Automatic Orientation Research Articles

Design and experiments of an integrated device for shrimp orientation and decapitation

To realize the automatic orientation and decapitation of shrimp, an integrated device for shrimp orientation and decapitation was designed based on the shape and size characteristics of shrimp, which was mainly composed of oriented rollers, shrimp pushing boards, adaptive clamping claw and knife for the decapitation of shrimp. Three kinds of shrimp of small, medium, and large size were selected. Taking the speed of the shrimp pushing boards, the horizontal speed of the adaptive clamping claw, the rotational speed of oriented rollers and the radius of the oriented rollers as the test factors, and the success rate of the shrimp decapitation as the index, the single factor test and the orthogonal test were carried out to study the effect of each factor on the shrimp decapitation, and then the main parameters of the device were optimized. The results showed that the optimal parameter combinations of the three sizes of shrimp were the speed of shrimp pushing plates of 60mm/s, the horizontal speed of adaptive clamping claw of 70mm/s, the rotational speed of oriented rollers of 60r/min, and the radius of oriented rollers of 20mm. Under the optimal combination of parameters, the device has the highest decapitation success rate and the success rate of shrimp decapitation was 91.5% for small shrimp, 94.6% for medium shrimp, and 92.8% for large shrimp, the decapitation speed was 36pcs/min for small shrimp, 38 pcs/min for medium shrimp, and 37 pcs/min for large shrimp. Therefore, the feasibility of the device design is verified.

Design of an information-computer system for the automated modeling of systems for automatic orientation of production objects in the machine and instrument industries

An information-computer system has been developed for the automated modeling of systems for automatic orientation of production objects, which is one of the most important and complex creative flexible production systems of machine and instrument engineering. The proposed information-computer system for automated modeling of systems of automatic orientation of production objects is an effective tool for solving an important task of a scientific and applied nature. Its use makes it possible to increase the speed and efficiency of information processing and to make correct and well-founded decisions when determining the composition and method of organization of systems of automatic orientation of production objects. The structure of this information-computer system is a specific set of software and hardware and information and telecommunication tools and interactive functional modules. This structure reproduces a certain paradigm that conditions the integrity and integration of the information-computer system for automated modeling of systems for automatic orientation of production objects in flexible production systems. In addition, uniformity, extensibility, the possibility of modernization and changeability of software components, protection of information from unauthorized access and preservation of commercial secrets are ensured according to international criteria for evaluating the protection of the computer system. Neuro-fuzzy network information processing and computer vision algorithms have been implemented for automatic identification of production objects and orientation devices, which are components of automatic orientation systems of production objects. The developed information-computer system processes information in real time with high accuracy and speed

Design of robotic arm for the porcelain bushing in substation

With the development and the application popularization of artificial intelligence robot technology and 5G technology, a robotic arm is designed and developed for rinsing porcelain bushing in high voltage substation in this paper. Firstly, the components and implementation of robotic arm are presented, subsequently, a circular cleaning structure with a 120-degree split is proposed to rinse the porcelain bushing. Secondly, a two-stage simple and effective method to realize automatic orientation is proposed utilizing photoelectric switches. Moreover, a prototype of robotic arm with control system is developed based on the regime switching function, and the result of edge computing is transmitted by 5G technology. Finally, feasibility and effectiveness of the robotic arm are verified in the Nanjing power grid. The case study manifests that the robotic arm developed by the proposed method in the paper can achieve efficient rinsing and all the corresponding information can be transmitted preciously. The proposed method lays a foundation for wide application of cleaning robot in high voltage substation.

Orientation system of solar panels based on a robot manipulator

Solar energy is one of the most interesting renewable energies, as it is an inexhaustible natural accumulation. The electrical energy generated depends on the performance of photovoltaic panels that is based on the direction of sunlight. The position of the sun changes during the day, even during the year, which imposes a system of automatic orientation of solar panels for this purpose, several devices have been proposed and marketed. In our article, we focus on the adaptation of a robot manipulator for orientation and positioning of solar panels, applying for the control system, the model of the robot controller. First, we present the robotic system, which is a well-mastered, and his order was the subject of several studies and applications, and the model of the robot used for controlling the system. Finally, we give the simulation results in two modes: Mode fixed facing south with an inclination of 45° and the robot tracking mode following the elevation and azimuth movements with two decoupled movement. The results found show a gain in terms of solar energy collected measured about 51%.

Design and Implementation of the Positioning and Directing Precision Seeder for Cucurbita Ficifolia Seeds

Highlights Identification of large seed plantule point direction were realized using machine vision. A large seed orientation seeder is designed to achieve automatic orientation seeding of large seeds. The directional seeding success (deflection angle of less than 15°) rate was 92.89%. The qualified rate of positioning and orientation reached 87.80% Abstract. A consistent plantule point and a uniform distribution of cucurbit seeds are required for factory seedlings and grafting. However, precision sowing Cucurbita ficifolia seeds automatically with a positioning and orientation method is difficult due to their large, non-spherical shape. To overcome this challenge, a machine vision-based precision seeder was designed specifically for Cucurbita ficifolia seeds. To achieve consistent seed placement and orientation at a 45° angle, a method using machine vision and precise seed positioning and orientation has been proposed. The plantule point location was determined by comparing the pixel values at both ends of seed. The positioning and orientation module was developed to achieve seeding with same orientation of plantule point and located in the center of the plug tray. Finally, the positioning and orientation precision seeder for seeds were tested and evaluated. The results showed that the accuracy rate of seed plantule point identification and the success rate of the seeds orientation actuator were 97.56% and 100.00%. 95.21% of seeds achieved a deflection angle of less than 15°. The germination port of 96.06% of the seeds is distributed in a circle with the center of the hole as the center and a radius of 10 mm. The qualified rate of positioning and orientation reached 87.80%, and the sowing efficiency was about 3750 grains/h. The results showed that the seeder achieves the consistent orientation of the germination port of seeds and sows the seeds in the center of the hole. This finding provides technical support for seedling testing and large-scale factory seedlings. Keywords: Cucurbita ficifolia seeds, Machine vision, PLC control, Positioning and orientation, Precision seeder.

Phase-field modeling of brittle fracture in functionally graded materials using exponential finite elements

This study introduces a novel implementation of exponential finite element (EFE) shape functions within the phase field model for predicting fracture responses in functionally graded materials (FGMs). The proposed approach utilizes an effective fracture toughness concept to analyze load–displacement responses and crack paths in various examples of FGMs. To optimize computational efficiency, a mixed scheme combining both linear finite element (LFE) and EFE shape functions is employed. Specifically, only the critical elements are corrected using EFE shape functions. Comparative analysis of simulation results against converged outcomes demonstrates the superiority of the EFE scheme, even when employing coarser meshes. The EFE approach accurately predicts load–displacement responses and crack paths for the evaluated examples. The proposed implementation offers a reliable and efficient tool for studying fracture behavior in FGMs. Despite the higher integration schemes and orientation requirements associated with EFE shape functions, the additional computational effort is found to be negligible. Implementation aspects include a staggered iteration scheme, a hybrid tension–compression splitting scheme, and automatic orientation of EFE shape functions.

Isolator Detection in Power Transmission Lines using Lightweight Dept-wise Convolution with BottleneckCSP YOLOv5

The detection of insulators is of great importance in power transmission lines. This is because accurate detection ensures reliability and continuity of energy transmission, preventing line interruptions. The proposed method in this study utilizes the DWB-YOLOv5 (Dept-wise convolution with BottleneckCSP YOLOv5) model to effectively detect insulators, contributing to the safe and uninterrupted operation of power lines. In the suggested approach, the DWB-YOLOv5 model is employed to detect insulators. The bottleneckCSP module enhances the accuracy of targets at various scales, while the depth-wise c2onvolution module assists in reducing the model's complexity. Images undergo preprocessing steps such as automatic orientation and resizing. The preprocessed images are fed into the DWB-YOLOv5 model to extract deep features, perform object detection, and conduct classification. The insulator detection model obtained through this method exhibits a minimum of 8.53% better mean average precision (mAP) performance compared to existing methods. This study represents a significant step towards ensuring the safe and uninterrupted operation of power transmission lines. Accurate detection of insulators facilitates the smooth functioning of lines, ensuring reliability and continuity in energy transmission. The proposed method offers important advantages such as high accuracy, lightweight design, and efficiency.

On automatic determination of quasicrystal orientations by indexing of detected reflections.

Automatic crystal orientation determination and orientation mapping are important tools for research on polycrystalline materials. The most common methods of automatic orientation determination rely on detecting and indexing individual diffraction reflections, but these methods have not been used for orientation mapping of quasicrystalline materials. The paper describes the necessary changes to existing software designed for orientation determination of periodic crystals so that it can be applied to quasicrystals. The changes are implemented in one such program. The functioning of the modified program is illustrated by an example orientation map of an icosahedral polycrystal.

Design and Study of a Spindle-Shaped Fry Head-to-Tail Orientation Device

The head-to-tail orientation of spindle-shaped fry is an important part of automated vaccine injection. The fry’s automatic orientation helps reduce labor and improve efficiency during the automated injection. This paper designed an electromagnetic vibration fry orientation device for grass carp fry, measured its friction characteristics with three different materials in scales and against scales, analyzed the kinematic characteristics of the fry on the electromagnetic vibration feeder, and clarified the main factors affecting fry transport. It used the trough’s inclination angle, amplitude, and material as the test factors, whereas the orientation success rate and orientation rate were used as the evaluation index. Orthogonal combination tests were carried out with 90–150 mm grass carp fry as the research object to obtain reasonable parameter combinations. The results showed that the best orientation effect was achieved when the surface of the trough was a silicone film with many bumps, the inclination of the plate spring was β = 15°, the inclination of the trough plane was θy = −4°, and the amplitude A = 0.7 mm. In this parameter combination, the directional device was tested and verified. The targeted success rate was ε = 95.5%, and the direction rate was η = 0.87 tail/s. The device could meet the requirements of the head and tails during the mechanized injection of the fry.

Identification of tomato leaf diseases based on multi-channel automatic orientation recurrent attention network

In existing deep learning-based tomato leaf disease identification algorithms, there are two factors limit the performance: 1) noise can be easily generated during image acquisition, transmission, and processing, which makes it challenging to extract disease features; 2) inter-class similarity and intra-class variability of tomato leaf diseases make it challenging to identify disease images. A new identification model for tomato leaf disease is proposed in this paper to solve the above problems. First, an Asymptotic Non-Local Means algorithm (ANLM) is introduced to reduce the image's noise interference and to decrease the difficulty of extracting tomato leaf disease features in the identification network. Then, a Multi-channel Automatic Orientation Recurrent Attention Network (M−AORANet) is proposed to extract abundant disease features. An automatic orientation attention network is designed to locate lesion sites on tomato leaves. The fine multiscale feature is extracted and recycled to solve the problem of inter-class similarity and intra-class variability identification of tomato leaf diseases. Experimental results on 7493 images demonstrated that the identification accuracy of M−AORANet reached 96.47%, which outperformed other current identification networks in comparison experiments. It can effectively provide decision information for tomato disease identification systems in precision agriculture.

The methodology of the archival aerial image orientation based on the SfM method

Nowadays, archival images find increasingly finding their way into geospatial applications, namely, among others, multi-temporal analysis, documentation reconstruction or change detection. It is, therefore, necessary to determine the images' external orientation elements that allow the images' position to be reconstructed in the assumed reference system. This paper aims to present a methodology for the extended evaluation of the automatic orientation process of archival images based on the commonly used Structure-from-Motion (SfM) approach. The work carried out presents: (1) the influence of parameter selection on the accuracy, number and distribution of tie points in the descriptor matching process at the pairwise image bundling stage using the descriptor matching approach together with the use of Random sample consensus filtered triangulation (RANSAC), (2) analyses of the reciprocal orientation quality of the images on detected points (control points) in the bundle adjustment process using simultaneous verification of the matching quality on check points, and (3) analysis of the external orientation accuracy. Points detected and matched using the SIFT algorithm on archival images of a fragment of Warsaw from 1986, 1994, and 2014 were used as reference data. A comparative analysis of the obtained results with the data obtained using the algorithms implemented in the Agisoft Metashape software (standard approach) shows that the relative orientation reprojection RMSE is about 4 time better, and detected points are even more robust.

Robotic-Assisted Automatic Orientation and Insertion for Bronchoscopy Based on Image Guidance

Due to the large number and complex structure of bronchial branches, frequent orientation and insertions during bronchoscopy are likely to cause surgeon fatigue and errors. Therefore, we designed a robotic-assisted automatic intervention system (RAIS) based on image guidance, which aims to realize automatic orientation and insertion of bronchoscope, for improving the intelligence and efficiency of the bronchoscopy. To realize image guidance, we proposed a highly robust and accurate lumen center detection method, which combines deep learning-based object detection and histogram back-projection. With image guidance of lumen center, RAIS automatically completes the orientation and insertion of bronchoscope. The results of human phantom lung experiments show that the accuracy and recall of proposed lumen center method can respectively reach 94.12% and 86.23% when the bronchoscope is being localized by RAIS. Moreover, the results show that it is feasible to automate the orientation and insertion of bronchoscope using RAIS, which is more efficient than the manual operating the robot. The proposed RAIS could replace the surgeon in performing a large number of repetitive and simple tasks, which can efficiently reduce the workload of the surgeon and improve the safety and efficiency of the procedure.

Design and Experiment of a Garlic Orientation and Orderly Conveying Device Based on Machine Vision

Aiming at the problem that the existing garlic-root-cutting equipment requires the orientation and orderly conveying of garlic, a garlic orientation and orderly conveying method based on machine vision and mechanical orientation mechanisms was proposed and a garlic orientation and orderly conveying device was designed. To realize garlic posture recognition, garlic and garlic roots were used as detection objects, the YOLOv5s objection detection model was used to establish a garlic feature detection model, and the model was trained. The garlic orientation and orderly conveying device was developed and a garlic posture recognition test and garlic orientation and orderly conveying test were completed. The test results show that the success rate of posture recognition is 98.67% and the average accuracy rate of the garlic deviation angle is 99.11%. When the conveying speed is 95 mm⋅s−1 and the rotating speed is 55 rpm, the orientation success rate is 95.6% and the conveying efficiency reaches 75 garlic per minute, which meets the design requirements. The accuracy of the garlic posture recognition method and the rationality of the garlic orientation and orderly conveying device design are verified, and the automatic orientation and orderly conveying of garlic is realized.

MAPPING WITH SKYSAT IMAGES

Abstract. The very high-resolution space imagery now competes with some functions that were previously solved with aerial images. Several very high-resolution optical satellites with a ground sampling distance (GSD) of 1 m and smaller are currently active. Not all of these satellites take images worldwide. Nevertheless, it is not a problem to obtain up-to-date satellite images with a very high resolution. Mapping projects not only need to consider access and quality, but also cost-effectiveness. Of course, the economic framework conditions are decisive for the decision as to whether space images or very high-resolution satellite images should be used. With a total 21 SkySat satellites, low-cost satellites with very high resolution have changed the economic conditions. To keep costs and weights down, the Skysat satellites were not designed to offer the best direct geo-referencing performance, but this problem can be solved by automatic orientation in relation to existing orthoimages.In North Rhine-Westphalia, the cadastral maps must be checked at regular intervals to ensure that the buildings are complete. A test project examined whether this is possible with SkySat images. The geometric conditions and the image quality with the effective ground resolutions are investigated. Experiences from earlier publications could not be used. First the specific problem had to be solved, the resolution of the SkySat images was improved by lowering the satellite orbit altitude from 500 km to 450 km and by a better super resolution with 0.50 m ground sampling distance for the SkySat Collect orthoimages and in addition Planet improved their generation of Collect images. The required standard deviation of the object details of 4 m was achieved clearly as the effective ground resolution of 0.5 m if the angle of incidence is below 20°.

The Techniques of Cultural Heritage: Literature Review

Documentation of cultural heritage is basically a computerized or digital representation of objects contains the realistic portrayal of objects in 2.5 or 3D and other details. It is an unquestionable reality that the most vital thing for transmitting cultural heritage to posterity is a delicate documentation. Up to the present there have been numerous advancements in documentation of cultural heritage through technology development, and contemporary documentation techniques have progressed speedily. In time, current techniques have turned out to be desirable over conventional methods in engineering in the existent state and in assurance of disfigurements and preparation of measured drawing projects of historical edifices. Over the most recent ten years, direct 3D documentation techniques are very well known and that great advancement. Generally several main geomatics approaches are using for documentation , in first approach, image based such as close range photogrammetry, unmanned aerial vehicles, infrared (IR) images, second approach are non-image-based such as conventional measurements, terrestrial laser scanning, and In third approach, many researcher are using hybrid method that companied between different techniques. With ongoing improvements in PC and information technologies, this notable customary method has been change with digital close-range photogrammetry. This new technique offers us new open doors, for example, automatic orientation and procedure of the measurement, create of 3D vector information, advanced ortho-image and digital surface model. Laser scanning is another innovation that lately has turned out to be progressively well known for documentation which gives exceptionally thick 3D points on an object surface with high exactness. Also, the 3D model and ortho-photo can be effortlessly created utilizing produced 3D point clouds and recorded digital pictures. This paper gives an overview about the techniques related with documentation of cultural heritage and the uses of cultural heritage.

Deformation mechanisms of Al thin films: In-situ TEM and molecular dynamics study

Molecular dynamics (MD) is a simulation method regularly used for examining the mechanical properties of materials on an atomic level. Despite many reasonable results obtained by this method, it remains unclear how well an MD simulation can reproduce the results of a specific experiment. Thin aluminum-based films were deformed in-situ in a transmission electron microscope (TEM). Grain boundary processes were identified as the primary deformation mechanism, and grain rotations during deformation were confirmed by automatic orientation maps. Tensile deformation of Al-based thin films with columnar grains corresponding to the material structure observed in the experiment was then simulated using MD. Several main attributes of the simulation were found to match the experimental results. The effect of grain orientation on intragranular dislocation activity was observed by TEM and confirmed by MD simulations.

Towards a Fleet of Robots for Orientation, Imaging, and Morphometric Analyses of Planktonic Foraminifera

Morphometric shell measurements help to quantify the evolutionary patterns of planktonic foraminifera (marine, calcite-secreting, and floating protists). The study of shell variations of these organisms requires observations at high stratigraphic resolution, which entails morphometric measurements from thousands of specimens. The collection of such data is time-consuming because specimens need to be oriented prior to imaging. In our studies about menardiform, globorotalids through time automatic devices were developed to orientate and image specimens under incident light. A first prototype—Automated Measurement system for shell mORphology (AMOR)—was realized in 2009 and was proven to be advantageous for gathering morphometric data. AMOR consists of a motorized universal tilting stage enabling an automatic orientation of specimens in a multicellular slide under a motorized binocular microscope. After the collection of images from the oriented specimens, shell parameters can be extracted and analyzed using separate digital imaging and morphometric software. AMOR was strongly tuned to Globorotalia menardii, a species with a quasi-symmetrical biconvex geometry in a keel view and often with a non-circular periphery in an equatorial view. Improvements of the software driving AMOR now allow the orientation of spiro- and umbilico-convex profiles and with circular forms in an equatorial view such as in phylogenetically related species like Globorotalia miocenica and Globorotalia multicamerata. Program AMOR v. 3.28 was given more flexibility using a scripting language for automatic control of the Windows graphical user interface. This approach was used to allow combinations of fix orienting functions in AMOR, which released us from reprogramming of the sophisticated LabView code. Scripting of core functions enables developing “portfolios” of adapted recipes for processing the morphologies that are beyond the menardiform morphogroup. To further expand on this concept, a follow-up robot—System AMOR 2—was completed in March 2020. It integrates the modified hardware, a newer digital camera, the updated software (AMOR v. 4.2), and improved functions. The present contribution describes the development from old AMOR to its newer twin, with the perspective of building a fleet of robots for the imaging of the oriented foraminifera in parallel.

Identification of Tomato Leaf Diseases Based on Multichannel Automatic Orientation Recurrent Attention Network

Identification of Tomato Leaf Diseases Based on Multichannel Automatic Orientation Recurrent Attention Network

Inter- and Intraobserver Repeatability of Myocardial Flow Reserve Values Determined with SPECT Study Using a Discovery NM530c Camera and Corridor 4DM Software.

Background: Myocardial blood flow (MBF) and flow reserve (MFR) examination, especially useful in the diagnosis of multivessel coronary artery disease (CAD), can be assessed with a cadmium-zinc-telluride (CZT) SPECT gamma camera, as an alternative to the expensive and less available PET. However, study processing is not free from subjective factors. Therefore, this paper aims to evaluate intra- and interobserver repeatability of MBF and MFR values obtained by the same operator and two independent operators. Methods: This study included 57 adult patients. MBF and MFR were assessed using a Discovery NM530c camera in a two-day, rest/dipyridamople protocol, using 99mTc-MIBI. Data were processed using Corridor4DM software, twice by one operator and once by another operator. Results: The repeatability of the assessed values was quite good in the whole myocardium, LAD and LCX vascular territories, but was poor in the RCA territory. Conclusions: The poor repeatability of MBF and MFR in RCA vascular territory can be explained by poor automatic orientation of the heart axis during post-processing and a so-called “cardiac creep” phenomenon. Better automatic heart orientation and introduction of automatic motion correction is likely to drastically improve this repeatability. In the present state of the software, PET is better for patients requiring assessment of MFR in the RCA territory.

Research and design of double position conducting resin automatic Slitter

With the expansion of the application of electronic technology such as LCD, the demand for conductive adhesive strip, which is the basic component related to it, is increasing, and the requirements for the accuracy of rubber strip are also higher. For this reason, the defects of low precision and low efficiency of the existing conductive adhesive Slitter are analyzed, and a new scheme of double position automatic Slitter is proposed. This paper analyzes and compares various layout and structure forms, adopts gantry layout structure, researches and adopts automatic feeding system, image recognition and orientation automatic correction system, accompanying pressing mechanism, and realizes automatic double film feeding, orientation automatic correction, automatic station conversion and shearing function. After trial production and test, the automatic Slitter designed in this paper is stable in operation, and its shearing accuracy and production efficiency are significantly improved.