Volumetric imaging of flame refractive index, density, and temperature using background-oriented Schlieren tomography

Liu, Hecong; Huang, Jianqing; Li, Lei; Cai, Weiwei

doi:10.1007/s11431-020-1663-5

Cited by 22 publications

(18 citation statements)

References 49 publications

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“…This work is also valuable for other tomographic modalities, e.g. background-oriented Schlieren tomography [25].…”

Section: Discussionmentioning

confidence: 99%

Laser absorption tomography based on unstructured meshing

Liu,

Peng,

Sanders

et al. 2023

Meas. Sci. Technol.

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Laser absorption tomography (LAT) is an imaging technique used to monitor gas flow and combustion processes. The measurement plane is typically discretized using square pixels in which the flow field is assumed to be uniform. This approach can introduce large discretization errors compared to a finite element mesh with linear interpolation, especially when the domain has an irregular and nonrectangular boundary. In this work, we assess the influence of triangular mesh and quadrilateral mesh schemes on reconstruction accuracy. Our theoretical analysis and numerical studies demonstrate that linear interpolation yields superior performance compared to the conventional uniform-pixel method, and the error can be reduced from 0.250 to 0.097 and 0.160 to 0.105 for triangular and quadrilateral meshes, respectively. Non-body-fitted mesh can increase error by 70% ~ 99%. The experiment also proves the superiority of body-fitted meshes with linear interpolation. Moreover, triangular mesh exhibits better noise immunity than quadrilateral mesh. The reconstruction quality appears to be insensitive to the mesh quality for the quadrilateral mesh.

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“…This work is also valuable for other tomographic modalities, e.g. background-oriented Schlieren tomography [25].…”

Section: Discussionmentioning

confidence: 99%

Laser absorption tomography based on unstructured meshing

Liu,

Peng,

Sanders

et al. 2023

Meas. Sci. Technol.

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“…Figure 4 shows a normalized integral OT image at the 101st layer height showing ROIs with potential defects due to the reduction of laser power at those specific regions highlighted inside a black box [ROI]. These regions with changes in intensity can be interpreted as anomalies that are caused by changes in temperature and energy density [26]. The entire printed cylinder consists of a total of 8 sections with ROIs in four layers each.…”

Section: Generation Of Artificial Defects By Reducing Laser Powermentioning

confidence: 99%

A Random Forest Classifier for Anomaly Detection in Laser-Powder Bed Fusion Using Optical Monitoring

Khan,

Birkhofer,

Kunz

et al. 2023

Materials

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Metal additive manufacturing (AM) is a disruptive production technology, widely adopted in innovative industries that revolutionizes design and manufacturing. The interest in quality control of AM systems has grown substantially over the last decade, driven by AM’s appeal for intricate, high-value, and low-volume production components. Geometry-dependent process conditions in AM yield unique challenges, especially regarding quality assurance. This study contributes to the development of machine learning models to enhance in-process monitoring and control technology, which is a critical step in cost reduction in metal AM. As the part is built layer upon layer, the features of each layer have an influence on the quality of the final part. Layer-wise in-process sensing can be used to retrieve condition-related features and help detect defects caused by improper process conditions. In this work, layer-wise monitoring using optical tomography (OT) imaging was employed as a data source, and a machine-learning (ML) technique was utilized to detect anomalies that can lead to defects. The major defects analyzed in this experiment were gas pores and lack of fusion defects. The Random Forest Classifier ML algorithm is employed to segment anomalies from optical images, which are then validated by correlating them with defects from computerized tomography (CT) data. Further, 3D mapping of defects from CT data onto the OT dataset is carried out using the affine transformation technique. The developed anomaly detection model’s performance is evaluated using several metrics such as confusion matrix, dice coefficient, accuracy, precision, recall, and intersection-over-union (IOU). The k-fold cross-validation technique was utilized to ensure robustness and generalization of the model’s performance. The best detection accuracy of the developed anomaly detection model is 99.98%. Around 79.40% of defects from CT data correlated with the anomalies detected from the OT data.

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“…( 13) are typically ill-posed in BOST. Therefore, the iteration-based methods are widely employed in BOST 15 . The iteration-based methods include algebraic reconstruction technique (ART), simultaneous iterative reconstruction technique (SIRT) and Landweber iteration.…”

Section: Reconstructionmentioning

confidence: 99%

“…The iteration-based methods include algebraic reconstruction technique (ART), simultaneous iterative reconstruction technique (SIRT) and Landweber iteration. Of which the ART has been proven to be better than SIRT and Landweber iteration 15 in BOST. Thus, the ART is used in this work.…”

Section: Reconstructionmentioning

confidence: 99%

A quantitative reconstruction method for background-oriented schlieren by reducing the weight matrix

Cai,

Song,

et al. 2023

Optical Metrology and Inspection for Industrial Applications X

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In the background-oriented schlieren (BOS), the 3D deflection caused by refractive index gradient is projected onto the camera imaging plane with one dimension leaved out, and sensed as a 2D displacement using the images of background with and without the flow field. In the reconstruction, instead of decomposing the 2D displacement as in previous studies, we project the elements in the BOS weight matrix to 2D. By doing so, this technique reduces memory usage and improves the reconstruction time as the number of rows in the weight matrix is decreased by a third, and the errors produced in 2D displacement decomposition are avoided.

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Volumetric imaging of flame refractive index, density, and temperature using background-oriented Schlieren tomography

Cited by 22 publications

References 49 publications

Laser absorption tomography based on unstructured meshing

Laser absorption tomography based on unstructured meshing

A Random Forest Classifier for Anomaly Detection in Laser-Powder Bed Fusion Using Optical Monitoring

A quantitative reconstruction method for background-oriented schlieren by reducing the weight matrix

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