Nondestructive Quality Control in Powder Metallurgy using Hyperspectral
Imaging
- URL: http://arxiv.org/abs/2207.12966v1
- Date: Tue, 26 Jul 2022 15:20:35 GMT
- Title: Nondestructive Quality Control in Powder Metallurgy using Hyperspectral
Imaging
- Authors: Yijun Yan, Jinchang Ren, He Sun
- Abstract summary: Contamination is one of the most headache problems which can be caused by multiple reasons.
With the use of a near-infrared HSI camera, applications of HSI for the non-destructive inspection of metal powders are introduced.
- Score: 6.912911497063973
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Measuring the purity in the metal powder is critical for preserving the
quality of additive manufacturing products. Contamination is one of the most
headache problems which can be caused by multiple reasons and lead to the
as-built components cracking and malfunctions. Existing methods for
metallurgical condition assessment are mostly time-consuming and mainly focus
on the physical integrity of structure rather than material composition.
Through capturing spectral data from a wide frequency range along with the
spatial information, hyperspectral imaging (HSI) can detect minor differences
in terms of temperature, moisture and chemical composition. Therefore, HSI can
provide a unique way to tackle this challenge. In this paper, with the use of a
near-infrared HSI camera, applications of HSI for the non-destructive
inspection of metal powders are introduced. Technical assumptions and solutions
on three step-by-step case studies are presented in detail, including powder
characterization, contamination detection, and band selection analysis.
Experimental results have fully demonstrated the great potential of HSI and
related AI techniques for NDT of powder metallurgy, especially the potential to
satisfy the industrial manufacturing environment.
Related papers
- Hyperspectral Imaging for Identifying Foreign Objects on Pork Belly [0.11249583407496218]
This study presents an automated solution for detecting foreign objects on pork belly meat using hyperspectral imaging (HSI)
A hyperspectral camera was used to capture data across various bands in the near-infrared (NIR) spectrum (900-1700 nm)
The proposed solution combines pre-processing techniques with a segmentation approach based on a lightweight Vision Transformer (ViT) to distinguish contaminants from meat, fat, and conveyor belt materials.
arXiv Detail & Related papers (2025-03-20T12:28:31Z) - A Deep Learning Approach for Pixel-level Material Classification via Hyperspectral Imaging [1.294249882472766]
Hyperspectral (HS) imaging offers advantages over conventional technologies such as X-ray fluorescence and Raman spectroscopy.
This study evaluates the potential of combining HS imaging with deep learning for material characterization.
The model achieved 99.94% classification accuracy, demonstrating robustness in color, size, and shape invariance, and effectively handling material overlap.
arXiv Detail & Related papers (2024-09-20T13:38:48Z) - Site-Controlled Purcell-Induced Bright Single Photon Emitters in Hexagonal Boron Nitride [62.170141783047974]
Single photon emitters hosted in hexagonal boron nitride (hBN) are essential building blocks for quantum photonic technologies that operate at room temperature.
We experimentally demonstrate large-area arrays of plasmonic nanoresonators for Purcell-induced site-controlled SPEs.
Our results offer arrays of bright, heterogeneously integrated quantum light sources, paving the way for robust and scalable quantum information systems.
arXiv Detail & Related papers (2024-05-03T23:02:30Z) - Accelerating Process Development for 3D Printing of New Metal Alloys [0.0]
Process mapping is crucial for determining optimal process parameters that consistently produce acceptable printing quality.
Process mapping is typically performed by conventional methods and is used for the design of experiments and ex situ characterization of printed parts.
Our method relaxes these limitations by incorporating the temporal features of molten metal dynamics during laser-metal interactions using video vision transformers and high-speed imaging.
arXiv Detail & Related papers (2023-12-29T19:46:18Z) - CINFormer: Transformer network with multi-stage CNN feature injection
for surface defect segmentation [73.02218479926469]
We propose a transformer network with multi-stage CNN feature injection for surface defect segmentation.
CINFormer presents a simple yet effective feature integration mechanism that injects the multi-level CNN features of the input image into different stages of the transformer network in the encoder.
In addition, CINFormer presents a Top-K self-attention module to focus on tokens with more important information about the defects.
arXiv Detail & Related papers (2023-09-22T06:12:02Z) - Systematic reduction of Hyperspectral Images for high-throughput Plastic
Characterization [0.0]
Hyperspectral Imaging (HSI) combines microscopy and spectroscopy to assess the spatial distribution of spectroscopically active compounds in objects.
It has diverse applications in food quality control, pharmaceutical processes, and waste sorting.
Due to the large size of HSI datasets, it can be challenging to analyze and store them within a reasonable digital infrastructure.
Recent high-tech developments in chemometrics enable automated and evidence-based data reduction.
arXiv Detail & Related papers (2023-08-28T11:38:08Z) - A comprehensive review of 3D convolutional neural network-based
classification techniques of diseased and defective crops using non-UAV-based
hyperspectral images [0.1338174941551702]
Hyperspectral imaging (HSI) is a non-destructive and contactless technology that provides valuable information about the structure and composition of an object.
Due to its wide spectral range, HSI can be a more effective tool for monitoring crop health and productivity.
With the advent of this imaging tool in agrotechnology, researchers can more accurately address issues related to the detection of diseased and defective crops.
arXiv Detail & Related papers (2023-06-15T18:02:53Z) - Evaluation of the potential of Near Infrared Hyperspectral Imaging for
monitoring the invasive brown marmorated stink bug [53.682955739083056]
The brown marmorated stink bug (BMSB), Halyomorpha halys, is an invasive insect pest of global importance that damages several crops.
The present study consists in a preliminary evaluation at the laboratory level of Near Infrared Hyperspectral Imaging (NIR-HSI) as a possible technology to detect BMSB specimens.
arXiv Detail & Related papers (2023-01-19T11:37:20Z) - Tensor Decompositions for Hyperspectral Data Processing in Remote
Sensing: A Comprehensive Review [85.36368666877412]
hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the observation and analysis of the Earth's surface.
The recent advancement and even revolution of the HS RS technique offer opportunities to realize the full potential of various applications.
Due to the maintenance of the 3-D HS inherent structure, tensor decomposition has aroused widespread concern and research in HS data processing tasks.
arXiv Detail & Related papers (2022-05-13T00:39:23Z) - Texture Characterization of Histopathologic Images Using Ecological
Diversity Measures and Discrete Wavelet Transform [82.53597363161228]
This paper proposes a method for characterizing texture across histopathologic images with a considerable success rate.
It is possible to quantify the intrinsic properties of such images with promising accuracy on two HI datasets.
arXiv Detail & Related papers (2022-02-27T02:19:09Z) - Ternary Metal Oxide Substrates for Superconducting Circuits [65.60958948226929]
Substrate material imperfections and surface losses are one of the major factors limiting superconducting quantum circuitry from reaching the scale and complexity required to build a practicable quantum computer.
Here, we examine two ternary metal oxide materials, spinel (MgAl2O4) and lanthanum aluminate (LaAlO3), with a focus on surface and interface characterization and preparation.
arXiv Detail & Related papers (2022-01-17T06:10:15Z) - Nondestructive Testing of Composite Fibre Materials with Hyperspectral
Imaging : Evaluative Studies in the EU H2020 FibreEUse Project [7.412753371103298]
hyperspectral imaging (HSI) can detect minor differences in terms of temperature, moisture and chemical composition.
This paper introduces applications of HSI for the non-destructive inspection of CFRP products.
arXiv Detail & Related papers (2021-11-04T17:01:38Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.