Coordinate Errors Research Articles

Dependence of the Coordinate Measurement Error of Geometric Elements’ Shape Characteristics on the Control Point Number

Dependence of the Coordinate Measurement Error of Geometric Elements’ Shape Characteristics on the Control Point Number

Robust Resource Allocation Algorithm for Energy-Harvesting-Based D2D Communication Underlaying UAV-Assisted Networks

Energy efficiency (EE) is a significant performance indicator in unmanned aerial vehicle (UAV)-assisted communication networks for providing a balance between power consumption minimization and transmission rate maximization. However, most of the current works focus on the transmission rate maximization under perfect channel state information (CSI) and exact coordinate information, which is too ideal in practical systems due to channel estimation errors and coordinate estimation errors. Thus, robust resource allocation algorithms with imperfect CSI and coordinate information are critically important to reduce users’ outages and improve system robustness. In this article, a robust EE maximization problem with channel uncertainties and coordinate uncertainties is formulated for an energy harvesting-based device-to-device (D2D) communication underlaying UAV-assisted network under some necessary constraints, which involve the outage probability constraints of ground terminals, the flight altitude constraint of the UAV, the minimum harvested energy constraints of D2D users, and the transmission time constraint. Both radio resource allocation and the flight altitude are jointly optimized based on the worst case approach. The considered nonconvex problem is transformed into a convex one by exploiting variable relaxation and variable substitution approaches. The Lagrange dual theory is used to derive the closed-form expressions of robust resource allocation. Simulation results demonstrate the effectiveness of the proposed algorithm by comparing it with the benchmark algorithms in terms of EE and robustness.

Quality of Radar Direction-Finding via Conical Scanning

Introduction. Conical scanning is applied for optimizing hardware resources in new devices, as well as when upgrading existing systems. All this explains the relevance of studying this type of direction finding systems.Aim. To adjust and complement the known calculation relations for the variance of direction finding results – an indicator of the quality (accuracy) of direction finding, as well as to determine the possibilities of optimizing direction finding and automatic object tracking processes.Materials and methods. Factors limiting the accuracy of direction finding via conical scanning were analyzed using spectral analysis. Mathematical modeling followed by statistical processing of quantitative results makes it possible to determine the conditions under which the influence of certain factors is predominant, as well as the conditions under which adjustment (completion) of the known calculation relations is required. The specified conditions are the errors at which the objects of direction finding are tracked. New calculation relations for the mentioned adjustment were determined by the methods of statistical radio engineering.Results. The validity of the calculation relations found is confirmed by mathematical modeling. Calculations and modeling lead to the need to optimize parameters for automatic object tracking systems.Conclusion. The study shows that, when choosing parameters for auto-tracking systems with conical scanning, it is important to implement object tracking not with minimal, but rather with optimized tracking errors in angular coordinates, which are to be estimated during direction finding. Moreover, the optimized errors (the values of static errors and the most probable values of the dynamic tracking errors) will require adjustment of the known analytical estimates for the variance of the direction finding results – the qualitative indicator of the direction finder (accuracy indicator). The determined analytical relationships allow such an adjustment to be performed, leading to an increased variance estimate by 10 dB.

Influence of coordinate system establishment error on tooth profile deviation measured by standard polar coordinate method on gear measuring center

This paper presents the influence of the coordinate system establishment error on the tooth profile deviation with the standard polar coordinate method (SPCM) for a gear measuring center (GMC). The tooth profile deviation measurement model of the SPCM and the coordinate system establishment error model are established. The influences of the coordinate system establishment errors in the X and Y directions on the measurement accuracy of involute tooth profile are simulated on a Digital Twin of GMC (DTGMC) platform, and the model is verified by experiments. The research shows that the influences of the coordinate system establishment errors in different directions on the tooth profile deviation are different, which should be taken seriously. It is found that by changing the error direction, the influence of the measurement error caused by the coordinate system establishment error can be offset, providing a new method to improve the measurement accuracy of the gear tooth profile with the SPCM.

Study of the Error Caused by Camera Movement for the Stereo-Vision System

The stereo-vision system plays an increasingly important role in various fields of research and applications. However, inevitable slight movements of cameras under harsh working conditions can significantly influence the 3D measurement accuracy. This paper focuses on the effect of camera movements on the stereo-vision 3D measurement. The camera movements are divided into four categories, viz., identical translations and rotations, relative translation and rotation. The error models of 3D coordinate and distance measurement are established. Experiments were performed to validate the mathematical models. The results show that the 3D coordinate error caused by identical translations increases linearly with the change in the positions of both cameras, but the distance measurement is not affected. For identical rotations, the 3D coordinate error introduced only in the rotating plane is proportional to the rotation angle within 10° while the distance error is zero. For relative translation, both coordinate and distance errors keep linearly increasing with the change in the relative positions. For relative rotation, the relationship between 3D coordinate error and rotation angle can be described as the nonlinear trend similar to a sine-cosine curve. The impact of the relative rotation angle on distance measurement accuracy does not increase monotonically. The relative rotation is the main factor compared to other cases. Even for the occurrence of a rotation angle of 10°, the resultant maximum coordinate error is up to 2000 mm, and the distance error reaches 220%. The results presented are recommended as practice guidelines to reduce the measurement errors.

Accuracy analysis of 3D model of open-pit mine based on tilt photogrammetry

Mineral resources account for a large proportion in the development of national economy in China. The topography conditions around the mine site are complex, and accurate measurement of the mine topography can ensure that the mineral resources are mined safely and reasonably. The traditional mine survey has certain danger. With the advantages of flexibility and no site constraints, the UAV is equipped with a high-resolution lens and combined with tilt photogrammetry technology to obtain high-resolution images of multiple angles of the mine area and fine texture information of the feature surface in a short period of time. A total of 918 optical images were collected as raw data using a consumer-grade UAV equipped with a common optical lens. They were pre-processed and modeled to generate a high-precision, clear-textured 3D model of the study area. The root mean square of the pixel is 0.53 after aerial triangulation and adjustment. Compared with the actual measured value, the mean square error of plane coordinates is ±0.1cm, and the maximum error is 0.2cm, the mean square error of height is ±0.1cm, and the maximum error is 0.2cm. The mean square error of model plane coordinates is ±2.9cm, and the maximum error is 10.2cm. The mean square error of height is ±6.4cm, and the maximum error is 8.6cm. The results show that the production model meets the requirements of relevant specifications and the use of tilt photogrammetry in hazardous areas can improve the safety of surveyors.

A hybrid coverage control for enhancing UWSN localizability using IBSO-VFA

Underwater node coverage is the basis of various applications in underwater wireless sensor network (UWSN). It is easy to cause the coordinates of underwater nodes drift affected by water flow action. Some sparsely deployed underwater nodes may form coverage holes, which makes it impossible to locate underwater targets effectively. Combined with the water flow situation, this paper proposes an improved brain storm optimization integrated with virtual force algorithm (IBSO-VFA) for improving UWSN coverage performance. After analyzing the water jet model and the resultant force along Z axis, the velocity components of east, north and depth directions can be derived, which can reveal the coordinate evolution model of drifted underwater nodes under water flow action. Underwater nodes present non-uniform distribution of partly sparse and partly dense coverage, even with a lot of coverage holes. Inspired by the virtual force algorithm, the drifted underwater nodes are driven to their relative communicable positions. Meanwhile, the brain storm optimization has been improved and applied to avoid falling into local coverage optimum by pure VFA. Based on the node maximum coverage, the dual mapping of signal domain and localizability domain is established in consideration of ranging and coordinate errors. Finally, a comprehensive performance test is conducted to evaluate IBSO-VFA performance in terms of coverage rates, k-coverage and localizability area. The results indicate that the IBSO-VFA can maximize the UWSN coverage and localizability performance. The proposed IBSO-VFA can provide a close-to-practical coverage model for drifted underwater nodes, and can provide a theoretical basis for ocean information perception in UWSN.

The dependence of coordinate measurements error of the geometric elements shape characteristics of products on the control points number

The issues of estimating the error of coordinate measurements of the shape characteristics of geometric elements of products depending on the number of control points, taking into account a given confidence probability, are considered. Analytical models are proposed for estimating the error based on a priori data, similar to estimating uncertainty by type B. The correspondence of model and experimental results is verified by the Monte Carlo method using a specially developed program in VBA and the library functions of the Statistical Analysis package of the Microsoft Excel program. Such a characteristic of the shape of the part as roundness is investigated. The influence of the parameters of regular structures associated with the features of the technological processes of manufacturing the part on the parameters of the distribution function of the coordinates of the control points is revealed. Fourier analysis is used to identify and quantify regular structures on the surface of the part. The sources of error that have a significant impact on the results of measurements of the shape characteristics of geometric elements of products are given. Based on the results of statistical calculations, the dependence of the measurement error of the shape characteristics on the number of control points is analyzed, the scope of application of analytical formulas for estimating the error of single measurements for a given confidence probability is determined. The article is intended for specialists in the field of practical coordinate metrology and related fields.

A novel load-dependent sensor placement method for model updating based on time-dependent reliability optimization considering multi-source uncertainties

An effective sensor network with an appropriate sensor configuration is the first step of model updating to obtain the actual structural response. However, sensor placements based on inherent structural characteristics (such as mode shapes) alone or their optimizations only with deterministic data are unlikely to provide very good results. Therefore, using a non-probabilistic theory to characterize the uncertainty in the uncertainty propagation process for model updating, this study proposes a time-dependent, reliability-based method for the optimal load-dependent sensor placement considering multi-source uncertainties. Due to the limitations of the uncertain parameters obtained using probabilistic or statistical methods, the uncertainties tackled in this study that includes those from structural properties and measurement processes are regarded as interval variables. Using the first-passage theory in the overall time history, different crossing situations of the reduced time history responses (that is, the modal coordinates) with respect to the full ones are constructed. The difference between the modal coordinates of the reduced and the full models is defined as the objective of the optimization, which indicates the matching level. Based on the time-dependent reliability-based index and the errors of deterministic modal coordinates between the reduced and full models, the multi-objective optimization is solved using NSGA-II. A detailed flowchart of the proposed method is given, and its effectiveness is verified by two simulated engineering examples for model updating.

Accurate grasp detection learning using oriented regression loss

PurposeRobot automatic grasping has important application value in industrial applications. Recent works have explored on the performance of deep learning for robotic grasp detection. They usually use oriented anchor boxes (OABs) as detection prior and achieve better performance than previous works. However, the parameters of their loss belong to different coordinates, this may affect the regression accuracy. This paper aims to propose an oriented regression loss to solve the problem of inconsistency among the loss parameters.Design/methodology/approachIn the oriented loss, the center coordinates errors between the ground truth grasp rectangle and the predicted grasp rectangle rotate to the vertical and horizontal of the OAB. And then the direction error is used as an orientation factor, combining with the errors of the rotated center coordinates, width and height of the predicted grasp rectangle.FindingsThe proposed oriented regression loss is evaluated on the YOLO-v3 framework to the grasp detection task. It yields state-of-the-art performance with an accuracy of 98.8% and a speed of 71 frames per second with GTX 1080Ti on Cornell datasets.Originality/valueThis paper proposes an oriented loss to improve the regression accuracy of deep learning for grasp detection. The authors apply the proposed deep grasp network to the visual servo intelligent crane. The experimental result indicates that the approach is accurate and robust enough for real-time grasping applications.

Transformacije med slovenskimi in mednarodnimi terestričnimi referenčnimi sestavi

The current Slovenian terrestrial reference frame (D96-17) is a static frame based on GNSS technology. An additional transformation connecting it with the new realisation of ETRS89 accepted by EUREF (D17) gives the D96-17 a specific character. In order to ensure a high-quality national terrestrial reference frame, connection to the current realisation of ITRS is needed. This change is particularly important in the light of the intended transition to the semi-kinematic terrestrial reference frame, supported by a national geo-kinematic model. Transformations between the current national and international terrestrial reference frames are discussed in detail in the present paper. Processes, equations, and parameters of datum transformations are given in both directions (forward and inverse), step-by-step and direct ones, rigorous and simplified (approximate). Furthermore, an analysis of coordinate differences between current Slovenian and international terrestrial reference frames and an analysis of coordinate errors for various simplifications of transformation between both reference frames are given. This allows users to choose an optimal transformation solution to meet their requirements. The role and importance of transformations under consideration in the positioning procedures and the precise navigation are also addressed.

Dimensionality-reduction-based surrogate models for real-time design space exploration of a jet engine compressor blade

Design space exploration (DSE) is a systematic analysis of designs based on parameters that are varied. DSE, however, often involves computationally expensive analyses that require large amounts of time and computer resources. To overcome this obstacle, tools and methods have been developed that allow the designer to quickly explore the design space. One such tool is surrogate modeling. A surrogate model's predictions are based off the relationship between the inputs and the outputs. If this relationship is sufficiently nonlinear, a nonlinear dimensionality reduction technique may unfold the data and create a linear relationship by discovering the data's true dimensionality. The resultant surrogate has the potential to be more accurate due to the simplified relationship between the inputs and outputs. This paper uses surrogate models based on dimensionality reduction to predict finite element analysis (FEA) nodal properties of a jet engine compressor blade. Four different dimensionality reduction methods are compared, namely PCA, KPCA, ISOMAP, and LLE. The results show that nonlinear dimensionality-reduction-based surrogate models can reduce surrogate error in sufficiently nonlinear data spaces. To measure the linearity of the manifold, a new term, called the manifold distance ratio (MDR), is introduced. Nonlinear dimensionality-reduction-based surrogate models can have less error than PCA-based surrogate models when the MDR >1.7. For our application, ISOMAP-based surrogate models decreased the mean error of the surrogate for predicting nodal stresses by 35.7% compared to PCA. The lowest error in predicting the nodal coordinates was the inverse-transform-based PCA. While all errors in nodal coordinates were small, less than 0.23%, the other linear and nonlinear algorithms had between 2.4 and 3.2 times more error.

Assessing the utility of CASP14 models for molecular replacement.

The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real‐world application. In CASP7, the metric for molecular replacement assessment involved full likelihood‐based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood‐based rigid‐body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log‐likelihood‐gain (LLG) score. This enabled multi‐copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative‐expected‐LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X‐ray, NMR or cryo‐EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

Research on quality detection method for axis-hole interference fit based on laser ultrasound

The interference fit quality determines the equipment’s service performance. In this work, interference fit assembly quality was evaluated using a laser ultrasonic method, including the assembly state of the interference fit. The power spectral density was used to calculate the power of the guided waves, and an interference assembly state evaluation method was proposed. Contact edge micro-cracks were identified by acquiring the full-field waveform propagation diagram, and these cracks were located by coupling the scanning area with the crack location. The center coordinate error for crack detection, which can basically determine the exact crack location, ranged between 0.09 mm and 0.15 mm. The length and width measurement errors ranged from 0.01 mm to 0.04 mm and 0.02 mm to 0.09 mm, respectively. The relationship curve between the guided wave power and interference was obtained experimentally. This method provides a new method for detection of the interference assembly structure state and the micro-cracks.

Evaluation of model refinement in CASP14.

We report here an assessment of the model refinement category of the 14th round of Critical Assessment of Structure Prediction (CASP14). As before, predictors submitted up to five ranked refinements, along with associated residue-level error estimates, for targets that had a wide range of starting quality. The ability of groups to accurately rank their submissions and to predict coordinate error varied widely. Overall, only four groups out-performed a "naïve predictor" corresponding to the resubmission of the starting model. Among the top groups, there are interesting differences of approach and in the spread of improvements seen: some methods are more conservative, others more adventurous. Some targets were "double-barreled" for which predictors were offered a high-quality AlphaFold 2 (AF2)-derived prediction alongside another of lower quality. The AF2-derived models were largely unimprovable, many of their apparent errors being found to reside at domain and, especially, crystal lattice contacts. Refinement is shown to have a mixed impact overall on structure-based function annotation methods to predict nucleic acid binding, spot catalytic sites, and dock protein structures.

Refraction error correction of Airborne LiDAR Bathymetry data considering sea surface waves

Airborne Light Detection And Ranging (LiDAR) Bathymetry (ALB) has an unparalleled advantage in integrated sea-land measurements, especially in the acquisition of topographic data in shallow water areas. Sea surface waves are an important factor affecting the quality of ALB data. This paper presents a method that strictly corrects the sea surface wave-induced refraction error for each seabed laser pulse without any complex modeling of the sea surface. In this method, an adaptive neighborhood selection method is first used to calculate the normal sea surface at the moment when a laser pulse enters the water, and then a laser pulse refraction error correction model considering sea surface waves is constructed. The distance condition equation, the angle condition equation and the coplanar condition equation are established based on Snell's law and the geometric relationship among the incident laser pulse, the normal vector of the wavy sea surface and the actual refracted ray in order to calculate the coordinates of each laser point at the seabed after refraction error correction. The experimental results show that sea surface waves have a significant impact on the three-dimensional point cloud coordinates of the underwater topography. Even in calm sea conditions, the plane coordinate displacement error of the seabed point caused by the sea surface waves may reach the meter level, and the depth coordinate displacement error can also exceed 0.2 m. The corrected displacement errors of the planimetric coordinates are significantly greater than the corrected displacement errors of the depth coordinates, which can effectively improve the quality of the ALB data.

Improvement of UAV Positioning Performance Based on EGNOS+SDCM Solution

The article presents the results of research on multi-SBAS (multi-satellite-based augmentation system) positioning in UAV (unmanned aerial vehicle) technology. For this purpose, a new solution was developed for combining the UAV position navigation solution from several SBAS systems. In this particular case, the presented linear combination algorithm is based on the fusion of EGNOS (European geostationary navigation overlay service) and SDCM (system of differential correction and monitoring) positioning to determine the resultant UAV coordinates. The algorithm of the mathematical model uses weights of measurements in three ways, i.e., Variant I, the reciprocal of the number of tracked satellites from a single SBAS solution; Variant II, the inverse square of mean coordinate errors from a single SBAS solution; and Variant III, the reciprocal of UAV flight speed from a single SBAS solution. The research experiment used real GNSS (global navigation satellite system) navigation data recorded by the VTOL unmanned platform. The test flight was made in April 2020 in Poland, near Warsaw. Based on the developed research results, it was found that the highest accuracy of UAV positioning was obtained when using the weighting model for Variant II. In the weight model of Variant II, the accuracy of the solution of the UAV position increased by 1–2% for the horizontal components and 19–22% for the vertical component h, concerning the results obtained from the weighing Variants I and III. It is worth noting that the proposed research model significantly improves the results of determining the ellipsoidal height h. Compared to the arithmetic mean model, determining the h component in the Variant II weight model is improved by about 23%. The paper also shows the advantage of EGNOS+SDCM positioning over EGNOS positioning alone in determining the accuracy of the vertical component h. The obtained research results show the significant advantages of the multi-SBAS positioning model in UAV technology.

2.85 and 2.99 Å resolution structures of 110 kDa nitrite reductase determined by 200 kV cryogenic electron microscopy

Cu-containing nitrite reductases (NiRs) are 110 kDa enzymes that play central roles in denitrification. Although the NiRs have been well studied, with over 100 Protein Data Bank entries, such issues as crystal packing, photoreduction, and lack of high pH cases have impeded structural analysis of their catalytic mechanisms. Here we show the cryogenic electron microscopy (cryo-EM) structures of Achromobacter cycloclastes NiR (AcNiR) at pH 6.2 and 8.1. The optimization of 3D-reconstruction parameters achieved 2.99 and 2.85 Å resolution. Comprehensive comparisons with cryo-EM and 56 AcNiR crystal structures suggested crystallographic artifacts in residues 185–215 and His255′ due to packing and photoreduction, respectively. We used a newly developed map comparison method to detect structural change around the type 2 Cu site. While the theoretical estimation of coordinate errors of cryo-EM structures remains difficult, combined analysis using X-ray and cryo-EM structures will allow deeper insight into the local structural changes of proteins.

NEURAL ACTIVITY AND LANDING BIOMECHANICS: EXPLORING THE RELATIONSHIPS BETWEEN THE BRAIN, BODY, AND ACL INJURY-RISK

Background:Anterior cruciate ligament (ACL) injuries predominantly occur via non-contact mechanisms, secondary to motor coordination errors resulting in aberrant frontal plane knee loads that exceed the thresholds of ligament integrity. However, central nervous system processing underlying high injury-risk motor coordination errors remain unknown, limiting the optimization of current injury reduction strategies.Purpose:To evaluate the relationships between brain activity during motor tasks with injury-risk loading during a drop vertical jump.Methods:Thirty female high school soccer players (16.10 ± 0.87 years, 165.10 ± 4.64 cm, 63.43 ± 8.80 kg) were evaluated with 3D biomechanics during a standardized drop vertical jump from a 30 cm box and peak knee abduction moment was extracted as the injury-risk variable of interest. A neuroimaging session to capture neural activity (via blood-oxygen-level-dependent signal) was then completed which consisted of 4 blocks of 30 seconds of repeated bilateral leg press action paced to a metronome beat of 1.2 Hz with 30 seconds rest between blocks. Knee abduction moment was evaluated relative to neural activity to identify potential neural contributors to injury-risk.Results:There was a direct relationship between increased landing knee abduction moment and increased neural activation within regions corresponding to the lingual gyrus, intracalcarine cortex, posterior cingulate cortex, and precuneus (r2= 0.68, p corrected < .05, z max > 3.1; Table 1 & Figure 1).Conclusion:Elevated activity in regions that integrate sensory, spatial, and attentional information may contribute to elevated frontal plane knee loads during landing. Interestingly, a similar activation pattern related to high-risk landing mechanics has been found in those following injury, indicating that predisposing factors to injury may be accentuated by injury or that modern rehabilitation does not recover prospective neural control deficits. These data uncover a potentially novel brain marker that could guide the discovery of neural-therapeutic targets that reduce injury risk beyond current prevention methods.Figure 1:The drop vertical jump landing assessment (left) and neural activity associated with abduction loading (right).

A data complementary method for sound source localization based on four-element microphone array groups

Data loss or distortion has adverse effects on sound source localization (SSL) accuracy and stability. Based on the sound source azimuth estimation algorithm, this paper establishes a model of a single four-element main microphone array, and proposes a data complementary method of SSL. The calculation formula of sound source coordinates is derived from the main array. Then, the effectiveness of the proposed algorithm is verified by the study of array parameters. Besides the sound velocity and elevation angle, the array parameters also include the distance between two array elements. Array groups are established surrounding the main array on the horizontal plane, through which the localization data are collected and complementarily processed, so as to relocate the sound source. The results show that the coordinate error rate against the theoretical data is approximately 5% and the error rate of the angle is approximately 0.5%. The SSL efficiency is well guaranteed.