aims to characterize these properties for mammalian peripheral nerves to build upon the resistive parameter set established by Weerasuriya et al. in 1984 for amphibian somatic peripheral nerves (frog sciatic nerve) that is currently used ubiquitously in the in-silico peripheral nerve modeling community. A custom designed characterization chamber was implemented and used to measure the radial and longitudinal impedance between 10 mHz and 50 kHz of freshly excised canine vagus nerves using four-point impedance spectroscopy. The impedance spectra were parametrically fitted to an equivalent circuit model to decompose and estimate the components of the various laminae. Histological sections of the electrically characterized nerves were then made to quantify the geometry and laminae thicknesses of the perineurium and epineurium. These measured values were then used to calculate the estimated intrinsic electrical properties, resistivity and permittivity, from the decomposed resistances and reactances. Finally, the estimated intrinsic electrical properties were used in a finite element method (FEM) model of the nerve characterization setup to evaluate the realism of the model. The geometric measurements were as follows: nerve bundle (1.6 ± 0.6 mm), major nerve fascicle diameter (1.3 ± 0.23 mm), and perineurium thickness (13.8 ± 2.1 μm). The longitudinal resistivity of the endoneurium was estimated to be 0.97 ± 0.05 Ωm. The relative permittivity and resistivity of the perineurium were estimated to be 2018 ± 391 and 3.75 kΩm ± 981 Ωm, respectively. The relative permittivity and resistivity of the epineurium were found to be 9.4 × 106 ± 8.2 × 106 and 55.0 ± 24.4 Ωm, respectively. The root mean squared (RMS) error of the experimentally obtained values when used in the equivalent circuit model to determine goodness of fit against the measured impedance spectra was found to be 13.0 ± 10.7 Ω, 2.4° ± 1.3°. The corner frequency of the perineurium and epineurium were found to be 2.6 ± 1.0 kHz and 368.5 ± 761.9 Hz, respectively. A comparison between the FEM model in-silico impedance experiment against the ex-vivo methods had a RMS error of 159.0 ± 95.4 Ω, 20.7° ± 9.8°. Although the resistive values measured in the mammalian nerve are similar to those of the amphibian model, the relative permittivity of the laminae bring new information about the reactance and the corner frequency (frequency at peak reactance) of the peripheral nerve. The measured and estimated corner frequency are well within the range of most bioelectric signals, and are important to take into account when modeling the nerve and neural interfaces.

Post-fire local buckling behaviour of cold-formed S700 high strength steel circular hollow sections under axial compression: Experiments, modelling and design

This paper presents experimental and numerical studies of the local buckling behaviour and compression resistances of cold-formed S700 high strength steel circular hollow sections (CHS) after exposure to elevated temperatures. The testing programme included post-fire material tests, initial local geometric imperfection measurements and stub column tests on ten specimens. Then, finite element models were developed to simulate the test structural responses and employed to perform parametric studies to generate further numerical data over a wide range of cross-section dimensions. Given that there are no existing design standards for high strength steel structures after exposure to elevated temperatures, the relevant ambient temperature design rules were evaluated, using post-fire material properties, for their applicability to cold-formed S700 high strength steel CHS after exposure to elevated temperatures, based on the test and numerical data. The evaluation results revealed that (i) the codified slenderness limits were generally accurate when used for cross-section classification of post-fire cold-formed S700 high strength steel CHS and (ii) although the codified design rules resulted in overall relatively accurate cross-section compression resistance predictions, the predicted resistances were conservative for cold-formed S700 high strength steel non-slender CHS after exposure to elevated temperatures of 900 °C and 1100 °C (owing to the high levels of material strain hardening) and those slender CHS (owing to the conservatism of the codified effective width methods).

Deep learning segmentation, classification, and risk prediction of complex vascular lesions on intravascular ultrasound images

BackgroundThis study aimed to access the performance of our deep learning-based model in the segmentation and classification of vascular lesions on IVUS images. MethodsA total of 5,089 IVUS frames derived from 100 patients with stable or unstable angina pectoris were retrospectively collected. Our deep learning diagnostic framework composed of two stages, image segmentation and lesion classification. Segmentation was performed using the dilated attention U-Net model. The standard classifier, ResNet18, was subsequently used to classify the lesions into six groups, plaques (fibrous, lipid, and calcified), dissections, hematomas, and thrombi. Segmentation performance was evaluated in terms of Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95), while classification was assessed based on sensitivity, specificity, area under the receiver operating characteristic curve, and F1 score. The predictive value of our proposed model for high-risk lesions based on geometric measurements was further assessed. ResultsThe segmentation performance of our model was deemed satisfactory, with average DSC values of 80.75%, 86.68%, and 79.21% demonstrated for dissections, hematomas, and thrombi, respectively. Good lesion classification performance was observed as well, with F1 scores of 94.89%, 95.91% and 96.42%, respectively. Our model further demonstrated the ability to stratify lesions at risk for dissection. ConclusionOur deep-learning diagnostic framework demonstrated accuracy in the identification, classification, and risk stratification of vascular lesions based on IVUS images. It is clinically conducive, easily adoptable, and enables the early diagnosis of complex lesions at risk of major adverse cardiovascular events.

Application of Digital Twin in Medium-Voltage Overhead Distribution Network Inspection

The paper is devoted to the digital transformation of the core engineering maintenance processes involved in medium-voltage overhead distribution network infrastructure inspection. The study presents an analysis of digital twin utilization for inspection of the infrastructure of medium-voltage overhead distribution networks. At present, the infrastructure monitoring process is still manual, and its automatization is a challenging task due to the large distances between and small dimensions of the elements involved. The proposed digital twin is employed for 3D infrastructure modeling and complex analysis based on photogrammetry and aerial scanning data processing methods. The paper describes practical use cases for these data-driven methods for specific infrastructure management processes, e.g., scheduled inspection processes, including geometrical parameter measurements and visual infrastructure element defect identification, unplanned inspection processes (state of emergency, post-storm, etc.), and vegetation management processes. The proposed method allows operations to be performed remotely without physical presence in the field. At the same time, data-driven solutions provide objective results and potential automation via machine learning algorithms, which are more profitable economically. As the proposed method allows processes to be performed remotely, these data-driven solutions offer cost-effective results for automation. The digital twin concept is applied to the Latvian medium-voltage overhead distribution network with the support of the Latvian distribution system operator “Sadales tīkls” JSC.

Improved calibration method for displacement transformation coefficient in optical and visual measurements

Optical and visual measurement technology is used widely in fields that involve geometric measurements, and among such technology are laser and vision-based displacement measuring modules (LVDMMs). The displacement transformation coefficient (DTC) of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process, and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view (FFOV). To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands, a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV. First, an image coordinate system, a pixel measurement coordinate system, and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM. In addition, marker spots in the FFOV are selected, and the DTCs at the marker spots are obtained from calibration experiments. Also, a fitting method based on locally weighted scatterplot smoothing (LOWESS) is selected, and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots. Finally, the calibrated distribution functions of the DTCs are applied to the LVDMM, and experiments conducted to verify the displacement measurement accuracies are reported. The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than ±15 µm and ±19 µm, respectively, and that for oblique displacement is better than ±24 µm. Compared with the traditional calibration method, the displacement measurement error in the FFOV is now 90% smaller. This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV, and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.

Experimental investigation of austenitic stainless steel I-section stub columns at elevated temperatures

Due to the absence of fundamental fire test data on the cross-section behaviour of stainless steel columns, an experimental investigation of stainless steel stub columns has been conducted at elevated temperatures to fill this gap. A total of six austenitic stainless steel welded I-section stub columns were isothermally tested at three different elevated temperature levels. Two stub columns were tested at room temperature as the reference group. Complementary material tests and local geometric imperfection measurements were conducted and presented herein. On the basis of the obtained experimental results, the accuracy and reliability of the design methods of the existing European fire design standard (EN 1993-1-2) and the design method of Xing et al. for cross-sectional behaviour of stainless steel columns in fire, which has been incorporated into the upcoming version of EN 1993-1-2, are evaluated. It is concluded that, compared to the existing design rules of EN 1993-1-2, the design method of Xing et al. can provide safe and reliable cross-sectional resistance predictions for the tested austenitic stainless steel I-section stub columns.

The Reconstruction of the Creation of the Holy Crown

Determining the place and time of an artefact’s origination starts with archaeometry surveys. The aim of the study of the Holy Crown is to characterise in detail the parts of the crown – the frame, the filigree and the sockets, i.e. the metal parts – and the decorations (enamel, gemstones, beads), to determine the exact composition of the materials and to discover the place of origin. Archaeometry also includes the reconstruction of the technical and technological processes associated with artefacts. The absolute age of the artefacts can be determined using organic materials such as adhesives. This is basically a natural science. If we include the auxiliary sciences - photo-optical data recording, 3D modelling, which allows us to continue the study on the computer – it is possible to determine the relative date and place of the crown parts, using parallels with applied art, palaeography, etc. To date, no systematic archaeometry study has been carried out on the Holy Crown. There have been photographs, geometric measurements, visual inspections and descriptions by jewellers and engineers. If we want to write a scientific summary, we have a lot to draw on. The present article is such a summary, in which we attempt to reconstruct the technology of the Holy Crown, with the aim of pointing out the need for a complete archaeometry study.

Efficient Geometry Surface Coding in V-PCC

In recent video-based point cloud compression (V-PCC), 3D point clouds are projected onto 2D images and compressed by High-Efficiency Video Coding (HEVC). However, HEVC was originally designed for natural visual signals, which is a suboptimal framework for point clouds. Therefore, there are still problems in geometry information compression in V-PCC: (1) The distortion based on the sum of squared error (SSE) in the existing rate-distortion optimization (RDO) is inconsistent with the geometric quality measurement; (2) The existing prediction cannot explore the fixed relationship between the corresponding far layer and near layer depth, which means that the far layer depth can be always not less than the corresponding near layer depth. In this paper, we present an efficient geometry surface coding (EGSC) method for V-PCC to address the problems. Firstly, an error projection (EP) model is designed to establish the relationship between the SSE-based distortion and the geometry quality metric. Secondly, an EP-based RDO is employed to improve the geometry information compression by estimating the point normals with gradients. Finally, an occupancy-map driven scheme is proposed to improve the prediction accuracy of merge modes. Experimental results show that the proposed method achieves an average of over 10% bit-rate saving compared with the V-PCC reference software.

Geometric Dimension Measurement Method for Bolster Spring Based on Three-Dimensional Laser Point Clouds

Geometric Dimension Measurement Method for Bolster Spring Based on Three-Dimensional Laser Point Clouds

Research on the Real-Time Detection Method for Image Processing – Based Civil Structure Crack

Early discovery of civil structure crack facilitates timely treatment, such as repair, reinforcement and grouting. The image processing – based rapid and accurate detection method for civil structure crack brings important research value. In view of complicated construction site of civil project and complex and diversified civil structure, existing method cannot realize crack detection and geometric measurement accurately. Therefore, this article researches the real-time image processing-based detection method for civil structure crack. Bilateral filtering algorithm was used to finish smoothing processing. Crack edge of civil structure was extracted with interpolation calculation – based subpixel edge detection algorithm, to obtain more accurate crack edge position. Civil structure crack was detected based on end-to-end object detection network YOLO. The effectiveness of the model built was verified according to experimental results.

Data Fusion of Non-destructive Testing Methods for Bridge Deck Condition Assessment

Background: Highway agencies explore the use of non-destructive testing (NDT) for assessing the condition of their infrastructure in the most cost-effective manner. NDTs can provide as-built construction quality, as well as in service condition assessment especially for older structures where some critical information and/or maintenance records are often not available. In many cases, the use of NDTs requires “ground true” data for either calibration or validation. Surveys for obtaining such information is often challenging for in service structures, time consuming and costly. Aim: Objective of this paper is to present a data fusion approach for forensic investigation of bridge decks, in which Ground Penetrating Radar (GPR) is used to assess the current condition combined with a Laser Scanner system to verify the bridge design features. Methods: The data fusion approach proposed in this study considers using GPR based condition data combined with geometric measurements of the bridge deck obtained from the Laser Scanner system. Such novel fusion approach permits to more accurately measure the current bridge deck conditions in terms of thickness of the bridge deck and rebar depth to assess deterioration. Furthermore, detection of variations in the rebar depth suggested the implementation of a correction procedure for the reflection amplitude of the GPR signal based on true rebar depths instead of the two-way travel time, which is commonly applied. Results: This innovative analysis approach provided a more refined assessment of delaminated areas in the bridge deck. The data fusion and suggested analysis methodology was tested on a pre-stressed concrete bridge in Italy. Discussion: The approach proposed in this study can be used elsewhere for assessing the condition of bridge decks. Conclusion: The merging of such methods is particularly valuable for bridges were construction drawing and records may not be available, and/or there is potential concern of a deviation between design and as-built characteristics (i.e., where quality assurance and quality control records may be questionable).

Investigations into the local buckling and post-buckling behaviour of fixed-ended hybrid I-section stub columns with slender web

It has been known that thin plate can carry loads considerably more than the buckling loads. This phenomenon is defined as the post-buckling behaviour, which is affected by material properties, geometric dimensions and boundary conditions of the plate. Hybrid I-section is a design concept where flanges are made of high strength steel and web is made of lower steel grade. In order to investigate the effect of slender web on the local buckling and post buckling of hybrid I-section under pure compression, experimental studies of twelve fixed-ended I-section stub columns with slender web were conducted. Tensile coupon tests and initial local geometric imperfection measurement were carried out before stub column tests. Experimental and theoretical methods for determining the critical local buckling load of plate elements were discussed, followed by a post-test finite element analysis to investigate the effects of stub column length and sectional steel combination on the buckling behaviour. Based on the experimental and numerical results, it was observed that for specimens which web plate failed by elastic local buckling, the ultimate test loads are affected by the web strength grade, indicating that the unbuckled portion of slender web plate still provides the post-buckling strength for I-section stub columns even after yielding. By comparing the existing design methods with the numerical ultimate loads, it was found that the Eurocode 3 gives the less scattered predictions than the North American code, Australian code and Chinese code, as well as the existing direct strength method and continuous strength method.

Fabrication of Rigid Polyurethane Foam Lumbar Spine Model for Surgical Training using Indirect Additive Manufacturing

Lumbar model is an artificial bone that is commonly used in surgical training to simulate working with the human-like bone for the trainer. The common lumbar model is made of rigid polyurethane (PU) foam and is produced using casting. However, the current lumbar model is expensive and has limitations in representing the real human lumbar, especially in geometry, visuals, and haptics. Therefore, an alternative method of fabricating lumbar models made of rigid polyurethane for surgical training using indirect additive manufacturing will be investigated in this paper. The proposed indirect additive manufacturing is a combination of 3D printing and casting methods. The main process of this method is started by fabricating a mold made of polyvinyl alcohol (PVA) using fused deposition modeling (FDM) 3D printing and subsequently casting PU foam material into the 3D printed PVA mold. Accordingly, the aim of this study is to find the optimized casting process parameters, especially for injecting the material into the mold, to achieve a better quality of lumbar model. The study was conducted using a Design of Experiment (DoE) Taguchi Orthogonal Array to optimize the casting process. The geometrical measurements of middle end-plate depth, upper end-plate width, spinal canal width, spinal canal depth, and lower pedicle length show the error ranged from 0.14% to 0.85%. The average porosity, measured from the body, lamina, and spinous, was found to be non-uniform. It is ranged from 19.58% to 21.94% on the middle part and 39.78% to 45.41% on the subsurface of lumbar model. The density was increased by 64.89% compared to the reference open molded PU foam.

Evaluation of impacts of the occupation, compatibility and adequacy process applied to buildings in residential yards on the construction site code of Palmas city – Tocantins state (TO).

The aim of the present study is to evaluate the progress of the occupation process applied to residential yards of Palmas City – Tocantins State (TO) in the light of the legislation providing on parameters and guidelines for residential buildings in this municipality. Aerial and satellite images, as well as tools of the geographic information system (GIS), at high resolution standards, were used for data processing and collection. Study site encompassed yards 407 North, 504 South and the Bertaville Sector, which are located in different regions of the city and at different occupation stages. Seeking to attest to the potential of the generated products in terms of photointerpretation, Geometric and geographic accurate measurements were turned into field images in order to attest to the photo-interpretation potential of the generated products. Impacts of rainwater surface runoff on the study site were evaluated based on urban index data, occupancy rate, built-up areas, waterproofing rates and urban voids, confronted with construction site code provisions.

A More Posterior Tibial Tubercle (Decreased Sagittal Tibial Tubercle–Trochlear Groove Distance) Is Significantly Associated With Patellofemoral Joint Degenerative Cartilage Change: A Deep Learning Analysis

To perform patellofemoral joint (PFJ) geometric measurements on knee magnetic resonance imaging scans and determine their relations with chondral lesions in a multicenter cohort using deep learning. The sagittal tibial tubercle-trochlear groove (sTTTG) distance, tibial tubercle-trochlear groove distance, trochlear sulcus angle, trochlear depth, Caton-Deschamps Index (CDI), and flexion angle were measured by use of deep learning-generated segmentations on a subset of the Osteoarthritis Initiative study with radiologist-graded PFJ cartilage grades (n= 2,461). Kruskal-Wallis H tests were performed to compare differences in PFJ morphology between subjects without PFJ osteoarthritis (OA) and those with PFJ OA. PFJ morphology was correlated with secondary outcomes of mean patellar cartilage thickness and mean patellar cartilage T2 relaxation time using linear regression models controlling for age, sex, and body mass index. A total of 1,626 knees did not have PFJ OA, whereas 835 knees had PFJ OA. Knees without PFJ OA had an increased (anterior) sTTTG distance (mean ± standard deviation, 11.1 ± 12.8 mm) compared with knees with PFJ OA (8.4 ± 12.7 mm) (P < .001), indicating a more posterior tibial tubercle in subjects with PFJ OA. Knees without PFJ OA had a decreased sulcus angle (127.4° ± 7.1° vs 128.0° ± 8.4°, P= .01) and increased trochlear depth (9.1 ± 1.7 mm vs 9.0 ± 2.0 mm, P= .03) compared with knees with PFJ OA. Decreased patellar cartilage thickness was associated with decreased trochlear depth (β= 0.12, P= .002) and increased CDI (β= -0.07, P < .001). Increased patellar cartilage T2 relaxation time was correlated with decreased sTTTG distance (β= -0.08, P= .01), decreased sulcus angle (β= -0.12, P= .04), and decreased CDI (β= -0.12, P < .001). PFJ OA, patellar cartilage thickness, and patellar cartilage T2 relaxation time were shown to be associated with the underlying geometries within the PFJ. This large longitudinal study highlights that a decreased sTTTG distance (i.e., a more posterior tibial tubercle) is significantly associated with PFJ degenerative cartilage change. Level III, retrospective comparative prognostic trial.

Quantifying the Influence of Surface Texture and Shape on Structure from Motion 3D Reconstructions

In general, optical methods for geometrical measurements are influenced by the surface properties of the examined object. In Structure from Motion (SfM), local variations in surface color or topography are necessary for detecting feature points for point-cloud triangulation. Thus, the level of contrast or texture is important for an accurate reconstruction. However, quantitative studies of the influence of surface texture on geometrical reconstruction are largely missing. This study tries to remedy that by investigating the influence of object texture levels on reconstruction accuracy using a set of reference artifacts. The artifacts are designed with well-defined surface geometries, and quantitative metrics are introduced to evaluate the lateral resolution, vertical geometric variation, and spatial-frequency information of the reconstructions. The influence of texture level is compared to variations in capturing range. For the SfM measurements, the ContextCapture software solution and a 50 Mpx DSLR camera are used. The findings are compared to results using calibrated optical microscopes. The results show that the proposed pipeline can be used for investigating the influence of texture on SfM reconstructions. The introduced metrics allow for a quantitative comparison of the reconstructions at varying texture levels and ranges. Both range and texture level are seen to affect the reconstructed geometries although in different ways. While an increase in range at a fixed focal length reduces the spatial resolution, an insufficient texture level causes an increased noise level and may introduce errors in the reconstruction. The artifacts are designed to be easily replicable, and by providing a step-by-step procedure of our testing and comparison methodology, we hope that other researchers will make use of the proposed testing pipeline.

Eliminating the Influence of Support Conditions on Geometric Shape Measurements of Large Crankshafts of Marine Engines

This paper presents an analysis of the possibility of determining the geometric deviations of large crankshafts of engines using both conventional and alternative fuels. Experimental tests were carried out on a test stand adapted to measure crankshafts seated with their main journals on a set of fixed supports with the possibility of height positioning and using a reference measuring system. A comparative assessment of the results was made for a selected crankshaft using the intercorrelation factor ρ, whose value ranged from 0.8982 to 0.9751. It was concluded that the proposed procedures can be useful in assessing of the geometric condition of the crankshafts with axial position deviations and with limited possibilities of their detection resulting from the adopted support conditions with a set of supports positioned at different heights. Experimental tests were supplemented with FE-analyses of the crankshaft supported at multiple locations and loaded with deviations in the position of the main journal axes.

Least squares based geometric error measurement for sparse view CT: a 2D simulation study

X-ray computed tomography (CT) is considered as one of the most common techniques in non-destructive testing and is also an essential and important method in the field of dimensional measurement. For high-precision measurement task scenarios, geometric errors due to the instability of the CT motion equipment cannot be ignored and need to be accurately measured and corrected. In-situ testing of large objects such as geotechnical materials, mechanical assemblies, metal weldments and concrete specimens also requires high-precision CT imaging of their interiors to obtain information of interest. The rotation of the scanning parts for these large in-situ tests and sparse-view scanning mode also makes it difficult to measure geometric errors. This paper therefore proposes a method for simultaneous measurement of geometric errors based on a priori information for in-situ testing characteristics. This method is capable of measuring geometric errors in sparse view projections with a length accuracy of 0.1 mm and an angular accuracy of radians in 0.5 seconds per angle, as the simulation results show. The reconstruction results show that this level of geometric error measurement accuracy provides a dimensional measurement accuracy of 0.01 mm for the internal structure. The data for the simulation experiments in this paper are generated from real concrete data by noisy simulation.