scholarly journals Towards Automatic Detection of Precipitates in Inconel 625 Superalloy Additively Manufactured by the L-PBF Method

Materials ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4507
Author(s):  
Piotr Macioł ◽  
Jan Falkus ◽  
Paulina Indyka ◽  
Beata Dubiel
Keyword(s):  
Chemical Composition ◽  
Information Gain ◽  
Signal To Noise Ratio ◽  
Automatic Segmentation ◽  
Automatic Detection ◽  
Inconel 625 ◽  
Detection And Identification ◽  
Inconel 625 Superalloy ◽  
Segmentation Of Images ◽  
Precipitated Phases

In our study, the comparison of the automatically detected precipitates in L-PBF Inconel 625, with experimentally detected phases and with the results of the thermodynamic modeling was used to test their compliance. The combination of the complementary electron microscopy techniques with the microanalysis of chemical composition allowed us to examine the structure and chemical composition of related features. The possibility of automatic detection and identification of precipitated phases based on the STEM-EDS data was presented and discussed. The automatic segmentation of images and identifying of distinguishing regions are based on the processing of STEM-EDS data as multispectral images. Image processing methods and statistical tools are applied to maximize an information gain from data with low signal-to-noise ratio, keeping human interactions on a minimal level. The proposed algorithm allowed for automatic detection of precipitates and identification of interesting regions in the Inconel 625, while significantly reducing the processing time with acceptable quality of results.

scholarly journals Characterization of the Structure, Mechanical Properties and Erosive Resistance of the Laser Cladded Inconel 625-Based Coatings Reinforced by TiC Particles

Materials ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2225
Author(s):  
Aleksandra Kotarska ◽  
Tomasz Poloczek ◽  
Damian Janicki
Keyword(s):  
Laser Cladding ◽  
Inconel 625 ◽  
Matrix Composites ◽  
Erosion Rates ◽  
Laser Cladding Process ◽  
Composition Variation ◽  
The Matrix ◽  
Reinforcing Material ◽  
Inconel 625 Superalloy

The article presents research in the field of laser cladding of metal-matrix composite (MMC) coatings. Nickel-based superalloys show attractive properties including high tensile strength, fatigue resistance, high-temperature corrosion resistance and toughness, which makes them widely used in the industry. Due to the insufficient wear resistance of nickel-based superalloys, many scientists are investigating the possibility of producing nickel-based superalloys matrix composites. For this study, the powder mixtures of Inconel 625 superalloy with 10, 20 and 40 vol.% of TiC particles were used to produce MMC coatings by laser cladding. The titanium carbides were chosen as reinforcing material due to high thermal stability and hardness. The multi-run coatings were tested using penetrant testing, macroscopic and microscopic observations, microhardness measurements and solid particle erosive test according to ASTM G76-04 standard. The TiC particles partially dissolved in the structure during the laser cladding process, which resulted in titanium and carbon enrichment of the matrix and the occurrence of precipitates formation in the structure. The process parameters and coatings chemical composition variation had an influence on coatings average hardness and erosion rates.

scholarly journals Automatic Detection of Discrimination Actions from Social Images

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 325
Author(s):  
Zhihao Wu ◽  
Baopeng Zhang ◽  
Tianchen Zhou ◽  
Yan Li ◽  
Jianping Fan
Keyword(s):  
Action Recognition ◽  
State Of The Art ◽  
Automatic Detection ◽  
Experimental Results ◽  
Practical Approach ◽  
Detection And Identification ◽  
Art Methods ◽  
Image Set ◽  
Social Images ◽  
Relationship Identification

In this paper, we developed a practical approach for automatic detection of discrimination actions from social images. Firstly, an image set is established, in which various discrimination actions and relations are manually labeled. To the best of our knowledge, this is the first work to create a dataset for discrimination action recognition and relationship identification. Secondly, a practical approach is developed to achieve automatic detection and identification of discrimination actions and relationships from social images. Thirdly, the task of relationship identification is seamlessly integrated with the task of discrimination action recognition into one single network called the Co-operative Visual Translation Embedding++ network (CVTransE++). We also compared our proposed method with numerous state-of-the-art methods, and our experimental results demonstrated that our proposed methods can significantly outperform state-of-the-art approaches.

scholarly journals Automatic Detection Technology of Sonar Image Target Based on the Three-Dimensional Imaging

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Wanzeng Kong ◽  
Jinshuai Yu ◽  
Ying Cheng ◽  
Weihua Cong ◽  
Huanhuan Xue
Keyword(s):  
Data Storage ◽  
3D Imaging ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Automatic Detection ◽  
Classification Model ◽  
Image Detection ◽  
Practical Applications ◽  
Sonar Image ◽  
Detection Technology

With 3D imaging of the multisonar beam and serious interference of image noise, detecting objects based only on manual operation is inefficient and also not conducive to data storage and maintenance. In this paper, a set of sonar image automatic detection technologies based on 3D imaging is developed to satisfy the actual requirements in sonar image detection. Firstly, preprocessing was conducted to alleviate the noise and then the approximate position of object was obtained by calculating the signal-to-noise ratio of each target. Secondly, the separation of water bodies and strata is realized by maximum variance between clusters (OTSU) since there exist obvious differences between these two areas. Thus image segmentation can be easily implemented on both. Finally, the feature extraction is carried out, and the multidimensional Bayesian classification model is established to do classification. Experimental results show that the sonar-image-detection technology can effectively detect the target and meet the requirements of practical applications.

Применение адаптивного анизотропного диффузного фильтра для повышения качества изображения отражателей при проведении ультразвукового неразрушающего контроля

2021 ◽  
pp. 3-12
Author(s):  
Е.Г. Базулин
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Antenna Arrays ◽  
Human Factor ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Efficient Operation ◽  
Optical Images ◽  
Segmentation Methods ◽  
Segmentation Of Images

Currently, in order to increase the speed of preparing the ultrasound control protocol and reduce the influence of the human factor, systems for recognizing (classifying) reflectors based on artificial neural networks are being actively developed. For their more efficient operation, the images of the reflectors need to be worked on in order to increase the signal-to-noise ratio of the image and its segmentation (clustering). One of the segmentation methods is to process the image with an adaptive anisotropic diffuse filter, which is used to process optical images. In model experiments, the effectiveness of using this texture filter for segmentation of images of reflectors reconstructed from echo signals measured using antenna arrays is demonstrated.

scholarly journals Microstructure and Mechanical Characterization of Laser Sintered Inconel-625 Superalloy

2014 ◽  
Vol 5 ◽  
pp. 772-779 ◽  
Author(s):  
N.H. Sateesh ◽  
G.C. Mohan Kumar ◽  
Krishna Prasad ◽  
Srinivasa C.K. ◽  
A.R. Vinod
Keyword(s):  
Mechanical Characterization ◽  
Inconel 625 ◽  
Inconel 625 Superalloy

scholarly journals Information gain from isotopic contrast variation in neutron reflectometry on protein–membrane complex structures

2020 ◽  
Vol 53 (3) ◽  
pp. 800-810
Author(s):  
Frank Heinrich ◽  
Paul A. Kienzle ◽  
David P. Hoogerheide ◽  
Mathias Lösche
Keyword(s):  
Experimental Design ◽  
Soft Matter ◽  
Lipid Membrane ◽  
Information Gain ◽  
Signal To Noise Ratio ◽  
Scattering Length ◽  
Model Parameters ◽  
Membrane Complex ◽  
Simple Model System ◽  
Molecular Components

A framework is applied to quantify information gain from neutron or X-ray reflectometry experiments [Treece, Kienzle, Hoogerheide, Majkrzak, Lösche & Heinrich (2019). J. Appl. Cryst. 52, 47–59], in an in-depth investigation into the design of scattering contrast in biological and soft-matter surface architectures. To focus the experimental design on regions of interest, the marginalization of the information gain with respect to a subset of model parameters describing the structure is implemented. Surface architectures of increasing complexity from a simple model system to a protein–lipid membrane complex are simulated. The information gain from virtual surface scattering experiments is quantified as a function of the scattering length density of molecular components of the architecture and the surrounding aqueous bulk solvent. It is concluded that the information gain is mostly determined by the local scattering contrast of a feature of interest with its immediate molecular environment, and experimental design should primarily focus on this region. The overall signal-to-noise ratio of the measured reflectivity modulates the information gain globally and is a second factor to be taken into consideration.

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