Data · dataset · 2025
Additive Manufacturing Powder Bed Four Types of Defects Dataset
Listed in ScienceDB
This dataset is from the powder bed image acquisition experiment in the SLM250 selective laser melting (SLM) device.
Description
During the experiment, two high-resolution cameras (model VISION3D PowerScan-5M330) were used to perform multi angle imaging of the powder bed. The powder bed substrate is a square with a side length of 250 mm × 250 mm, and the image resolution is 2448 × 2048 pixels.
Two monochrome cameras capture images from different angles to capture defect features on the powder bed. A total of 2477 powder bed images were collected in the experiment, including various artificially simulated defects, to simulate the types of defects that may occur during the actual printing process. Defect categories include: ditches (420 sheets), stacking (600 sheets), insufficient spreading (800 sheets), and craters (657 sheets).
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In addition, the dataset also includes five times the amount of data generated through random data augmentation and corresponding annotation files to improve the training performance of the model. The annotation file adopts two formats, XML
- and TXT *, to select the defect areas in each image and provide defect category and coordinate information. The annotation of each defect includes category labels and position coordinates in the image, making the dataset suitable for research on object detection and defect classification.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.16373 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Additive manufacturing 76% · Image 75% · Imaging 75%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.16373 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:field:401401 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (76%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:imaging | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |